The Cluster Active Archive: Studying the Earth's Space Plasma Environment (Astrophysics and Space Science Proceedings)

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Author: Harri Laakso | Matthew Taylor | C. Philippe Escoubet

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Astrophysics and Space Science Proceedings

The Cluster Active Archive Studying the Earth’s Space Plasma Environment

Harri Laakso Editor ESA/ESTEC, Noordwijk, The Netherlands

Matthew G.T.T. Taylor Editor ESA/ESTEC, Noordwijk, The Netherlands

C. Philippe Escoubet Editor ESA/ESTEC, Noordwijk, The Netherlands

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Editors Dr. Harri Laakso European Space Agency European Space Research & Technology Centre (ESTEC) Keplerlaan 1 2200 AG Noordwijk Netherlands [email protected]

Dr. C. Philippe Escoubet European Space Agency European Space Research & Technology Centre (ESTEC) Keplerlaan 1 2200 AG Noordwijk Netherlands [email protected]

Dr. Matthew Taylor European Space Agency European Space Research & Technology Centre (ESTEC) Keplerlaan 1 2200 AG Noordwijk Netherlands [email protected]

ISSN 1570-6591 e-ISSN 1570-6605 ISBN 978-90-481-3498-4 e-ISBN 978-90-481-3499-1 DOI 10.1007/978-90-481-3499-1 Springer Dordrecht Heidelberg London New York Library of Congress Control Number: 2009934513 c Springer Science+Business Media B.V. 2010 ° No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Cover design: eStudio Calamar S.L. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)

Preface

Magnetospheric physics started more than 50 years ago when many of the first satellites carried detectors to explore the space environment around the Earth and made plenty of new discoveries. The first findings inspired the development of a plethora of scientific satellites in the 1960s and 1970s exploring near-Earth space, which was found to have several distinct regions with their own structural and dynamical characteristics. Since then magnetospheric physics has remained a strong space science discipline, not only for its own sake but also because near-Earth space provides us with a unique space laboratory where we can investigate physical processes of tenuous collisionless plasmas with in-situ instruments and apply the resulting understanding to physical phenomena observed in more exotic environments of the Solar System and of the Universe. For long time magnetospheric research was carried out only by means of single spacecraft. In the 1970s the science community realized that one needs coordinated simultaneous observations from several satellites in order to make a major step forward in magnetospheric and space plasma physics. In particular the ISEE (three satellites), GEOS (two satellites) and DE (two satellites) programs provided many new discoveries that single spacecraft measurements could not achieve. In particular it was the dual spacecraft constellation of ISEE-1 and ISEE-2 that offered the first opportunity to improve the understanding of spatio-temporal features in physical processes of space environment while the other previous missions were separated by very large distances and were on different orbits, so one could not separate spatial and temporal features. In early 1980s the science community started dreaming about the next generation of multi-satellite constellation mission, the culmination of which came in 1982 when a group of scientists proposed a four-satellite mission, called Cluster, to ESA. After the assessment studies, the Cluster mission, together with the SOHO mission, were selected as the first cornerstone of the ESA’s Horizons 2000 Programme in 1986. Unfortunately, after 10 years of hard work the Cluster satellites were dramatically destroyed by the failure of the first flight of Ariane 5 on 4 June 1996. However, it was decided soon after that the mission was of such high importance to the science community that the satellites and payload must be rebuilt, and 4 years later the four Cluster spacecraft were successfully launched in pairs on two Soyuz rockets in July and August 2000. After 1 year of successful operations, the mission was extended

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Preface

for an additional 35 months, up to December 2005. Later the mission was further extended for 4 years until the end of 2009, and a new extension proposal has been submitted to request further operations beyond 2009. During the first extension, ESA decided to establish the Cluster Active Archive (CAA) to contain all processed and validated high-resolution scientific data, as well as raw data, calibration data and documentation from all the Cluster instruments. This is essential in order to preserve all Cluster observations in a stable, long-term archive for scientific analysis well beyond the end of the mission. The CAA activities started in 2004 and 2 years later in February 2006, the CAA opened services to the community. The Cluster mission has held science workshops twice a year since autumn 2001, which has helped bring together scientists to compare and exchange their observations and begin new collaborations. Before the CAA, scientists got access to the Cluster observations via their personal contacts with the instrument Principal Investigators and Co-Investigators. Now and in the future, the CAA provides the primary access route to the Cluster observations. Soon after the CAA opening it was realized that while some of the Cluster datasets are quite easy to use, there are plenty of complex datasets whose usage may not always be obvious. Therefore it was decided to organize a school for the users of the CAA datasets, which was organized together with the 15th Cluster science workshop in order to attract as many users as possible. The details of this and other workshops can be found at the CAA website http://caa.estec.esa.int/. The 15th Cluster workshop, attended by 120 people, was held in Hotel Playa la Arena (Puerto Santiago), Tenerife, Canary Islands, on 9–15 March 2008. The workshop provided the attending community with an in-depth overview of the CAA data products and tools. In addition, attendees were able to discuss with instrument team developers, the core CAA team and software developers. The packed schedule included presentations of instrument datasets, software tools and the CAA infrastructure and was interspersed with invited scientific talks and several dedicated science sessions on the bow shock, solar wind, magnetopause and cusp, the magnetotail and inner magnetosphere. The fact that the workshop/school was hosted in the same location as the accommodation was fundamental in the success of the meeting, allowing attendees to continue working with colleagues and discussing work in and around the workshop hours. This book contains presentations made at the workshop, including several articles about the CAA and its datasets as well as a few overview papers on the Cluster mission. In addition all participants were offered an opportunity to publish their scientific results on solar wind/magnetosheath, magnetopause, and magnetotail, presented during the workshop in this book. We would like to thank the following people for their contributions in reviewing the articles in this book: O. Alexandrova, A. Allen, M. André, T. Asikainen, ˚ A. Asnes, R. Benson, J. Blecki, J. Borovsky, D. Burgess, J. Cao, N. CornilleauWehrlin, P. Daly, I. Dandouras, J. Davies, M. Dunlop, J. Eastwood, S. Elkington, A. Eriksson, J. Faden, A. Fazakerley, J. Fennell, R. Friedel, T. Fritz, S. Fung, E. Gamby, V. Génot, M. Goldstein, E. Grigorenko, B. Grison, M. Hapgood,

Preface

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C. Harvey, R. Horne, C. Jacquey, Y. Khotyaintsev, L. Kistler, H. Kucharek, G. Le, E. Lucek, J. McFadden, S. Milan, F. Mozer, J. Mukherjee, H. Opgenoorth, C. Owen, G. Parks, M. Parrot, A. Pedersen, C. Perry, J. Pickett, P. Puhl-Quinn, J. Rae, J.L. Rauch, A. Retino, A. Roux, V. Sergeev, A. Tjulin, K. Torkar, K. Trattner, A. Walsh, Y. Wang, J. Weygand, J. Wild, and Q. Zong. May 2009

Harri Laakso, Matthew G.T.T Taylor, and Philippe Escoubet

View on the Tenerife Island

Contents

Preface .. . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .

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Part I Products and Services of the Cluster Active Archive 1

Cluster Active Archive: Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . H. Laakso, C. Perry, S. McCaffrey, D. Herment, A.J. Allen, C.C. Harvey, C.P. Escoubet, C. Gruenberger, M.G.G.T. Taylor, and R. Turner

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ASPOC Data Products in the Cluster Active Archive . . . . . . . . .. . . . . . . . . . . 39 K. Torkar and H. Jeszenszky

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Cluster Ion Spectrometry (CIS) Data in the Cluster Active Archive (CAA) . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . 51 I. Dandouras, A. Barthe, E. Penou, S. Brunato, H. Rème, L.M. Kistler, M.B. Bavassano-Cattaneo, A. Blagau, and the CIS Team

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Digital Wave Processor Products in the Cluster Active Archive .. . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . 73 K.H. Yearby, H.St.C. Alleyne, S.N. Walker, I. Bates, M.P. Gough, A. Buckley, and T.D. Carozzi

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EDI Data Products in the Cluster Active Archive . . . . . . . . . . . . .. . . . . . . . . . . 83 E. Georgescu, P. Puhl-Quinn, H. Vaith, M. Chutter, J. Quinn, G. Paschmann, and R. Torbert

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The EFW Data in the CAA .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . 97 Y. Khotyaintsev, P.-A. Lindqvist, A. Eriksson, and M. André

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FGM Data Products in the CAA .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .109 J.M. Gloag, E.A. Lucek, L.-N. Alconcel, A. Balogh, P. Brown, C.M. Carr, C.N. Dunford, T. Oddy, and J. Soucek

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Contents

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PEACE Data in the Cluster Active Archive . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .129 A.N. Fazakerley, A.D. Lahiff, R.J. Wilson, I. Rozum, C. Anekallu, M. West, and H. Bacai

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RAPID Products at the Cluster Active Archive .. . . . . . . . . . . . . . .. . . . . . . . . . .145 Patrick W. Daly and Elena A. Kronberg

10 STAFF Instrument Products Distributed Through the Cluster Active Archive .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .159 N. Cornilleau-Wehrlin, L. Mirioni, P. Robert, V. Bouzid, M. Maksimovic, Y. de Conchy, C.C. Harvey, and O. Santol´ık 11 Cluster Wideband Data Products in the Cluster Active Archive .. . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .169 J.S. Pickett, J.M. Seeberger, I.W. Christopher, O. Santol´ık, and K.M. Sigsbee 12 The WHISPER Relaxation Sounder and the CLUSTER Active Archive. . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .185 J.G. Trotignon, P.M.E. Décréau, J.L. Rauch, X. Vallières, A. Rochel, S. Kougblénou, G. Lointier, G. Facskó, P. Canu, F. Darrouzet, and A. Masson 13 ESOC Data Products in the CAA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .209 J. Volpp and D. Sieg Part II Tools for the CAA Data Analysis 14 QSAS, QM Science Analysis Software . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .225 A.J. Allen 15 Flexible Tools for Accessing the Cluster Archives . . . . . . . . . . . . .. . . . . . . . . . .233 E. Gamby, J. De Keyser, and M. Roth 16 AMDA, Automated Multi-Dataset Analysis: A Web-Based Service Provided by the CDPP .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .239 C. Jacquey, V. Génot, E. Budnik, R. Hitier, M. Bouchemit, M. Gangloff, A. Fedorov, B. Cecconi, N. André, B. Lavraud, C. Harvey, F. Dériot, D. Heulet, E. Pallier, E. Penou, and J.L. Pinçon 17 Cluster CAA Module for PaPCo .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .249 ˚ J. Faden, A. Asnes, R. Friedel, M. Taylor, S. McCaffrey, C. Perry, and M.L. Goldstein

Contents

Part III

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Measurement Techniques and Calibration Routines

18 Electron Density Estimation in the Magnetotail: a Multi-Instrument Approach.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .261 A. Masson, O. Santol´ık, M.G.G.T. Taylor, C.P. Escoubet, ˚ A.N. Fazakerley, J. Pickett, A. Asnes, X. Vallières, H. Laakso, and J.-G. Trotignon 19 Cluster-PEACE In-flight Calibration Status . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .281 A.N. Fazakerley, A.D. Lahiff, I. Rozum, D. Kataria, H. Bacai, ˚ C. Anekallu, M. West, and A. Asnes 20 Generation and Validation of Ion Energy Spectra Based on Cluster RAPID and CIS Measurements . . . . . . . . . . . . .. . . . . . . . . . .301 Elena A. Kronberg, Patrick W. Daly, Iannis Dandouras, Stein Haaland, and Edita Georgescu Part IV

Magnetospheric Missions

21 The Cluster Mission: Space Plasma in Three Dimensions . . . .. . . . . . . . . . .309 M.G.G.T. Taylor, C.P. Escoubet, H. Laakso, A. Masson, and M.L. Goldstein 22 Double Star: Mission, Instruments and Joint Observations ... . . . . . . . . . .331 M.W. Dunlop, C.P. Escoubet, Z.-X. Liu, C. Shen, H. Laakso, M.G.G.T. Taylor, A.N. Fazakerley, and the Double star PIs Part V

Observations of Solar Wind and Magnetosheath

23 Effect of Shock Normal Orientation Fluctuations on Field-Aligned Beam Distributions. . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .349 K. Meziane, A.M. Hamza, M. Wilber, M.A. Lee, C. Mazelle, E.A. Lucek, T. Hada, and A. Markowitch 24 Wave Number Spectra in the Solar Wind, the Foreshock, and the Magnetosheath . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .363 Y. Narita, K.-H. Glassmeier, S.P. Gary, M.L. Goldstein, and R.A. Treumann 25 Cluster Hot Flow Anomaly Observations During Solar Cycle Minimum . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .369 G. Facskó, M. Tátrallyay, G. Erd˝os, and I. Dandouras

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Contents

26 On the Growth of Mirror Mode Waves in the Magnetosheath Based on Cluster Observations . . . . . . . .. . . . . . . . . . .377 M. Tátrallyay, G. Erd˝os, I. Dandouras, and E. Georgescu Part VI Observations of Magnetopause and Cusp 27 Mixed Azimuthal Scales of Flux Transfer Events . . . . . . . . . . . . . .. . . . . . . . . . .389 R.C. Fear, S.E. Milan, E.A. Lucek, S.W.H. Cowley, and A.N. Fazakerley 28 Perspectives Gained from a Combination of Polar, Cluster and ISEE Energetic Particle Measurements in the Dayside Cusp . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .399 T.A. Fritz 29 Energetic Particles in the Cusp: A Cluster/RAPID View . . . . .. . . . . . . . . . .415 T. Asikainen Part VII Observations of Magnetospheric Tail 30 Plasma Flow Reversals in the Magnetotail and Their Implications on Substorm Models. . . . . . . . . . . . . . . . . . .. . . . . . . . . . .429 A.T.Y. Lui 31 Spatial and Temporal Structures in the Vicinity of the Earth’s Tail Magnetic Separatrix Cluster Observations .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .435 E.E. Grigorenko, L.M. Zelenyi, M.S. Dolgonosov, and J.-A. Sauvaud 32 Cluster Observations of Energy Conversion Regions in the Plasma Sheet .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .453 O. Marghitu, M. Hamrin, B. Klecker, K. Rönnmark, S. Buchert, L.M. Kistler, M. André, and H. Rème 33 Acceleration of > 40 keV Electrons in Near-Earth Magnetotail Reconnection Events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .461 ˚ A. Asnes, M.G.G.T. Taylor, and A.L. Borg 34 Evolution and Energization of Energetic Electrons in the Inner Magnetosphere . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .467 J.F. Fennell and J.L. Roeder

Contributors

L.-N. Alconcel Space and Atmospheric Physics, The Blackett Laboratory, Imperial College, London, SW7 2BW, UK A.J. Allen Blacket Laboratory, Imperial College, London, SW7 2AZ, UK, [email protected] H.St.C. Alleyne Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK, [email protected] M. André Swedish Institute of Space Physics, Uppsala, Sweden N. André CDPP/CESR, CNRS/Université Paul Sabatier, 9, avenue du colonel Roche, 31028 Toulouse, France C. Anekallu Mullard Space Science Laboratory, University College London, UK T. Asikainen Department of Physics Centre of Excellence in Research, P.O. Box 3000, FIN-90014, University of Oulu, Finland, [email protected] ˚ A. Asnes ESA/ESTEC, Noordwijk, The Netherlands, [email protected] H. Bacai Mullard Space Science Laboratory, University College London, UK A. Balogh Space and Atmospheric Physics, The Blackett Laboratory, Imperial College, London, SW7 2BW, UK and International Space Science Institute (ISSI), Hallerstrasse 6, 3012 Bern, Switzerland A. Barthe Université de Toulouse, Centre d’Etude Spatiale des Rayonnements, B.P. 44346, 31028 Toulouse, France and AKKA Technologies, 6 Rue R. Camboulives, 31036 Toulouse, France, [email protected] I. Bates Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK

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Contributors

M.B. Bavassano-Cattaneo Istituto di Fisica dello Spazio Interplanetario, INAF, Via del Fosso del Cavaliere 100, 00133 Roma, Italy, [email protected] A. Blagau Institute of Space Sciences, P.O. Box MG-23, RO 77125 BucharestMagurele, Romania, [email protected] A.L. Borg Norwegian Defense Research Institute, Kjeller, Norway M. Bouchemit CDPP/CESR, CNRS/Université Paul Sabatier, 9, avenue du colonel Roche, 31028 Toulouse, France V. Bouzid Laboratoire de Physique des Plasmas, Ecole Polytechnique, UPMC, CNRS, route de Saclay, 91128 Palaiseau, France P. Brown Space and Atmospheric Physics, The Blackett Laboratory, Imperial College, London, SW7 2BW, UK S. Brunato Université de Toulouse, Centre d’Etude Spatiale des Rayonnements, B.P. 44346, 31028 Toulouse, France and Noveltis, 2 Avenue de l’Europe, 31520 Ramonville-Saint-Agne, France, [email protected] S. Buchert Swedish Institute of Space Physics, Uppsala, Sweden A. Buckley Space Science Group, University of Sussex, Falmer, Brighton, BN1 9QH, UK, [email protected] E. Budnik Noveltis, 2, Avenue Europe, 31520 Ramonville Saint Agne, France P. Canu Laboratoire de Physique des Plasmas, Vélizy, France, [email protected] T.D. Carozzi Space Science Group, University of Sussex, Falmer, Brighton, BN1 9QH, UK, [email protected] C.M. Carr Space and Atmospheric Physics, The Blackett Laboratory, Imperial College, London, SW7 2BW, UK B. Cecconi LESIA, Observatoire de Paris-Meudon, 5, place Janssen, 92195 Meudon I.W. Christopher Department of Physics and Astronomy, The University of Iowa, Iowa City, 52240, USA M. Chutter University of New Hampshire, Durham, USA, [email protected] N. Cornilleau-Wehrlin Laboratoire de Physique des Plasmas, Ecole Polytechnique, UPMC, CNRS, route de Saclay, 91128 Palaiseau, France and Station de Radioastronomie de Nançay, 18330 Nancay, France, [email protected]

Contributors

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S.W.H. Cowley University of Leicester, UK I. Dandouras Université de Toulouse, Centre d’Etude Spatiale des Rayonnements, B.P. 44346, 31028 Toulouse, France, [email protected] F. Darrouzet Institut d’Aéronomie Spatiale de Belgique, Bruxelles, Belgique, [email protected] J. De Keyser Belgian Institute for Space Aeronomy, Brussels, Belgium P.M.E. Décréau Laboratoire de Physique et Chimie de l’Environnement et de l’Espace, Université d’Orléans, Orléans, France, [email protected] F. Dériot CNES, Centre spatial de Toulouse, 18 avenue E. Belin, 31401 Toulouse, France M.S. Dolgonosov Space Research Institute of RAS, Moscow, Profsoyuznaya str, 84/32, Russia C.N. Dunford Space and Atmospheric Physics, The Blackett Laboratory, Imperial College, London, SW7 2BW, UK M.W. Dunlop SSTD, Rutherford Appleton Laboratory, Chilton, Didcot, Oxfordshire, OX11 0QX, UK, [email protected] G. Erd˝os KFKI Research Institute for Particle and Nuclear Physics, H-1525 Budapest, P.O. Box 49, Hungary A. Eriksson Swedish Institute of Space Physics, Uppsala, Sweden C.P. Escoubet European Space Agency, ESTEC, D-SRE, Keplerlaan 1, 2200 AG Noordwijk, The Netherlands G. Facskó Laboratoire de Physique et Chimie de l’Environnement et de l’Espace, Université d’Orléans, Orléans, France and KFKI Research Institute for Particle and Nuclear Physics, H-1525 Budapest, P.O. Box 49, Hungary, [email protected] J. Faden Cottage Systems, Iowa City, IA, USA, [email protected] A.N. Fazakerley Mullard Space Science Laboratory, University College London, Dorking, Surrey, RH5 6NT, UK, [email protected] R.C. Fear University of Leicester, UK, [email protected] A. Fedorov CDPP/CESR, CNRS/Université Paul Sabatier, 9, avenue du colonel Roche, 31028 Toulouse, France J.F. Fennell The Aerospace Corporation, P.O. Box 92957, Los Angeles, CA 90009, USA, [email protected] R. Friedel Los Alamos National Labs, Los Alamos, NM, USA T.A. Fritz Center for Space Physics, Boston University, Boston, MA 02215 USA, [email protected]

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Contributors

E. Gamby Belgian Institute for Space Aeronomy, Brussels, Belgium, [email protected] M. Gangloff CDPP/CESR, CNRS/Université Paul Sabatier, 9, avenue du colonel Roche, 31028 Toulouse, France V. Génot CDPP/CESR, CNRS/Université Paul Sabatier, 9, avenue du colonel Roche, 31028 Toulouse, France E. Georgescu Max-Planck-Institute for Solar Research, Katlenburg-Lindau, Germany, [email protected] J.M. Gloag Space and Atmospheric Physics, The Blackett Laboratory, Imperial College, London, SW7 2BW, UK M.L. Goldstein Geospace Physics Laboratory, NASA Goddard Space Flight Center, Code 673, Greenbelt, MD 20771, USA M.P. Gough Space Science Group, University of Sussex, Falmer, Brighton, BN1 9QH, UK, [email protected] E.E. Grigorenko Space Research Institute of RAS, Moscow, Profsoyuznaya str, 84/32, Russia, [email protected] C. Gruenberger European Space Agency, ESTEC, Noordwijk, The Netherlands T. Hada ESST, Kyushu University, Fukuora, Japan M. Hamrin Department of Physics, Ume˚a University, Ume˚a, Sweden and Swedish Institute of Space Physics, Ume˚a, Sweden A.M. Hamza Physics Department, University of New Brunswick, Canada C.C. Harvey Centre de Données de Physique des Plasmas, CNRS, Toulouse, France D. Herment European Space Agency, ESTEC, Noordwijk, The Netherlands D. Heulet CNES, Centre spatial de Toulouse, 18 avenue E. Belin, 31401 Toulouse, France R. Hitier Co-Libri, Cremefer 11290 Montréal, France C. Jacquey CDPP/CESR, CNRS/Université Paul Sabatier, 9, avenue du colonel Roche, 31028 Toulouse, France, [email protected] H. Jeszenszky Space Research Institute, Austrian Academy of Sciences, Schmiedlstrasse 6, 8042 Graz, Austria D. Kataria Mullard Space Science Laboratory, University College London, UK Y. Khotyaintsev Swedish Institute of Space Physics, Uppsala, Sweden, [email protected] L.M. Kistler Space Science Center, University of New Hampshire, Durham, NH 03824, USA, [email protected]

Contributors

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B. Klecker Max-Planck-Institut für extraterrestrische Physik, Garching, Germany S. Kougblénou Laboratoire de Physique et Chimie de l’Environnement et de l’Espace, Université d’Orléans, Orléans, France, [email protected] H. Laakso European Space Agency, ESTEC, D-SRE, Keplerlaan 1, 2200 AG Noordwijk, The Netherlands, [email protected] A.D. Lahiff Mullard Space Science Laboratory, University College London, UK B. Lavraud CDPP/CESR, CNRS/Université Paul Sabatier, 9, avenue du colonel Roche, 31028 Toulouse, France M.A. Lee Space Science Center, University of New Hampshire, Durham, USA P.-A. Lindqvist Royal Institute of Technology, Stockholm, Sweden Z.-X. Liu Centre for Space Science and Applied Research, Chinese Academy of Sciences, Beijing 100080, China G. Lointier Laboratoire de Physique et Chimie de l’Environnement et de l’Espace, Université d’Orléans, Orléans, France, [email protected] E.A. Lucek Space and Atmospheric Physics, The Blackett Laboratory, Imperial College, London, SW7 2BW, UK, [email protected] A.T.Y. Lui The Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20723, USA, [email protected] M. Maksimovic LESIA, Observatoire de Paris-Meudon, 5 place Jules Jansen, 92195 Meudon Cedex, France O. Marghitu Institute for Space Sciences, Bucharest, Romania and Max-Planck-Institut für extraterrestrische Physik, Garching, Germany, [email protected] A. Markowitch Laboratoire de Physique et Astroparticules, Université de Montpellier, France A. Masson RSSD, ESA, Noordwijk, The Netherlands and ESA/ESTEC, D-SRE, Keplerlaan 1, 2200 AG Noordwijk, The Netherlands, [email protected] C. Mazelle Centre d’Etudes Spatiales des Rayonnements, Toulouse, France S. McCaffrey European Space Agency, ESTEC, Noordwijk, The Netherlands K. Meziane Physics Department, University of New Brunswick, Canada, [email protected] L. Mirioni Laboratoire de Physique des Plasmas, Ecole Polytechnique, UPMC, CNRS, route de Saclay, 91128 Palaiseau, France

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Contributors

T. Oddy Space and Atmospheric Physics, The Blackett Laboratory, Imperial College, London, SW7 2BW, UK E. Pallier CDPP/CESR, CNRS/Université Paul Sabatier, 9, avenue du colonel Roche, 31028 Toulouse, France G. Paschmann Max-Planck-Institute for Extraterrestrial Physics, Garching, Germany, [email protected] E. Penou Université de Toulouse, Centre d’Etude Spatiale des Rayonnements, B.P. 44346, 31028 Toulouse, France and CDPP/CESR, CNRS/Université Paul Sabatier, 9, avenue du colonel Roche, 31028 Toulouse, France, [email protected] C. Perry Rutherford Appleton Laboratory, Chilton, Didcot, Oxon, UK J.S. Pickett Department of Physics and Astronomy, The University of Iowa, Iowa City, 52240, USA, [email protected] J.L. Pinçon LPCE, Laboratoire de Physique et Chimie de l’Environnement, 45071 Orléans, France P. Puhl-Quinn University of New Hampshire, Durham, USA, [email protected] J. Quinn Boston University, Boston, MA, USA, [email protected] J.L. Rauch Laboratoire de Physique et Chimie de l’Environnement et de l’Espace, Université d’Orléans, Orléans, France, [email protected] P. Robert Laboratoire de Physique des Plasmas, Ecole Polytechnique, UPMC, CNRS, route de Saclay, 91128 Palaiseau, France A. Rochel Laboratoire de Physique et Chimie de l’Environnement et de l’Espace, Université d’Orléans, Orléans, France, [email protected] J.L. Roeder The Aerospace Corporation, P.O. Box 92957, Los Angeles, CA 90009, USA K. Rönnmark Department of Physics, Ume˚a University, Ume˚a, Sweden M. Roth Belgian Institute for Space Aeronomy, Brussels, Belgium H. Rème Université de Toulouse, Centre d’Etude Spatiale des Rayonnements, B.P. 44346, 31028 Toulouse, France and CNRS, UMR 5187, B.P. 44346, 31028 Toulouse, France, [email protected] I. Rozum Mullard Space Science Laboratory, University College London, UK

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O. Santol´ık Department of Physics and Astronomy, The University of Iowa, Iowa City, Iowa, 52240, USA and Institute of Atmospheric Physics, ASCR, Bocni II/1401, CZ-14131 PRAHA 4, Czech Republic and Institute of Atmospheric Physics and Charles University, Faculty of Mathematics and Physics, Prague, 18000, Czech Republic J.-A. Sauvaud Centre d’Etudie Spatial des Rayonnements, Toulouse cedex4, France J.M. Seeberger Department of Physics and Astronomy, The University of Iowa, Iowa City, 52240, USA C. Shen Centre for Space Science and Applied Research, Chinese Academy of Sciences, Beijing 100080, China D. Sieg Hewlett-Packard GmbH at European Space Operations Centre, [email protected] K.M. Sigsbee Department of Physics and Astronomy, The University of Iowa, Iowa City, 52240, USA J. Soucek Department of Space Physics, Institute of Atmospheric Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic M. Tátrallyay KFKI Research Institute for Particle and Nuclear Physics, H-1525 Budapest, P.O. Box 49, Hungary, [email protected] M.G.G.T. Taylor European Space Agency, ESTEC, Noordwijk, The Netherlands, [email protected] R. Turner European Space Agency, ESTEC, Noordwijk, The Netherlands R. Torbert University of New Hampshire, Durham, USA, [email protected] K. Torkar Space Research Institute, Austrian Academy of Sciences, Schmiedlstrasse 6, 8042 Graz, Austria, [email protected] J.G. Trotignon Laboratoire de Physique et Chimie de l’Environnement et de l’Espace, Université d’Orléans, Orléans, France, [email protected] H. Vaith University of New Hampshire, Durham, USA, [email protected] X. Vallières Laboratoire de Physique et Chimie de l’Environnement et de l’Espace, Université d’Orléans, Orléans, France, [email protected] J. Volpp European Space Operations Centre, Robert-Bosch-Strasse 5, D-64625 Darmstadt, Germany, [email protected]

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S.N. Walker Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK, [email protected] M. West Mullard Space Science Laboratory, University College London, UK and Royal Observatory, Belgium M. Wilber Space Sciences Laboratory, University of California, Berkeley, USA R.J. Wilson Mullard Space Science Laboratory, University College London, UK and Los Alamos National Laboratory, Los Alamos, USA K.H. Yearby Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK, [email protected] L.M. Zelenyi Space Research Institute of RAS, Moscow, Profsoyuznaya str, 84/32, Russia

Part I

Products and Services of the Cluster Active Archive

Chapter 1

Cluster Active Archive: Overview H. Laakso, C. Perry, S. McCaffrey, D. Herment, A.J. Allen, C.C. Harvey, C.P. Escoubet, C. Gruenberger, M.G.G.T. Taylor, and R. Turner

Abstract The four-satellite Cluster mission investigates the small-scale structures and physical processes related to interaction between the solar wind and the magnetospheric plasma. The Cluster Active Archive (CAA) (URL: http://caa.estec.esa.int) will contain the entire set of Cluster high-resolution data and other allied products in a standard format and with a complete set of metadata in machine readable format. The total amount of the data files in compressed format is expected to exceed 50 TB. The data archive is publicly accessible and suitable for science use and publication by the world-wide scientific community. The CAA aims to provide user-friendly services for searching and accessing these data and ancillary products. The CAA became operational in February 2006 and as of Summer 2008 has data from most of the Cluster instruments for at least the first 5 years of operations (2001–2005). The coverage and range of products are being continually improved with more than 200 datasets available from each spacecraft, including high-resolution magnetic and electric DC fields and wave spectra; full three-dimensional electron and ion distribution functions from a few eV to hundreds of keV; and various ancillary and browse products to help with spacecraft and event location. The CAA is continuing to extend and improve the online capabilities of the system and the quality of the existing data. It will add new data files for years 2006–2009 and is preparing for the long-term archive with complete coverage after the completion of the Cluster mission.

H. Laakso (), S. McCaffrey, D. Herment, C.P. Escoubet, C. Gruenberger, M.G.G.T. Taylor, and R. Turner European Space Agency, ESTEC, Noordwijk, The Netherlands e-mail: [email protected] C. Perry Rutherford Appleton Laboratory, Chilton, Didcot, Oxon, UK A.J. Allen Imperial College, London, UK C.C. Harvey Centre de Données de Physique des Plasmas, CNRS, Toulouse, France

H. Laakso et al. (eds.), The Cluster Active Archive, Astrophysics and Space Science Proceedings, DOI 10.1007/978-90-481-3499-1 1, c Springer Science+Business Media B.V. 2010

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1.1 Introduction The Cluster mission consists of four identical spacecraft, each carrying 11 instruments [2]. The satellites were launched in two pairs in July/August 2000, and after a 6-months commissioning phase, the mission moved into an operational phase in February 2001. The mission has been approved to operate until summer 2009, and a new extension proposal is in preparation to request further operations beyond 2009.

1.1.1 Cluster Mission A key aspect of the Cluster mission is the controllable flight formation. At two locations along the satellite trajectories, the four spacecraft are aligned at the tips of a regular tetrahedron that is the optimal configuration for the measurements of spatial gradients. In other positions the tetrahedron is less regular and near the perigee the satellites fly in a string-of-pearls formation, and there are two positions on each orbit where the four satellites are coplanar. The size of the tetrahedron formation was changed systematically, covering various distances between 100 and 10,000 km during the years 2001–2005. This strategy was necessary to cover the different characteristic spatial and temporal scales of the fundamental plasma physics processes in the different regions of the dynamic magnetosphere. During the mission extension, which started in January 2006, Cluster has been in a multi-scale phase where three satellites fly in a 10,000 km triangular formation and the fourth satellite (Cluster 4) is perpendicular to the plane and is separated from Cluster 3 by a distance varying between 40 km and a few 1,000 km.

1.1.2 CAA Concept The key scientific rationales for the Cluster Active Archive are (1) to maximize the scientific return from the Cluster mission by making all high-resolution Cluster data available to the world-wide scientific community, (2) to ensure that the unique Cluster observations are preserved in a stable, long-term archive for scientific analysis beyond the end of the mission, and (3) to provide this archive as a major contribution by ESA and the Cluster science community to the International Living With a Star programme. The CAA database and services are established and maintained by the European Space Agency (ESA) at ESTEC. The aims of the CAA are to ensure that the CAA contains all of the Cluster high resolution data; the data archived should be of the best quality achievable within the limited resources available; the data should be suitable for science use and publication by the world-wide scientific community;

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and the CAA will provide user friendly services for searching and accessing these data and ancillary products such as orbit information. The implementation of the CAA has two important aspects: (1) In view of the shortage of manpower in most institutes processing Cluster data, ESA-supported manpower has been deployed in institutes where the relevant expertise exists, to assist in the preparation, validation, and documentation of the high-resolution data to be deposited in the archive, and (2) each PI team matches the level of ESA supported manpower with an equal level of effort from their own National Funding Agency.

1.1.3 CAA Standards The CAA standards form the basis of a consistent approach to the formatting and description of the digital data products being handled by the CAA. This is vital for the development of standard data handling tools and to maximize the ease of use of numerous products that are provided by many different groups. The lack of standardization in the past has proved a major impediment to the full exploitation of data, and every effort is being made to avoid this in the case of the CAA. In the early phase of the CAA two important working groups were established for standardization: one for the definition of the data format [1], and the other for the creation of a metadata model and dictionary [3].

1.2 Infrastructure The CAA project, managed by ESA, draws upon expertise from within ESA, the Cluster instrument teams and other groups. This combination encompasses the full range of skills and experience in handling the diverse and complex Cluster products that is required to achieve the CAA goals.

1.2.1 Organization The structure of the project team in summer 2008 is presented in Fig. 1.1. The core team consists of a project manager, technical manager, system engineer, and two system/software developers. The project has received support from the agency in the form of a Young Graduate Trainee (YGT) for 2 years. The Cluster project scientist and his deputy provide additional scientific support. The remaining CAA resources are deployed within the instrument teams. This is a key aspect of the CAA approach and is intended to ensure timely delivery of the best quality data from all the Cluster instruments. Some important supporting data are received from

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Fig. 1.1 CAA management structure

the Cluster Joint Science Operations Centre (JSOC) that provides the CAA with data catalogues of orbital parameters of the predicted scientific events. The European Space Operations Centre (ESOC) provides the CAA with a wide range of spacecraft operations related information, which could be helpful as background information for science data processing; for further information, see Volpp and Sieg [Chapter 13].

1.2.2 System Architecture A key requirement of the CAA system architecture is that the system be scalable as the amount of data increases over time, affecting all hardware components, including servers, storage, backup system, and network. The current hardware components are sketched in Fig. 1.2. The total volume of compressed data products to be handled by the CAA is expected to exceed 50 TB, built up over the course of the mission. The CAA will keep all data available online to ensure the users have rapid access to the data they request. To provide the necessary flexibility and performance, the data storage is implemented via a storage area network (SAN). The SAN uses Fibre Channel network technology, which is well suited to the small, closed environment of the CAA system. This SAN is local to the CAA system, and is not part of a wider departmental SAN infrastructure. Storage is implemented on 7 RAID (Redundant Array of Independent Disks) arrays, each connected to the CAA servers via a dedicated fibre-channel infrastructure that includes fibre-channel “fabric” switches. These RAID arrays use highly cost-effective SATA (Serial Advanced Technology Attachment) disks, up to 250 GB each, but logical volumes are created by a hardware controller on each device, to create much larger volumes. The volumes are generally built as RAID 5, the most recent as RAID 6, in most cases with a hot spare. Each RAID array is divided


Fig. 1.2 Sketch of the CAA system in autumn 2008. The system has seven servers and most disks are directly mounted to the main data processing server (CAA-2), and the data catalogue disks are NFS mounted to other servers. CAA-5 is the access point to the users and data providers

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into volumes of approximately 2 TB, in order to be manageable for backups. There are currently 21 volumes in use, giving approximately 42 TB of data connected to the server. In addition, several servers have significant internal storage, bringing the total data storage to approximately 45TB. The main data processing and database handling operations are undertaken by two (Ubuntu) Linux servers (caa-2 and caa-3 in Fig. 1.2), both having two Quadcore Intel Xeon 2.33 GHz processors. The systems share data using NFS (Network File System) and access rights using NIS (Network Information Service). Additional servers (containing 8 Intel Xeon processors and 4 Pentium processors) host the main web interface and development activities, and data backup services. The recent addition of a dedicated web development server allows development in parallel to operational systems. The CAA backup solution is based on an Overland Neo 4100 system with 2 internal drives and 24 TB tape capacity (58 tapes online from a pool over several hundred, each tape holding between 200 and 400-GB) based on LTO3 (Linear Tape Open) technology. The library is connected via fast SCSI to an Intel based Linux server, running the commercially licenced BakBone Netvault software. This system handles incremental backups, full backups, and periodic data archiving requirements. A number of network issues had to be taken into account in implementing the CAA at ESA. The CAA machines are inside a firewall protected part of ESA grid that provides high speed access to the international academic networks. Significant volumes of data are transferred from the instrument teams and ESOC to the CAA, and later the users request these data, all of which require good network connectivity between the CAA and the public internet. For this network, a dedicated inter-connect between systems has been implemented, before that is connected to the world. Interconnectivity of the servers is essential as the tasks are distributed to various servers. For this purpose, a dedicated local network was implemented in order to allow secure local communications between systems, without loading the DMZ (demilitarized zone) or exposing internal data such as backups, potentially to the world. The application software at the CAA has been partially developed by the CAA core team and partially in the PI institutes or other involved institutes, all of which needs to be supported by the CAA system. For this reason Linux was selected as the CAA operating system, as many instrument teams use Linux in one form or another. The services and data sets available from the CAA have grown and as a consequence have increased the requirements on the system performance. The CAA processing system handles various tasks, such as data management; data delivery; data processing for those instruments that provide software rather than pre-processed products; data ingestion into the CAA database; and data manipulation and visualization.

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1.2.3 System Reviews Formal project reviews are held annually to verify that the key milestones have been met, that the technical aspects of the project are sound, and that the activities are progressing on schedule and within budget. The following project reviews have been held: System Specification Review in November 2003, to approve the user require-

ments, to review conceptual design, to review proposed PI inputs, to agree the archive implementation plan, and to release instrument team contracts Implementation Review in May 2005, to approve the archiving plans of the experiments and the technical implementation of the overall system First to second Operations Review in May 2006 and 2007 to review the status of data delivery and CAA services for years 2001–2002 and 2003–2004, respectively Third Operations Review in May 2008, to review the first part of the CAA activity (data availability from years 2001–2005) Fourth Operations Review in May 2009, to review the CAA activity for the first part of the second mission extension (data availability from years 2006–2007)

In future the operations reviews will be held annually as before. In addition in February-March 2009 an extensive peer review process was carried out to evaluate the usability and quality of the CAA database and its services to the users. More than 200 recommendations were obtained that are now under implementation.

1.2.4 User Access Statistics The CAA opened its services to the science community in February 2006. The evolution of the number of registered users and their use of CAA is shown in Fig. 1.3. At the time of opening, nearly 100 people had registered to support beta testing of the system. The top panel of the figure shows there has been a consistent rise in the number of registered users, approximately 20–30 new users per month, as shown in the middle panel, until there are currently about 800 registered users. The monthly number of user logins to the CAA website is shown in the second panel from bottom. The current average rate is around 450–500 logins per month. There is a clear increase by approximately 50% over the last year, which is in line with the increasing number of active users shown in the second panel from top that shows the number of those users who have logged in the CAA, either via web or command line interface. The bottom panel in Fig. 1.3 shows the monthly download volume. This is not expected to increase drastically because many institutes have implemented centralized data servers for the CAA data so that files are downloaded only once unless a new version of data file is ingested into the CAA (which can be automatically

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Fig. 1.3 User statistics of the CAA. The panels from top to bottom are: the total number of registered users, the number of active users per month (i.e. users who have logged in the system), the number of new registered users per month, the total number of logins per month through the web-site, and the total monthly download rate in GigaBytes

checked via a command-line request). The download minimum in December 2007 was caused by a system failure whose consequences required several weeks for recovery and the statistics of download volume was lost. Within spring and summer 2008 the CAA will received plenty of new data as well as many of the old datasets have been recalibrated and will be ingested into the system which will likely raise the downloading rate.

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1.2.5 User Feedback The CAA is a new type of data archiving activity for the Sun–Earth science community which, for the first time, provides this community with access to all calibrated full resolution data from a space mission. Therefore it is planned that both the data and the services of the CAA will significantly improve over time. Here the scientific community can make important contributions by using the data and the system and providing feedback to the CAA suggesting where the improvements, changes and additional features are desirable. To facilitate this feedback, the CAA has opened a user feedback area at http://caa.estec.esa.int/caa/feedback intro.xml where users can find two kinds of forms for reporting problems or sending suggestions. The first form is technical where users can report on missing data, speed of the system, and so on. The second form is for scientific issues where users can tell the CAA team what they want from the CAA system.

1.3 Standards The Cluster Exchange Format (CEF) is a self-describing ASCII format consisting of a metadata header followed by data represented as a comma-separated list of values. This was recommended by the Cluster Science Data System (CSDS) Archive Task Group for the exchange of science data between instrument teams of the Cluster mission. Adoption of a single common format allows the delivery of data products to users throughout the whole science community, including future scientists without the need for specific access software. The CEF format provides storage of science products in a robust and easily accessible form. The complexity of some high-resolution data products led the CAA design team to produce an extended version 2 of the CEF as the format to be used in the CAA [1]. Earlier versions of this syntax are referred to as CEF 1, and the syntax specified for the CAA is designated CEF 2. The data description or metadata consists of (1) a data model that is a logical framework into which the metadata information is placed, and (2) a data dictionary that is an ensemble of words used to populate the data model. The data model and data dictionary define the semantics used to describe the data. The development of the standard CAA data dictionary [3] was a major activity during implementation phase since it is a vital input to the development of the instrument team products. However, the dictionary has been updated several times during the operations phase.

1.3.1 CEF Data Format Files in the CEF syntax must have names with the extension .cef to assist identification. An exclamation mark is used as a comment marker, and all input to the right

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of this marker up to the new line character is ignored on input. A header must be included, preceding the data records, and provide sufficient metadata to fully describe the data and their formatting. Use of detached headers is supported to minimize duplication. The file syntax and header content of a CEF file is specified in Allen et al. [1]. Entries in a record are comma separated and white space surrounding delimiters is ignored. Missing parameter values must be padded by a fill value that must be specified in the metadata. All data files are tabular and homogeneous – they have a sequence of records each with the same variables in the same order. Each record is ended by END OF RECORD MARKER, which by default is a new line character (nn) but can be set to another character in order to allow multiline records. The END OF RECORD MARKER, tab characters, carriage return (nr), new line and white space characters at the start and end of records and surrounding delimiters should be ignored when read. Thus, data may safely be formatted with white space and end of line markers for human (text editor) readability, allowing for easier exchange between platforms where the end of line marker is variously nrnn under DOS, nn under Unix and nr under Mac OS. For time series the records are ordered on the monotonic increasing time variable, and the time tag must be the first entry in a record. The other entries in the record are associated with that time via the metadata. Time tags are usually centered within the sampling interval, and the spacing between time tags is often the same as that sampling interval. Otherwise, Delta PLUS and Delta MINUS metadata describe the sampling or integration interval corresponding to the data and the location of the time tag within that interval. Time is represented as a text string in the strict ISO 8601 ASCII calendar date time format: yyyy-mm-ddTHH:MM:ss.wwwZ where the trailing ‘Z’ is UTC designator. For example, 2001-02-01T01:23:00.000Z corresponds to 01 February 2001 at 01:23:00 UT. This format permits any number of digits after the decimal point in the seconds field, e.g., the example above is a valid time string to millisecond accuracy. This format is robust for arbitrary timing accuracy, but software developers must take care to ensure that their software retains the accuracy. Multi-dimensional variables follow the natural ordering of the C Programming Language (i.e., the last index varies the fastest), and one entry is required for each element. For a velocity vector one has three entries and for a 2 by 2 array four entries, while a 16 by 8 by 24 array (e.g. for a distribution function) has 3,072 entries. It must be recognized that some data products may result in extremely long record lines. The rigid record structure to the data is intended to allow simple generic software to handle all instrument files.

1.3.2 CEF Metadata Metadata must contain all the information required to read and interpret the data (syntactic description), and to understand what the resulting numerical values

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Table 1.1 Hierarchical levels for metadata Level Description Mission Information relevant to the whole mission Observatory One of four spacecraft (Cluster-1, Cluster-2, Cluster-3, and Cluster-4) or Cluster-Multi that contains datasets that contain data from more than one observatory Experiment Each spacecraft has 11 experiments, each identified by its Principal Investigator, plus the auxiliary data Instrument Some experiments consists of more than one physical instrument, each of which produces its own datasets; for two of these, CIS and STAFF, for the purpose of archiving it has been found convenient to identify two instruments. Thus CAA contains datasets from 4(11 C 2) D 52 instruments Dataset Each instrument produces one or more datasets; this level of metadata is common to the whole of each dataset Parameter A dataset contains one or more parameters, each of which has its own metadata and is also common to the entire dataset File Each dataset is composed of files, the number of which will grow with time during the lifetime of the CAA

represent (semantic description), including how the data were obtained. The purpose of the CAA Metadata Dictionary [3] is to describe fully the required CAA metadata information and to explain how that information must be formatted so as to be exploitable by the generic CAA software. Table 1.1 shows different concepts in the CAA that are hierarchically organized. An example of CEF metadata is given in Appendix. Three forms of metadata are recognized: File metadata are used to provide information unique to the file such as filename,

time coverage and provenance. Global metadata is applicable to the entire contents of a dataset, and fulfils the

same purpose as the global attributes in a CDF file. Support metadata (called variable metadata in the CEF) describes an individual

parameter in a dataset, and is equivalent to the CDF variable attributes. Support metadata blocks must appear in the CEF header in the same order as the corresponding parameters appear in the data records. Apart from this, there is no required order for the global metadata or parameters blocks within any metadata block although usually the global metadata are followed by the parameter definitions. Apart from quoted text data and variable names, metadata information is case insensitive. The open format also allows for the inclusion of any extra metadata deemed desirable by the generating team. Lines of metadata may be continued using ‘n’ as a continuation marker, following one of the commas separating a list of values. A metadatum consists of a text string of the form “KEYWORD D value”. The keyword values can be of three types: (1) a single data value (which may be numerical, logical, enumerated text string, formatted text string, free text string, ISO time code), (2) a comma delimited sequence of data values or (3) the name of a data variable in the same file carrying the requisite information.

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1.4 Software System The CAA is built around a MySQL database and XML-based data management system, which provides a robust and extensible framework for handling the data products delivered to the CAA. There are two routes of accessing the data products: web GUI and command-line interfaces that are described in the following section.

1.4.1 User Interface The access point to the CAA database and services is the website at http://caa.estec. esa.int/ (Fig. 1.4). Part of the information on the website is available to all visitors, but the access to the main data and graphical products requires a login into the system. Therefore users must first register to the system. The registration procedure is fully automatic so that the user defines the password (which can be changed later if wished) but the user-id is determined by the system and is sent to the e-mail address given during the registration process. The registration allows the CAA to gather usage statistics (see Section 1.2.4) and more importantly to monitor the system performance in order to improve it, when and where necessary. In addition, the users can save their configurations of datasets or plots for using them during future requests. Furthermore, occasionally poor-quality data products may have been delivered and ingested into the system, and in such cases the CAA can find from the usage database who had requested those data and these users can then be informed about the presence of better quality products.

1.4.1.1 Web Interface Figure 1.5 shows the front page of the CAA website after a user has successfully logged into the system. The user can now find USER AREA in the left-hand menu bar that currently holds user-defined lists of profiles that are useful when searching or plotting certain variables regularly. In “Modify User Details” one can modify user details such as password or contact e-mail address. Currently the following data services are provided (see the left-hand menu bar): CAA Data Download Area: allows users to perform data requests, using filters

given in the entry page. CAA Graphical Products: allows users to display some of variables. CAA Quick-look Plots: allows users to view pre-generated quick-look plots that

are based on non-validated data sets processed by instrument teams or CSDS. CAA Inventory Plots: allows users to view the completeness of the database.

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Fig. 1.4 The front page of the CAA website (http://caa.estec.esa.int/) in early 2009

There are currently a little more than 200 datasets from each spacecraft in the CAA data repository. By setting values for Start Time, Stop Time, Observatory, Experiment, Measurement Type, and Instrument Type, one can filter datasets to be shown on the GUI, thus speeding identification of the datasets needed by a user. Some, all or none of these selections may be set. For instance, if only Start and Stop Time are selected, then all the datasets that exist for this interval will be shown. If Time fields are left empty, this defaults to the time range of the entire mission.

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Fig. 1.5 The front page of the CAA website after login into the system

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For Observatory, the option Cluster Multi refers to the products that contain data from more than one spacecraft. Measurement Type is a general description of the type of measurement. Instrument Type supplies information about the nature of the instrument used to obtain the data. Often the same physical parameter can be obtained from more than one type of instrument. For example, electron density can be derived from particle detector, Langmuir probe, wave spectral or active resonance sounder data. After the selection, available datasets are listed by Observatory (see Fig. 1.6). Clicking “Expand/Collapse All” will toggle the expansion/collapse of the results. When expanded, the datasets available are listed. The following details are provided for each dataset: Dataset Name: with check box beside it to indicate if the user wishes to download

this dataset. Notice that this Dataset Name needs to be known for the use of command-line interface (see next section). Result Timespan: tells the timespan where this dataset is available on the CAA. Note that this does not tell anything about the coverage of the dataset which can be examined via inventory plots. Dataset Details this link opens up a new window with the dataset metadata details, e.g., variables available in the dataset. Users must select each dataset they wish to download by clicking on the checkbox. Currently there is a limit of about 1 GB on the amount of data one can download at one time. This limit is necessary because the web request is executed immediately and larger requests may time-out the Internet connection before completion. The requests of larger amounts of data can be done via command-line interface (see Section 1.4.1.2), which supports batch operation and currently has a limit of 50 GB. After selecting the datasets, possibly modifying the time interval and then clicking on “Search”, the available datasets will be listed, including an estimated total size of uncompressed files given in brackets. There is also again a link to the dataset information. Here the users must select each dataset they wish to download, by clicking on the checkbox, and then click “Download”. In addition the user may also choose to download the files in a single file (default) or in shorter intervals (e.g. hourly or daily files). Next the files are combined and compressed into a single zip file. Once this process has completed, the new page shows a link “Search results ready for download”. Selecting this link, the user will be prompted for their local directory where the file will be stored in the .zip format.

1.4.1.2 Command-Line Interface During year 2007 a command-line tool was introduced which allows users to bypass the graphical interface to gain faster access to the data products. This facility is utilized to make automated enquiries about the arrival of new files on the CAA database and also for data analysis and visualization software tool to gain direct

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Fig. 1.6 Results of searching datasets. For each experiment the datasets are grouped into smaller sets helping the faster identification of the right dataset

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access to the CAA database. For example, when new files have been ingested into the system, a user can run a script that will automatically transfer the appropriate files from the CAA to the users’ own local systems. The data download volume via the command-line interface is three times greater than via the web forms interface, and it supports batch operation so that large jobs can be queued for offline processing. McCaffrey [4] defines the format, syntax and mechanism of this tool that allows users to submit requests from a command line using the GNU wget tool [GNUWGET]. The non-CEF files delivered (e.g., for graphical products) are direct copies of the original files, whereas the CEF files delivered cover exactly the time span specified in the request. If the requested parameters are correct, and there are data available, the request may not be executed immediately if there are many other jobs currently executing or if the request is large. When a request is scheduled, the user will receive a file called CAA Info.log.X that indicates a URL where the completed file can be retrieved. The following example URL is a request of three CEF products, covering an interval of four days to be split to daily files: http://caa.estec.esa.int/caa query/?uname=uname&pwd=pwd&dataset id=C1 C P EDI EGD,C1 CP EFW L3 P,C1 CP FGM FULL&time range=2001-02-01T00: 00:00Z/2001-02-05T00:00:00Z &file interval=1day where C1 CP EDI EGD, C1 CP EFW L3 P, and C1 CP FGM FULL are the datasets for electron gyroperiod, 4-s averages of spacecraft potential and fullresolution magnetic field, respectively. Notice that CEF is a default format, but one can also request data in CDF format. The job size is over the ‘immediate execute’ limit, and will therefore be scheduled. When complete, the software creates a zip file and alerts the user via email that the file is available for download (if the parameter ‘notify’ is not specified, a notification email is sent as default).

1.4.2 Visualization The CAA provides three visualization utilities. The main graphics tool is “CAA Graphical Products” that displays variables using the calibrated CAA data products. The “CAA Quicklook Plots” are produced outside the CAA and may be based on quick calibration routines. “CAA Inventory Plots” provide a view on the coverage of the CAA data products.

1.4.2.1 CAA Graphics At http://caa.estec.esa.int/caa/graphics.xml one can display some variables that are either variables in datasets (e.g. electric or magnetic field components) or results of some data manipulation (e.g. omni-directional energy spectrograms for electrons

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Fig. 1.7 Selecting variables for graphical display. At the moment there are about 100 variables for each spacecraft that can be displayed. Selected variables can be saved as a profile for future use

and ions). Figure 1.7 shows the variables of Whisper available for graphics. The list of selected variables are displayed in a window where the order of the variables can be changed, and if the set of variables is frequently used, one can save it as a profile for future use. The graphics are based on IDL software libraries that are used to read, manipulate and plot the variables. These scripts are made available for download from the CAA website (see software in the menu bar). Figure 1.8 shows an example of the plot for a 4-h interval on 17 March 2001. Under “Plot Type”, one can find four types of plots, including pre-generated 1h, 6 h and 1 day plots that are created when new data files are ingested into the system. Selecting “On demand”, one can specify any interval (up to one orbit) for which the selected panels will be displayed.

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Fig. 1.8 Example of graphical display for a 4-h interval on 17 March 2001

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1.4.2.2 Quick-Look Plots The quick-look plots, produced by the PI teams or the CSDS, may be based on simple calibration routines and are generally not suitable for scientific analysis or publication without prior discussion with the producer. For CSDSweb plots, please note that the plot availability on the CAA is delayed. The complete set of plots is available at the CSDSwebsite (http://www.cluster.rl.ac.uk/csdsweb-cgi/ csdsweb pick). The quick-look plot utility also allows browsing of the pre-generated WBD (Cluster Wide-Band Plasma Wave Investigation Experiment) science plots. The WBD plots can also be retrieved through “Search”. The overview plots can be downloaded in both postscript and png format under Cluster-Multi Observatory whereas the high-resolution (30 s) WBD gif plots are produced for each spacecraft individually and can be downloaded under each spacecraft. 1.4.2.3 Pre-generated Inventory Plots The inventory plots give an overview of the coverage of the database for a number of datasets for each instrument and spacecraft. During the ingestion process, each data file is examined and any time step longer than 5 min is recorded as a data gap and is shown in the inventory plot. The data used by the inventory plots are generated subsequent to ingestion, and the inventory plots are produced later usually at the end of the day, and so there may be a delay between ingestion (i.e. the time when the data become available for downloading or plotting) and an update of an inventory plot. The following three colours are used to indicate the data content: Blue: the data exist (notice that the data can be fill values) Purple: there is a data gap White: no data exists in the database

In addition the top two panels tell the presence of predicted events (top panel) and the spacecraft mode (second from top) where blue is used for normal mode and red for burst mode (higher data rates).

1.4.2.4 User-Defined Inventory Plots Users can also produce their own inventory plots over intervals that are longer than 6 h in the data search area. Selecting one or more datasets and clicking then on “INVENTORY”, one gets an inventory plot that shows the data coverage for the selected time interval. Notice that these plots are generated on the fly using the current ingestion status. So some data may appear on these that are not yet on the pre-generated inventory plots.

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1.4.3 Support Tools There are some software tools available for the users under “Software” in the lefthand menu bar. The software, called Qtran (Queen Mary File Translator), can translate files between CDF and CEF. Notice that if a user requests to download a CEF file in CDF format, this is the tool used to perform the conversion. The same software is also able to read other record-oriented ASCII data files and may help with translation from ASCII into the recommended exchange format. The QSAS (Queen Mary Science Analysis System) software [Allen, Chapter 14] can manipulate CEF files and visualize multi-instrument and multi-spacecraft products. Both the Qtran and QSAS software are maintained at the Imperial College of London. The CAAtools package provides a set of tools for checking the products against the metadata dictionary and CEF specification. The CEF product validation part of the package is made available for download, and the library is also used by the CAA Matlab toolbox for reading CEF datasets. For Matlab users there are two toolboxes for reading, writing, manipulating and plotting CEF files. The function cefRead can be applied directly to gzipped CEF files. Documentation and the Matlab source files are provided under Software. For IDL the CAA has developed two packages that simplify the process of reading and plotting data. The cef read procedure provides a single command to load a CEF file into IDL. Options include to load only a sub-set of variables or to restrict the reading to a set of time intervals. The software will also handle conversion of the time information into MJD (Modified Julian Date) or CDF epoch formats. The documentation provides the full details of the utility as well as several examples of different reading options and a full example of generating multi-panel plots of simple scalar and vector parameters. For users not wishing to do their own plotting in IDL an additional package provides an extensive set of options to generate high quality plots of CEF products including scalars, vectors and multi-dimensional arrays. The software makes use of the cef read software described above and is based on the software used within the CAA to provide pre-generated and on-demand graphical products.

1.5 Science Data Products The CAA holds three types of science data files: calibrated and uncalibrated data files from the instrument teams that are available in CEF format; raw data files received from the ESOC; CSDS primary and summary parameters (PP and SP, respectively) data files. The CSDS files are preliminary survey data and not calibrated to the level done within the CAA and are so not suitable for publication without discussion with the relevant instrument team.

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1.5.1 CAA Products The key CAA science data products are the datasets that have been calibrated and validated within the CAA. Each team performs detailed calibration of the data to the level suitable for optimum scientific return. However, all data cannot be validated manually, and thus the data files can still contain features that represent instrumental effects rather than physical processes. It is therefore important that the users read all documentation and caveat information related to the data and contact the CAA for specific questions or problems. At the moment there are over 200 different datasets from each spacecraft, and even in this phase of the project new datasets can still appear into the system. In summer 2008 approximately the first 5 years (2001–2005) of observations have been ingested, and the following 4 years (2006–2009) will become available before summer 2010. In addition, large-scale reprocessing of some products is planned to improve quality and consistency, which highlights the benefit of the cross calibration working group, which has helped to identify and solve calibration issues. The total number of CEF and other format data files that are currently active (i.e. latest version) is in excess of 3.5 million with a total uncompressed volume equivalent to over 40 TB. The pre-generated plot panels amount to more than twice this number of files although they require much less disk space. In addition there remains a large volume of raw and some Level-1 data that are not yet available via the CAA catalogue system but that are being added as time and resources permit.

1.5.2 Cluster Raw Data System For the second extension of the Cluster mission, starting in January 2006, there was a change in the distribution of the raw data. Earlier, the raw data collected by ESOC were transferred to CDROM (Raw Data Media – RDM) and mailed to about 70 recipients. Now the data are transferred over the network from ESOC to the CAA from where they can be accessed by the users. The CAA is also working to provide a full online archive of the RDM from the entire mission by copying the existing CDs. Notice that these data primarily useful to the instrument teams that are able to decommutate the data content and produce the instrument products in physical units. Currently the CAA does not provide access to the PI software. For automated access of the RDM data, one can use HTTP GET method either within a web browser address bar or using a command line based http browser (e.g. wget) tool: http://caa.estec.esa.int/cgi-bin/caa rdm?key1=value1&key2=value2&. . . Both the keyword and the value are treated as case insensitive. The files delivered are direct copies of the contents of the original RDM volume. The details of the utility including the keywords and their values are explained by Perry [5].

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1.5.3 CSDS Products The raw Cluster data files are transferred from ESOC to the national Data Centres (DCs), previously on CD-ROMs, and since January 2006 through the network via CAA. The national DCs process the raw data using PI software and produce physically meaningful parameters (fields, particle fluxes, temperatures, spectral densities, etc.) for those experiments for which the DC is responsible. The results are stored as CDF files. These files are then exchanged with the other national DCs so that each one has a full set, which is then made available to the scientific users in that country. The interfacing between the users and the DC, as well as among the DCs themselves, is the CSDS Data Management System (DMS), a software package that has been developed especially for this purpose. A number of JSOC (Joint Science Operations Centre) products (e.g. predicted orbit and event files, scientific events catalogue) are also made available to the local users via the national DC. The key CSDS datasets are Prime Parameter Data Base consists of 65 parameters from all four spacecraft

averaged over one spin (4 s). Summary Parameter Data Base consists of 86 parameters from only one space-

craft and averaged over 1 min; auxiliary parameters such as position and spin orientation are also included. Event Catalogues provide data concerning predicted and observed scientific events for the Cluster mission. CSDS auxiliary data contains such information as tetrahedron quantities, orbit number, position, velocity and attitude of spacecraft. All the vector quantities are given in the GSE coordinate system. The rotation angle between the GSE and GSM is also given, enabling a straightforward and unambiguous conversion. CSDS products that can be found at http://sci2.estec.esa.nl/cluster/csds/ ring.html were not initially part of the CAA. However, now these products are being transcribed into CEF format files and ingested in the CAA and can be used in combination with CAA products.

1.6 Cross-calibration Activity The CAA cross-calibration working group is actively supported by the instrument teams with two to three annual workshops; for the list of the past workshops, see http://caa.estec.esa.int/caa/cross-cal.xml. This activity is invaluable for assessing and improving the quality of the datasets. Although the active participants in the working group come mainly from the instrument teams, anyone interested in the calibration issues of various measurements are welcome to participate in these workshops.

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The key issues in the meetings have been: To improve the calibration of dc magnetic field measurements much better than

1 nT To determine the total plasma density using various measurements techniques To calibrate the dc electric field measurements using and comparing various data

sources To determine the E B-drift velocity using and comparing various data sources To compare energy fluxes of electrons and ions between different experiments To compare power spectral densities of wave measurements, including both elec-

tric and magnetic field wave components

1.7 Future Planning The CAA development will continue to enhance the core functionality of the system, to reprocess existing data files (2001–2005) and to expand the coverage of the datasets to the next years (2006–2009). There will be further updates to both the web and command line data request mechanism to support the selection and delivery of the non-CEF formatted data products. These products include pre-generated graphical products supplied by the instruments teams, calibration information and reformatted raw data. The activities planned for the period leading up to the next operations review in May 2009 are as follows: Routine operations, data delivery and maintenance of the existing data access and

value-added services Production and delivery of data files from years 2006–2007 before May 2009 Monitoring system of the file ingestion processes in order to display the status

of ingestion as well as to monitor the performance of the system in the validation/ingestion procedures Development of advanced documentation service for searching and browsing the Cluster documents, i.e., a utility to search for specific reports (e.g. ESOC spacecraft anomaly information) Improvements to user interface based on user feedback and problem reports. ı Additional search and filtering options for dataset selection ı Provision of the detailed data coverage information as a CAA product (to be used by external tool developers) ı Updates to the command line interface in response to requests from tool developers ı Provision of a simple and easy to use interface Value-added software development activities

ı Adding new plotting options to the CAA graphics menu ı Provide a user selectable option to automatically include referenced products such as caveat information and documentation

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In addition some progress has also been made on the translation of CAA metadata into Space Physics Archive Search and Extract (SPASE). Automated translation of simple products is straightforward but differences between the CAA and SPASE parameter specification increase the difficulty of translation as the dimensionality and complexity of products increase. Discussions are underway with the NASA Virtual Magnetospheric Observatory at UCLA to improve compatibility.

Appendix: CEF Metadata The users are strongly advised to become familiar with the CEF metadata dictionary given by Harvey et al. [3] in order to get a full benefit of the metadata provided with the numerical data. This appendix points out some of the metadata details that users should be aware of. We have included an example of metadata from the FGM SPIN resolution data file on 1 January 2003, 0–1 UT, which is given in the end of this appendix. The user should be aware that the delivered files to the users and the actual source files in the CAA database are not identical. The source files can be of any length and most of the metadata are usually given in detached header files. When the data are requested by the user, CAA software tools are used to create a file of the desired interval from the source files and the metadata are included in the file. The FILE NAME starts with the dataset name and the requested interval followed by the version number that tells the latest ingestion date of all input data files used for the requested file, which is 2006 August 15 in the case of the example file. The top-level metadata provides some general level information about the mission and the experiment: MISSION: all MISSION metadata are the same for all datasets and are provided

by a detached MISSION header file. OBSERVATORY: There are four OBSERVATORY header files, one for each

Cluster spacecraft. These metadata are the same for all datasets from the same spacecraft. EXPERIMENT and INSTRUMENT: these metadata provide some details of the experiment and are identical to all the datasets of one experiment on one spacecraft. INSTRUMENT CAVEATS: the instrument level general caveats are given here, the relevant dataset is given here. This may include references to external files. The important part of metadata are given at the dataset level and are global to the all files of the given dataset. Some of the useful keywords are: DATASET ID is a unique identifier of the dataset, which is also used in the be-

ginning of the filename. This ID is needed when requesting data via the command line interface. DATASET TITLE is a concise description of the dataset. DATASET DESCRIPTION provides a detailed description of the dataset.

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TIME RESOLUTION is a time interval between two data points, expressed

in seconds. If this is not constant, the two further keywords, MIN TIME RESOLUTION and MAX TIME RESOLUTION, must be used. PROCESSING LEVEL tells the level to which the data have been processed. Possible values are: Raw, Uncalibrated, Calibrated, Derived, and Auxiliary. DATASET CAVEATS provides miscellaneous information about the dataset. This may include references to external files. LOGICAL FILE ID is the same filename. VERSION NUMBER is the date of the latest ingested file used to create the requested file. DATASET VERSION lists all the individual files used to produce the requested file. FILE CAVEATS provides specific caveats of individual files. This may include references to external files. FILE TYPE is normally CEF but for plots and some other files it can be something else. In principle any type of file including binary files can be included in the CAA database as long as a proper detached header is provided. FILE TIME SPAN tells the requested time interval.

Each parameter is described with a number of useful keywords where the most important ones are: CATDESC provides a concise description of the parameter. COORDINATE SYSTEM provides an acronym of a coordinate system (for

vectors, tensors or their components). Allowed acronyms are provided by Harvey et al. [3]. DELTA PLUS (DELTA MINUS) provides the number of units (of the parameter) to be added to (or be subtracted from) the nominal value to obtain the upper (or lower) limit of the parameter interval within which the data was acquired. This is used in particular with time tags to provide the time interval where the data value is valid. DEPEND 0 ties explicitly the parameters to the independent variable parameter(s) on which it depends. FIELDNAM describes the parameter and which can be used, for example, to give a title for a plot (use LABLAXIS for the axis label). This could be the same as CATDESC. Note, however, that while FIELDNAM is optional, CATDESC is not. FILLVAL is used to replace bad or missing data. FRAME VELOCITY is important to the physical parameters whose values depend upon the motion of the coordinate system in which they are measured. Three possible values are accepted: Observatory (default); Inertial (i.e. GEI); EarthCorotating. LABEL i is used for multi-dimensional parameters to label individual components (as LABLAXIS is not sufficient to describe the variables).

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LABLAXIS can be used to label the y-axis of a plot or to provide a column

heading for a data listing. For more than one-dimensional parameters, the labels can be given in LABEL i. QUALITY provides a quality of the parameter, with the following values: 0 – Not applicable; 1 – Known problems, use at your own risk; 2 – Survey data, not for publication; 3 – Good for publication, subject to PI approval; 4 – Excellent data which has received special treatment. REPRESENTATION is used to provide essential information describing vectors and tensors; for details, see Harvey et al. [3]. SI CONVERSION factor is required to take the archived value to the corresponding value in a standard SI unit. For instance, “1:0E 9 > T” is used to transform the magnetic field data stored in nanotesla (nT) into tesla (T). SIGNIFICANT DIGITS provides the number of decimal digits required to preserve the precision of the parameter and can have a value of any positive integer. SIZES provides the dimensions of the array that is required for any parameter represented by more than one component (vectors, tensors, spectral arrays, etc.). For example, SIZES D 3 is for a vector of 3 components. TENSOR ORDER: 0 for scalars (default value), 1 for vectors (e.g., magnetic field or velocity), 2 for tensors (e.g., plasma pressure). UNITS: this provides the unit of the parameter that can be indicated on the axes of a plot. If parameter has no unit, this must be specified by UNITS D “unitless”. VALUE TYPE provides identification of the value type (essential for ASCII conversion) with possible values: CHAR; DOUBLE; FLOAT; INT; ISO TIME; ISO TIME RANGE.

The following example shows the metadata for the FGM SPIN resolution data file on 1 January 2003, 0–1 UT, requested on 17 February 2009: FILE NAME = “C1 CP FGM SPIN 20030101 000000 20030101 010000 V060815.cef” FILE FORMAT VERSION = “CEF-2.0” END OF RECORD MARKER = “$” START META = MISSION ENTRY = “Cluster” END META = MISSION START META = MISSION TIME SPAN VALUE TYPE = ISO TIME RANGE ENTRY = 2000-08-16T12:39:00Z/2009-12-31T23:59:59Z END META = MISSION TIME SPAN START META = MISSION AGENCY ENTRY = “ESA” END META = MISSION AGENCY START META = MISSION DESCRIPTION ENTRY = “The aim of the Cluster mission is to study small-scale structures of the” ENTRY = “magnetosphere and its environment in three dimensions. To achieve this,” ENTRY = “Cluster is constituted of four identical spacecraft that will flight in a”

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ENTRY = “tetrahedral configuration. The separation distances between the spacecraft” ENTRY = “will be varied between 40 km and 10 000 km, according to the key” ENTRY = “scientific regions.” END META = MISSION DESCRIPTION START META = MISSION KEY PERSONNEL ENTRY = “Philippe Escoubet>[email protected] >Cluster Project Scientist” END META = MISSION KEY PERSONNEL START META = MISSION REFERENCES ENTRY = “The Cluster and Phoenix Missions>Cluster project and” ENTRY = “instrument teams>Space Sci. Rev. 79, Nos. 1-2, 1997” END META = MISSION REFERENCES START META = MISSION REGION ENTRY = “Solar Wind” ENTRY = “Bow Shock” ENTRY = “Magnetosheath” ENTRY = “Magnetopause” ENTRY = “Magnetosphere” ENTRY = “Magnetotail” ENTRY = “Polar Cap” ENTRY = “Auroral Region” ENTRY = “Cusp” ENTRY = “Radiation Belt” ENTRY = “Plasmasphere” END META = MISSION REGION START META = MISSION CAVEATS ENTRY = “*CL” END META = MISSION CAVEATS START META = OBSERVATORY ENTRY = “Cluster-1” END META = OBSERVATORY START META = OBSERVATORY CAVEATS ENTRY = “*C1 CQ” END META = OBSERVATORY CAVEATS START META = OBSERVATORY DESCRIPTION ENTRY = “Cluster-1 (Rumba)” ENTRY = “Launched: 09 Aug 2000” ENTRY = “ESA Number: 1” ENTRY = “COSPAR ID: 2000-045A” ENTRY = “USSPACECOM catalogue number 26463” ENTRY = “CSDS Code: C1” ENTRY = “ESOC FD code: S1” ENTRY = “ESA Flight Model Number: FM5” END META = OBSERVATORY DESCRIPTION

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START META = OBSERVATORY TIME SPAN VALUE TYPE = ISO TIME RANGE ENTRY = 2000-07-16T12:39:00Z/2009-12-31T23:59:59Z END META = OBSERVATORY TIME SPAN START META = OBSERVATORY REGION ENTRY = “Solar Wind” ENTRY = “Bow Shock” ENTRY = “Magnetosheath” ENTRY = “Magnetopause” ENTRY = “Magnetosphere” ENTRY = “Magnetotail” ENTRY = “Polar Cap” ENTRY = “Auroral Region” ENTRY = “Cusp” ENTRY = “Radiation Belt” ENTRY = “Plasmasphere” END META = OBSERVATORY REGION START META = EXPERIMENT ENTRY = “FGM” END META = EXPERIMENT START META = EXPERIMENT DESCRIPTION ENTRY = “Fluxgate Magnetometer” END META = EXPERIMENT DESCRIPTION START META = INVESTIGATOR COORDINATES ENTRY = “Andre Balogh>PI>[email protected]” ENTRY = “Elizabeth Lucek>PI>[email protected]” END META = INVESTIGATOR COORDINATES START META = EXPERIMENT REFERENCES ENTRY = “*CL CD CAA FGM ICD 0001 V0 1.pdf” ENTRY = “*CL CD FGM USERMAN.pdf” ENTRY = “http://www.sp.ph.ic.ac.uk/Cluster/” END META = EXPERIMENT REFERENCES START META = EXPERIMENT KEY PERSONNEL ENTRY = “Andre Balogh>PI>[email protected]” ENTRY = “Elizabeth Lucek>PI>[email protected]” END META = EXPERIMENT KEY PERSONNEL START META = EXPERIMENT CAVEATS ENTRY = “*CL CQ FGM CAVF.txt” END META = EXPERIMENT CAVEATS

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START META = INSTRUMENT NAME ENTRY = “FGM1” END META = INSTRUMENT NAME START META = INSTRUMENT DESCRIPTION ENTRY = “FGM Experiment on Cluster C1” END META = INSTRUMENT DESCRIPTION START META = INSTRUMENT TYPE ENTRY = “Flux Feedback” END META = INSTRUMENT TYPE START META = MEASUREMENT TYPE ENTRY = “Magnetic Field” END META = MEASUREMENT TYPE START META = INSTRUMENT CAVEATS ENTRY = “*C1 CQ FGM CAVF” END META = INSTRUMENT CAVEATS START META = DATASET ID ENTRY = “C1 CP FGM SPIN” END META = DATASET ID START META = DATA TYPE ENTRY = “CP>CAA Parameter” END META = DATA TYPE START META = DATASET TITLE ENTRY = “Magnetic field, spin resolution” END META = DATASET TITLE START META = DATASET DESCRIPTION ENTRY = “This dataset contains spin resolution measurements of the magnetic field vector” ENTRY = “ from the FGM experiment on the Cluster C1 spacecraft” END META = DATASET DESCRIPTION START META = CONTACT COORDINATES ENTRY = “Elizabeth Lucek>PI>[email protected]” END META = CONTACT COORDINATES START META = TIME RESOLUTION ENTRY = 4 END META = TIME RESOLUTION START META = MIN TIME RESOLUTION ENTRY = 4.412 END META = MIN TIME RESOLUTION

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START META = MAX TIME RESOLUTION ENTRY = 3.636 END META = MAX TIME RESOLUTION START META = PROCESSING LEVEL ENTRY = “Calibrated” END META = PROCESSING LEVEL START META = ACKNOWLEDGEMENT ENTRY = “Please acknowledge the FGM team and ESA Cluster Active Archive” ENTRY = “ in any publication based upon use of this data” END META = ACKNOWLEDGEMENT START META = DATASET CAVEATS ENTRY = “*C1 CQ FGM CAVF” END META = DATASET CAVEATS START META = LOGICAL FILE ID ENTRY = “C1 CP FGM SPIN 20030101 000000 20030101 010000 V060815” END META = LOGICAL FILE ID START META = VERSION NUMBER ENTRY = 060815 END META = VERSION NUMBER START META = DATASET VERSION ENTRY = “Merged file, the dataset version for each segment follows: ” ENTRY = “2003-01-01T00:00:00Z/2003-01-01T01:00:00Z, C1 CP FGM SPIN 20021231 092502 20030102 182906 V01” ENTRY = “ 01” END META = DATASET VERSION START META = FILE CAVEATS ENTRY = “CAA Merged File - $Id: cefmerge.c,v 1.23 2008/08/06 14:56:43 cperry Exp cperry $” ENTRY = “The file caveats for each segment follows:-” ENTRY = “2003-01-01T00:00:00Z/2003-01-01T01:00:00Z C1 CP FGM SPIN 20021231 092502 20030102 182906 V01” ENTRY = “Calibration parameters have been estimated using the Fourier analysis” ENTRY = “ method, solar wind analysis and the range jump correction method.” END META = FILE CAVEATS START META = FILE TYPE ENTRY = “cef” END META = FILE TYPE START META = METADATA TYPE ENTRY = “CAA” END META = METADATA TYPE

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START META = METADATA VERSION ENTRY = “2.0” END META = METADATA VERSION START META = FILE TIME SPAN VALUE TYPE = ISO TIME RANGE ENTRY = 2003-01-01T00:00:00.000Z/2003-01-01T01:00:00.000Z END META = FILE TIME SPAN START META = GENERATION DATE VALUE TYPE = ISO TIME ENTRY = 2009-02-17T15:49:51Z END META = GENERATION DATE START VARIABLE = time tags C1 CP FGM SPIN PARAMETER TYPE = “Support Data” CATDESC = “Interval centred time tag” UNITS = “s” SI CONVERSION = “1.0 > s” SIZES = 1 VALUE TYPE = ISO TIME SIGNIFICANT DIGITS = 24 FILLVAL = 9999-12-31T23:59:59Z FIELDNAM = “Universal Time” LABLAXIS = “UT” DELTA PLUS = half interval C1 CP FGM SPIN DELTA MINUS = half interval C1 CP FGM SPIN END VARIABLE = time tags C1 CP FGM SPIN START VARIABLE = half interval C1 CP FGM SPIN PARAMETER TYPE = “Support Data” CATDESC = “Half averaging interval length” UNITS = “s” SI CONVERSION = “1.0>s” SIZES = 1 VALUE TYPE = FLOAT SIGNIFICANT DIGITS = 6 FILLVAL = -1e30 FIELDNAM = “Half width of averaging interval” LABLAXIS = “s” END VARIABLE = half interval C1 CP FGM SPIN START VARIABLE = B vec xyz PARAMETER TYPE = ENTITY = PROPERTY = FLUCTUATIONS =

gse C1 CP FGM SPIN “Data” “Magnetic Field” “Vector” “Waveform”

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CATDESC = UNITS = SI CONVERSION = TENSOR ORDER = COORDINATE SYSTEM = REPRESENTATION 1 = SIZES = VALUE TYPE = SIGNIFICANT DIGITS = FILLVAL = QUALITY = FIELDNAM = LABLAXIS = DEPEND 0 = LABEL 1 = END VARIABLE = B vec xyz gse

“Cluster C1, Magnetic Field Vector, spin resolution in GSE” “nT” “1.0E-9>T” “1” “GSE>Geocentric Solar Ecliptic” “x”, “y”, “z” 3 FLOAT 6 -1e30 3 “Cluster C1, Magnetic Field Vector, spin resolution in GSE” “Mag Field” time tags C1 CP FGM SPIN “Bx”, “By”, “Bz” C1 CP FGM SPIN

START VARIABLE = B mag C1 CP FGM SPIN PARAMETER TYPE = “Data” ENTITY = “Magnetic Field” PROPERTY = “Magnitude” FLUCTUATIONS = “Waveform” CATDESC = “Cluster C1, Magnetic Field Magnitude, spin resolution” UNITS = “nT” SI CONVERSION = “1.0E-9>T” TENSOR ORDER = “0” SIZES = 1 VALUE TYPE = FLOAT SIGNIFICANT DIGITS = 6 FILLVAL = -1.0E30 QUALITY = 3 FIELDNAM = “Cluster C1, Magnetic Field Magnitude, spin resolution” LABLAXIS = “B” DEPEND 0 = time tags C1 CP FGM SPIN END VARIABLE = B mag C1 CP FGM SPIN START VARIABLE = sc pos PARAMETER TYPE ENTITY PROPERTY CATDESC UNITS SI CONVERSION TENSOR ORDER COORDINATE SYSTEM REPRESENTATION 1 SIZES VALUE TYPE SIGNIFICANT DIGITS FILLVAL

xyz = = = = = = = = = = = = =

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gse C1 CP FGM SPIN “Data” “Other1” “Vector” “Position of Cluster C1 in GSE” “km” “1.0E3>m” “1” “GSE>Geocentric Solar Ecliptic” “x”, “y”, “z” 3 FLOAT 7 -1.0E30

36 QUALITY FIELDNAM LABLAXIS DEPEND 0 LABEL 1 END VARIABLE = sc pos

H. Laakso et al. = = = = = xyz

0 “Position of Cluster C1 in GSE” “Position” time tags C1 CP FGM SPIN “x”, “y”, “z” gse C1 CP FGM SPIN

START VARIABLE = range C1 CP FGM SPIN PARAMETER TYPE = “Support Data” CATDESC = “Cluster C1, FGM instrument range, defined on spin resolution time line” TENSOR ORDER = “0” UNITS = “Unitless” SIZES = 1 VALUE TYPE = INT SIGNIFICANT DIGITS = 1 FILLVAL = -9 FIELDNAM = “Cluster C1, FGM Instrument Range, on spin resolution time line” LABLAXIS = “Range” DEPEND 0 = time tags C1 CP FGM SPIN END VARIABLE = range C1 CP FGM SPIN START VARIABLE = tm C1 CP FGM SPIN PARAMETER TYPE = “Support Data” CATDESC = “Cluster C1, FGM telemtry mode (burst mode/normal mode) on spin resolution time line” UNITS = “Unitless” TENSOR ORDER = “0” SIZES = 1 VALUE TYPE = INT SIGNIFICANT DIGITS = 2 FILLVAL = -99 FIELDNAM = “Cluster C1, telemetry mode on spin resolution time line” LABLAXIS = “TM” DEPEND 0 = time tags C1 CP FGM SPIN END VARIABLE = tm C1 CP FGM SPIN DATA UNTIL = EOF 2003-01-01T00:00:02.187Z,2,-15.086,7.672,8.769,19.062,31105.1,91115.5,33976.5,2,22 $ 2003-01-01T00:00:06.197Z,2,-15.017,9.020,8.156,19.323,31108.8,91119.2,33972.9,2,22 $ 2003-01-01T00:00:10.208Z,2,-14.396,9.873,5.241,18.226,31112.4,91123.0,33969.3,2,22 $ 2003-01-01T00:00:14.218Z,2,-11.938,14.285,2.235,18.750,31116.1,91126.8,33965.7,2,22 $ 2003-01-01T00:00:18.229Z,2,-11.995,15.514,5.203,20.289,31119.8,91130.6,33962.1,2,22 $ 2003-01-01T00:00:22.240Z,2,-11.672,15.160,5.497,19.907,31123.5,91134.4,33958.5,2,22 $ 2003-01-01T00:00:26.250Z,2,-11.143,13.097,7.096,18.602,31127.2,91138.1,33954.9,2,22 $ 2003-01-01T00:00:30.261Z,2,-12.215,12.659,6.489,18.751,31130.8,91141.9,33951.3,2,22 $

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References 1. Allen A., S.J. Schwartz, C. Harvey, C. Perry, C. Huc, P. Robert, Cluster Exchange Format – Data File Syntax, DS-QMW-TN-0010, v2.4, 04 March 2008. URL: http://caa.estec.esa.int/ caa/documentation.xml 2. Escoubet, C. P., M. Fehringer, and M. Goldstein, The Cluster mission, Ann Geophys., 19, 1197, 2001. 3. Harvey C.C., A.J. Allen, F. Dériot, C. Huc, M. Nonon-Latapie, C.H. Perry, S.J. Schwartz, T. Erikssony and S. McCaffrey, Cluster Metadata Dictionary, CAA-CDPP-TN-0002, v2.3, 03 March 2008. URL: http://caa.estec.esa.int/caa/documentation.xml 4. McCaffrey, S., Command Line Query Interface, Doc: CAA-EST-CMDLINE-0001, v2.0, 06 April 2007. URL: http://caa.estec.esa.int/documents/CAA-EST-CMDLINE-001.pdf 5. Perry, C., Raw Data Network Delivery Interface Document, Doc CAA-EST-ID-0001, v1.2, 28 November 2005. URL: http://caa.estec.esa.int/documents/ CAA-EST-CMDLINE-001.pdf

Chapter 2

ASPOC Data Products in the Cluster Active Archive K. Torkar and H. Jeszenszky

Abstract The instrument ASPOC (Active Spacecraft Potential Control) controls the electric potential of the Cluster spacecraft by means of an ion beam. This modification of the charge balance improves the plasma measurements on board. Beneficial effects have also been observed for the electric field measurements by double probes (EFW). Comprehensive knowledge about the status of the instruments including the ion beam current is necessary to correctly interpret spacecraft potential data. This paper provides an overview of the instrument modes and the parameters contained in the ASPOC data sets in the Cluster Active Archive. A few examples illustrate the relation between instrument modes and data.

2.1 Introduction The ASPOC (Active Spacecraft Potential Control) instruments for the Cluster mission have been described by Torkar et al. [6]. The primary objective of ASPOC is to insure the effective and complete measurement of the ambient plasma distribution functions down to low energy. With the exception of very rare eclipse time intervals the Cluster spacecraft are illuminated by the Sun, and photo-electrons are emitted from the surface. Throughout the Cluster orbit, i.e. outside the plasmasphere, emitted photo-electrons will dominate over collected plasma electrons. A balance between escaping and collected electrons is achieved at a positive potential forcing low energy photoelectrons to orbit back to the spacecraft, allowing only a fraction of the photoelectrons at higher energies to escape and be in current balance with collected plasma electrons. Ions can be neglected because of their low mobility compared to the electrons. The resulting uncontrolled potentials may reach C50 V and more in regions of the magnetosphere with tenuous plasma. In order to control the electrical potential of the spacecraft, the ASPOC instruments emit a beam of positive indium ions (115 amu) at energies of about 6–9 keV K. Torkar () and H. Jeszenszky Space Research Institute, Austrian Academy of Sciences, Schmiedlstrasse 6, 8042 Graz, Austria e-mail: [email protected]


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K. Torkar and H. Jeszenszky

and currents up to about 30 A. Typical currents applied in the mission were between 10 and 20 A. The emission of positive charges from the spacecraft balances the excess of charge accumulating on the vehicle from interactions with the environment. By adjusting the positive emission current, the spacecraft potential can thus be adjusted to single-digit positive voltages. As a result of the equilibrium between the relevant currents of photo-electrons generated at the spacecraft surface, plasma electrons from the environment, and the ASPOC ion beam current, the spacecraft potential will be clamped to a potential determined by a current balance between ASPOC-generated ions on the one hand and escaping photoelectrons minus collected ambient electrons on the other hand. In a tenuous plasma the latter term can be neglected. The resulting improvement of both particle and electric field measurements is most effective in low plasma density environments and boundaries thereof. In these environments the equilibrium potential of the spacecraft is not only strongly fluctuating together with the variations of plasma density, but also the absolute value of the potential easily reaches tens of volts positive. As a consequence, the bulk of photo-electrons will return to the surface and the plasma electron detectors, where the resulting high count rates let the micro-channel plates age at a faster rate. The energies and trajectories of plasma electrons and ions are modified in the potential well around the spacecraft, thereby complicating the interpretation of the distribution functions and the calculation of plasma moments. The improvement of the electron measurements by a controlled spacecraft potential is illustrated in Fig. 2.1 adapted from Torkar et al. [7]. It shows energy-time spectrograms of field-aligned electrons measured by the PEACE-LEEA sensors (for an instrument description see Szita et al. [5]) of Spacecraft 1 (panel a) and 4 (panel b) over a 2-h time interval starting at 06 UT on May 21, 2002. The electron features in the 10–100 eV decade clearly visible on spacecraft 4 – where ASPOC reduced the potential to 8 V – are not discernible on spacecraft 1, where the uncontrolled potential peaked at 47 V. The spacecraft potential is measured by the EFW instrument (Gustafsson et al., [2, 3]). Its probes are controlled to stay within 1–2 V relative to the ambient plasma and thus provide a reference for the measurement. A reduction of the spacecraft potential also helps to avoid wake artefacts in electric field measurements by the double probes, which may occur in cold, streaming plasma, e.g., polar wind [1]. Under similar conditions, the ion spectrometer CIS [4] could detect cold ion beams (HC and OC ) only while ASPOC was operating. As the photo-emission is fairly stable, the potential of a spacecraft (without control) reflects the variation of the plasma electron current and thereby images the electron density and temperature. As the temperature effect is relatively small, the uncontrolled spacecraft potential is often used as an estimator for plasma density. However, the introduction of an artificial ion current for control purposes changes the relationship dramatically. Under the influence of a constant artificial ion beam current, the controlled spacecraft behaves like a strongly biased plasma probe with rather small residual variations of the potential. As illustrated in Fig. 2.2, a good correlation between the uncontrolled potential (spacecraft 1, black line, scale on the left hand side) and the controlled potential (here represented by spacecraft 3, green

2

ASPOC Data Products in the Cluster Active Archive

a

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C1 2002141 0600 PA 180

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Fig. 2.1 Energy-time spectrograms of field-aligned electrons from the PEACE-LEEA sensors of spacecraft 1 (panel a) and spacecraft 4 (panel b) plotted as function of time on May 21, 2002, from 06 to 08 UT

line and dots) may still exist. The potential of spacecraft 3 is shown in two different ways. The full, green line refers to the common scale with spacecraft 1 on the left hand side and demonstrates the significant reduction of the potential. The same data set is also shown by the green dots for which the right hand scale is valid. The good correlation between the residual variations of the controlled potential on spacecraft 3 with the uncontrolled values on spacecraft 1 is obvious. Thus, by inserting the ASPOC ion current into the current balance equation for the controlled spacecraft one can deduce the uncontrolled potential and use it for density estimations as usual.

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Fig. 2.2 Spacecraft potential (raw potential between the probes and the spacecraft body) measured by EFW (Electric Fields and Waves, [2]) on spacecraft 1 (black, scale at the left) and 3 (both the green line with scale at the left and green dots with scale on the right) on April 30, 2002, from 10:20 to 12:00 UT

2.2 Instrument Overview 2.2.1 Ion Emitters The ion emitters are liquid metal ion sources using indium as charge material. A needle is mounted in a reservoir with indium, which has to be elevated to operational temperature (well above the melting point of indium at 156ıC by an attached small heater. The melting process is initiated by command and takes about 12–20 min. When the specified temperature has been reached, high voltage is turned on and ramped up until the field emission process around the liquid indium at the tip ignites and an ion beam is generated. As soon as the ion beam appears, the high voltage supply is switched into a current controlled mode where the emission current is being set, while the extraction voltage adjusts itself to the conditions of the emitter. The emitters are operated one at a time. For lifetime and redundancy, each instrument holds eight emitters, arranged in two “modules” with four emitters each. All emitters within a module are connected to a single high voltage circuit. The selection of the active emitter is made by heating one of them (the tip curvature of cold emitters with solid indium is not suitable for field emission).

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2.2.2 Currents in the Emitter System The behaviour of the ion beam current is better understood with some knowledge of the currents flowing in the emitter system. At first, there is the current of the emitted ion beam. This current is referred to as ion current, beam current, or emission current. It continues through the ambient plasma and is closed by other currents to the spacecraft surface, particularly the photoemission current. ASPOC ions returning to the spacecraft can be totally neglected even if the ion beam is emitted perpendicular to the magnetic field. Secondly, there is the total current delivered by the high voltage supply to the emitter. This current includes the beam current and internal loss currents (e.g. the current to the extraction and beam focusing electrodes), and may therefore be larger than the beam current. There are two major types of loss currents: currents from ions hitting the extractor electrode, and leakage currents through insulators. The percentage of extractor electrode currents with regard to the total current is small (0–20%) for small to medium currents and may increase from 30% to 50% for currents of about 50 A. The typical emission currents applied on Cluster range between 10 and 16 A. They set an upper limit to the spacecraft potential on the order of 6–8 V. The emission current of an emitter may be increased to maximum current over a short period (between 30 s and a few minutes) as a precaution to remove any contamination from the emitter, thereby ensuring that the operating voltage remains within operational limits. This procedure is called “cleaning”.

2.2.3 Instrument Modes The most widely used active mode of the instrument is the “constant total current mode” (ITOT). It sets a constant output current of the high voltage unit, which includes any losses inside the lens system. Experience has shown that the resulting emission of an almost constant ion current fulfils all requirements for spacecraft potential control in the magnetosphere and the solar wind even without on-board feedback from measurements of the spacecraft potential. In “constant ion current mode” (IION) the processor of the instrument reads the monitor of the outgoing beam current and adjusts the output current of the high voltage supply to compensate for any losses in the system. This mode has been used during commissioning only. In the two available, so-called feedback modes, a measurement of the spacecraft potential is supplied to ASPOC by either the electric field experiment (EFW) or the electron analyser (PEACE) and this information is then used to adjust the beam current in order to maintain a constant value of the potential in a closedloop scheme. This mode is called feedback mode with EFW (mode FEFW) or feedback mode with PEACE (mode FPEA). The measurements of the spacecraft potential are updated once every spin and sent to ASPOC via dedicated serial, digital inter-experiment links. The mode FEFW has been tested successfully during commissioning. Unfortunately, active soundings of the WHISPER instrument cause

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spikes in the potential information transmitted on board. The control software could not handle these spikes, so that this feedback mode could not be used in the nominal mission. The feedback mode with PEACE suffered from the difficulty to provide a reliable potential estimator from the electron spectra onboard, and was not used in the mission at all. In standby mode (STDB) both the emitters and their heaters are turned off. The standby mode is also the safe mode of the instrument, to which it returns autonomously under certain error conditions. The transition into standby mode also clears all error flags and the emitter selection, and disables high voltage and the heaters. In order to reduce the time before emission starts, a “hot standby” mode (HOTS) keeps the indium in a liquid state. This mode can be used to interrupt the ion emission by command, without change of modes or emitters before and after the break. The re-ignition time is reduced to the time required to sweep the high voltage (less than a minute). A “test and commissioning” mode (T&C) varies the total ion current in steps of 8 or 16 s with 2 or 4 A current increments. This mode has been used occasionally to establish the current-voltage characteristics of the spacecraft. A technical mode (TECH) is available for low-level commanding during commissioning and re-commissioning of emitters. Start-up (STUP) is a state of the instrument at the beginning of an active mode when the emitter is being warmed up and ion emission has not yet started. Depending on ambient temperature and emitter condition it takes about 12–20 min to reach a temperature inside the emitters which is sufficient to ignite the ion beam. Within this period the “instrument mode” reported in telemetry is already the commanded target mode, although there is no ion emission yet.

2.3 ASPOC Datasets in the Cluster Active Archive The ASPOC Datasets in the Cluster Active Archive are listed in Table 2.1. All data sets are Cluster Exchange Format (CEF) files, except the textual caveat description. The caveat information consists of an automatically generated part (CEF) and a manually generated part (text) added after inspection of the data produced in the batch process. The automatically generated caveats shall help the user to assess the quality. The production software derives a quality parameter from the total current consumed by the ion emitter and the emitted ion current. In the typical mode of operation a constant current is applied to the ion emitters. If internal loss currents can be neglected, the emitted ion current is also constant and the resulting spacecraft potential has the best stability. In the presence of loss currents, the emitted ion current and with it the spacecraft potential will start to fluctuate. Table 2.2 summarises the definition of the quality levels. There are new entries whenever the instrument mode changes, or when the commanded emission current changes.

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Table 2.1 ASPOC data sets Product Description IONC ASPOC ion beam current at a sampling interval of 0.5 s IONS Snapshots (samples of 8.25 s duration collected every 128.8 s) of the ion beam current with a sampling interval of 0:033 s. Suitable to check current fluctuations in the beam and to resolve the current profile during the ignition or shut-down of an ion emitter STAT Comprehensive status information of the instrument at 5.15 s resolution (10.3 s for some parameters) Operating mode, including emitter start-up status and cleaning: In both of these states the beam current deviates significantly from the nominal current Emitter identification and emitter module identification: Each instrument carries eight emitters bundled into two modules with a common high voltage system within a module. Both emitters and modules may exhibit individual characteristics and performance, which may have an effect on the value and temporal behaviour of the beam current Anomaly flags: These flags give the reason for an anomaly, for example failure of ignition of an emitter Ion beam energy: The voltage applied to the emitter is equivalent to the energy of the ions in the beam Total ion source current: The current delivered by the high voltage supply into the emitter will be higher than the emitted current if internal losses are present Heater current: The current drawn by the heater element associated with an emitter Heater voltage: The voltage applied to the heater element associated with an emitter. Voltage and current together can be used to calculate not only the electrical power but also the temperature of the heater element. From this temperature, the temperature of the emitter tip can be derived Temperature of the ion source module: This parameter contains the ambient temperature of the emitter module. The temperature of the emitter tip shows a strong dependence on the heater temperature, but also some influence of this ion source module temperature Raw spacecraft potential received on board from EFW: This parameter mirrors the spacecraft potential data delivered by the instrument EFW to ASPOC on board the spacecraft. It differs from the EFW data product in the archive with respect to timing CMDH

CAVEATS

Command history with time stamps according to on-board execution time by the instrument. The execution delay may reach 1 min. Included parameters are the command code, the command counter, command mnemonic, description, and parameter (if any) Information on the status and quality of the ion emission (see the description of quality levels). Time spans correlate with commands to change the operational mode or the value of the current

ACTIVE

Mean quality level during time span Minimum quality level during time span Maximum quality level during time span Comment; a textual description associated with the average quality level value

Contains the time spans when ASPOC is switched on and is emitting a significant ion current (>1 A). Useful for quick checks whether ASPOC was operational

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K. Torkar and H. Jeszenszky Table 2.2 Quality level definition Quality flag Condition 1 Ibeam =Itotal > 0:97 2 0:92 < Ibeam =Itotal 0:97 3 0:75 < Ibeam =Itotal 0:92 4 0:30 < Ibeam =Itotal 0:75 5 0:00 < Ibeam =Itotal 0:30 8 Itotal 20A and Ibeam =Itotal 0:50 9 Ibeam D 0:0

Ion emission quality definition Excellent Good, almost completely stable Moderate fluctuations Substantial fluctuations Severe variations Cleaning No emission

2.4 Examples and Applications No specific software is required to use the data sets. However, visualisation software in IDL language originally developed for the validation of the data products is available. It allows to browse through a set of CEF files, either uncompressed or in gzip. Check boxes allow to select certain parameters. Plot options and scales can be set automatically or interactively. The plots presented in this section have been generated by this tool. Figure 2.3 shows beam current and voltage in the top and bottom panel, respectively, over a 12-h time interval for spacecraft 3. The colour bar at the bottom indicates the quality flag, which is one (excellent) for this operational interval of about 7 h. The commands to enter into active mode have been sent shortly before 04 UT (red vertical lines). It takes about 15 min (interval indicated by the yellow status bar) until the emitter is hot and ion emission starts. The time interval contained in the respective entry in the ACTIVE data set would only cover the time interval of the green status bar. Figure 2.4 shows (from top to bottom) for the same time interval the beam current, total current, and spacecraft potential (as transmitted on board from EFW to ASPOC). Noteworthy is the “bite-out” of the beam current at 18:30 UT, due to a suddenly appearing and later disappearing leakage current inside the emitter. Although the beam current decreases by about 30%, the spacecraft potential hardly shows any reaction. This shows that variations of the beam current should be taken into account for accurate studies related to spacecraft potential, but do not generally deteriorate the control of the spacecraft potential. Finally, Fig. 2.5 illustrates an application of the beam current snapshot parameter (IONS) at 33 ms resolution. The plotted interval covers 15 s around a beam turn-on. The top panel contains the standard beam current parameter (IION) which cannot fully resolve the variation of the beam current, whereas the snapshot reflects the variations very accurately, which is confirmed by the analogous variation of the spacecraft potential (bottom panel) taken from the EFW data set C3 CP EFW L2 P.

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Satellite #3 - 20040728

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Fig. 2.3 ASPOC data set visualisation with beam current, beam energy, data quality, and commands

Fig. 2.4 ASPOC data set visualisation with beam current, total current, and spacecraft potential

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Fig. 2.5 Example of ASPOC snapshot data set with corresponding variation of the spacecraft potential

2.5 Status of the Data Sets As the ASPOC instruments were finally shut down at the end of June, 2008, the data set in the Cluster Active Archive can be considered complete. Unless there are future outside requests for additions or modifications, the data set is also the final one. Files have been generated whenever the instruments were powered on, even if no ion emission took place. This is the case for many data sets in the extended mission due to exhaustion of the ion emitter reservoirs. Acknowledgements The authors would like to thank many teams for their valuable efforts: the CAA team for building the archive, the ASPOC team for building the instruments, the EFW and PEACE teams for good co-operation during the project, and ESOC and JSOC for operational support.

References 1. Engwall, E., A. I. Eriksson, M. André, I. Dandouras, G. Paschmann, J. Quinn, K. Torkar, Low-energy (order 10 eV) ion flow in the magnetotail lobes inferred from spacecraft wake observations, Geophys. Res. Lett 33, L06110, doi:10.1029/2005GL025179, 2006.

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2. Gustafsson, G, R. Bostrom, G. Holmgren, A. Lundgren, K. Stasiewicz, L. Ahlen, F.S. Mozer, D. Pankow, P. Harvey, P. Berg, R. Ulrich, A. Pedersen, R. Schmidt, A. Butler, A. Fransen, D. Klinge, C.-G. Falthammar, P.-A. Linqvist, S. Christenson, J. Holtet, B. Lybekk, T.A. Sten, P. Tanskanen, K. Lappalainen, J. Wygant, The electric field experiment for the Cluster mission, Space Sci. Rev. 79, 137–156, 1997. 3. Gustafsson, G., M. André, T. Carozzi, A.I. Eriksson, C.-G. Fälhammar, R. Grard, G. Holmgren, J.A. Holtet, N. Ivchenko, T. Karlsson, Y. Khotyaintsev, S. Klimov, H. Laakso, P.-A. Lindqvist, B. Lybekk, G. Marklund, F. Mozer, K. Mursula, A. Pedersen,B. Popielawska, S. Savin, K. Stasiewicz, P. Tanskanen, A. Vaivads, J-E.Wahlund, First results of electric field and density observations by Cluster EFW based on initial months of operation, Ann. Geophys. 19, 1219– 1240, 2001. 4. Rème, H., Aoustin, C., Bosqued, J. M., Dandouras, I, et al., First multispacecraft ion measurements in and near the Earth’s magnetosphere with the identical Cluster ion spectrometry (CIS) experiment, Ann. Geophys. 19, 1303–1354, 2001. 5. Szita, S., A. N. Fazakerley, P. J. Carter, et al., Cluster PEACE observations of electrons of spacecraft origin, Ann. Geophys 19, 1721–1730, 2001. 6. Torkar K., W. Riedler, C.P. Escoubet M. Fehringer, R. Schmidt, R.J.L. Grard, H. Arends, F. Rüdenauer, W. Steiger, B.T. Narheim, K. Svenes, R. Torbert, M. André, A. Fazakerley, R. Goldstein, R.C. Olsen, A. Pedersen, E. Whipple, H. Zhao, Active spacecraft potential control for Cluster – implementation and first results, Ann. Geophys 19, 1289–1302, 2001. 7. Torkar K., K.R. Svenes, A. Fazakerley, S. Szita, H. Rème, I. Dandouras, M. Fehringer, C.P. Escoubet, M. André, Improvement of plasma measurements onboard Cluster due to spacecraft potential control, Adv. Space Res 36, doi:10.1016/j.asr.2005.01.109, 2005.

Chapter 3

Cluster Ion Spectrometry (CIS) Data in the Cluster Active Archive (CAA) I. Dandouras, A. Barthe, E. Penou, S. Brunato, H. Rème, L.M. Kistler, M.B. Bavassano-Cattaneo, A. Blagau, and the CIS Team

Abstract The Cluster Active Archive (CAA) aims at preserving the four Cluster spacecraft data, so that they are usable in the long-term by the scientific community as well as by the instrument team PIs and Co-Is. This implies that the data are filed together with the descriptive and documentary elements making it possible to select and interpret them. The CIS (Cluster Ion Spectrometry) experiment is a comprehensive ionic plasma spectrometry package onboard the four Cluster spacecraft, capable of obtaining full three-dimensional ion distributions (about 0–40 keV/e) with a time resolution of one spacecraft spin (4 s) and with mass-per-charge composition determination. The CIS package consists of two different instruments, a Hot Ion Analyser (HIA) and a time-of-flight ion Composition Distribution Function (CODIF) analyser, plus a sophisticated dual-processor based instrument control and

I. Dandouras (), A. Barthe, E. Penou, S. Brunato, and H. Rème Université de Toulouse, Centre d’Etude Spatiale des Rayonnements, B.P. 44346, 31028 Toulouse, France and CNRS, UMR 5187, B.P. 44346, 31028 Toulouse, France e-mail: [email protected]; [email protected]; [email protected] A. Barthe AKKA Technologies, 6 Rue R. Camboulives, 31036 Toulouse, France e-mail: [email protected] S. Brunato Noveltis, 2 Avenue de l’Europe, 31520 Ramonville-Saint-Agne, France e-mail: [email protected] L.M. Kistler Space Science Center, University of New Hampshire, Durham, NH 03824, USA e-mail: [email protected] M.B. Bavassano-Cattaneo Istituto di Fisica dello Spazio Interplanetario, INAF, Via del Fosso del Cavaliere 100, 00133 Roma, Italy e-mail: [email protected] A. Blagau Institute of Space Sciences, P.O. Box MG-23, RO 77125 Bucharest-Magurele, Romania e-mail: [email protected]


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data processing system (DPS). For the archival of the CIS data a multi-level approach has been adopted. The CAA archival includes processed raw data (Level 1 data), moments of the ion distribution functions (Level 2 data), and calibrated highresolution data in a variety of physical units (Level 3 data). The latter are 3-D ion distribution functions. In addition, a software package has been developed to allow the CAA user to interactively calculate partial or total moments of the ion distributions. The CIS data archive includes also experiment documentation, graphical products for browsing through the data, and data caveats. Given the complexity of an ion spectrometer, and the variety of its operational modes, each one being optimised for a different magnetospheric region or measurement objective, consultation of the data caveats by the end user will always be a necessary step in the data analysis.

3.1 Introduction The Cluster Active Archive (CAA) aims at preserving the four Cluster spacecraft data, so that they are usable in the long-term by the world-wide scientific community as well as by the instrument team PIs and Co-Is. Its purpose is to maximise the scientific return from the mission, and to ensure that the unique data set returned by the Cluster mission is preserved in a stable, long-term archive for scientific analysis beyond the end of the mission. This implies that the instrument data, properly calibrated, are filed together with the descriptive and documentary elements making it possible to select and interpret them [8]. The CAA home page is at http://caa.estec.esa.int/.

3.2 The CIS Experiment The CIS (Cluster Ion Spectrometry) experiment is a comprehensive ionic plasma spectrometry package onboard the four Cluster spacecraft, capable of obtaining full three-dimensional ion distributions (about 0–40 keV/e) with a time resolution of one spacecraft spin (4 s) and with mass-per-charge composition determination [10]. The prime scientific objective of the CIS experiment is the study of the dynamics of magnetised plasma structures in and in the vicinity of the Earth’s magnetosphere, with the determination, as accurately as possible, of the local orientation and the state of motion of the plasma structures required for macrophysics and microphysics studies. The four Cluster spacecraft encounter ionic plasma of vastly diverse characteristics in the course of 1 year (Fig. 3.1). In order to study all the plasma regions with the fluxes shown in Fig. 3.1, the CIS experiment needs therefore to be a highly versatile and reliable ionic plasma experiment, capable of measuring both the cold and hot ions of Maxwellian and non-Maxwellian populations (for example, beams) from the solar wind, the magnetosheath, and the magnetosphere (including the upper ionosphere), with sufficient angular, energy and mass resolutions to accomplish the scientific objectives.

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Cluster Ion Spectrometry (CIS) Data in the Cluster Active Archive (CAA)

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IONS 1010 SW

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Fig. 3.1 Representative ion fluxes encountered along the Cluster orbit in the solar wind (SW), the magnetopause (MP), the magnetosheath (MSH), the plasma mantle (PM), the plasma sheet (PS), the lobe and upwelling ions (UPW). The range of the different sensitivities of CIS1/CODIF (low side, high side and RPA) and CIS2/HIA (low side and high side) are shown with different colours

To satisfy all these criteria, which cannot be met with a single instrument, the CIS package consists of two different instruments: A time-of-flight ion Composition and Distribution Function analyser (CODIF,

or CIS-1) A Hot Ion Analyser (HIA, or CIS-2)

In addition, each of the instruments, in order to be able to cover a dynamic range of about 6 orders of magnitude in particle fluxes, provides two different geometric factors: a high-sensitivity side (or HS) and a low-sensitivity side (or LS).

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The CIS experiment includes also a sophisticated dual-processor based instrument control and data processing system (DPS). The CIS home page is at http://cluster.cesr.fr:8000/.

3.2.1 The CODIF (CIS-1) Instrument The CODIF instrument is a high-sensitivity mass-resolving spectrometer with an instantaneous 360ı 8ı field of view to measure full 3-D distribution functions of the major ion species (in as much as they contribute significantly to the total mass density of the plasma), within one spin period of the spacecraft. Typically these include HC , HeC , HeCC and OC , with energies from 25 eV=e to 40 keV/e and with medium .22:5ı / angular resolution. The CODIF instrument combines ion energy per charge selection, by deflection in a rotationally symmetric toroidal electrostatic analyser, with a subsequent time-of-flight analysis after post-acceleration to 15 keV=e. Ions are selected as a function of their E=q (energy per charge) ratio, by sweeping the high voltage applied between the two toroidal hemispheres. The full energy sweep with 31 contiguous energy channels is performed 32 times per spin. In the time-of-flight (TOF) section the velocity of the incoming ions is measured, which allows then the calculation of their m=q (mass per charge) ratio. Microchannel plate (MCP) electron multipliers are used to detect both the ions and the secondary electrons, which are emitted from a carbon foil at the entry of the TOF section, during the passage of the ions. These secondary electrons give the “start” signal, for the time-of-flight measurement, and the position information (elevation angle of the incoming ion, provided by the MCP sectoring in anodes). In order to cover populations ranging from magnetosheath protons to tail lobe ions, a dynamic range of more than 105 is required. CODIF therefore consists of two sections, each with a 180ı field of view, with geometry factors differing by a factor of 100. This way, one of the sections will have counting rates which are statistically meaningful and which at the same time can be handled by the time-offlight electronics. However, intense ion fluxes can in some cases saturate the CODIF instrument (particularly if data are acquired from the high sensitivity side), but these fluxes are measured with HIA. The operation of the high-sensitivity side (“high-G”, or “HS”) and of the low-sensitivity side (“low-g”, or “LS”) on CODIF is mutually exclusive, and only one of the two sides can be selected at a time to supply data. The high-sensitivity side is divided into eight sectors (or anodes), 22:5ı each, and the low-sensitivity side into six 22:5ı sectors, i.e. there are two “blind” anodes. With an additional Retarding Potential Analyser (RPA) device in the aperture system of the CODIF sensor, and with pre-acceleration for the energies below 25 eV/e, the range is extended to energies as low as almost the spacecraft potential. The retarding potential analyser operates only in the RPA mode, and provides an energy range between about 0.7 and 25 eV/e (with respect to the spacecraft potential). The operation on CODIF of the RPA mode and of the normal magnetospheric modes (which provide a 25 eV/e to 40 keV/e energy range) is mutually exclusive.

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During the RPA operation, however, ion measurements above 25 eV/e are provided by the HIA instrument. For the RPA aperture system all anodes have the same geometric factor (on both sides), although the instrument electronics allow the operation of only one side at a time.

3.2.2 The HIA (CIS-2) Instrument The HIA instrument is an ion energy spectrometer, capable of obtaining full three-dimensional ion distributions with good angular and time resolution (one spacecraft spin). HIA combines the selection of incoming ions, according to the ion energy per charge by electrostatic deflection in a quadrispherical analyser, with a fast imaging particle detection system. This particle imaging is based on microchannel plate (MCP) electron multipliers and position encoding discrete anodes. As for CODIF, ions are selected as a function of their E=q (energy per charge) ratio, by sweeping the high voltage applied between the two hemispheres. In order to cover populations ranging from solar wind and magnetosheath ions to tail lobe ions, a dynamic range of more than 105 is required. HIA therefore consists of two 180ı field-of-view sections, with two different sensitivities (with a ratio 20), corresponding respectively to the high-sensitivity (“high-G”, or “HS”) and to the low-sensitivity (“low-g”, or “LS”) side. The “low g” side allows detection of the solar wind and the required high angular resolution is achieved through the use of 8 sectors (or MCP anodes), 5:625ı each, the remaining 8 sectors having 11:25ı resolution. The 180ı “high G” side is divided into 16 sectors, 11:25ı each. For each sensitivity side a full 4 steradian scan, consisting of 32 energy sweeps, is completed every spin of the spacecraft, i.e. every 4 s, giving a full three-dimensional distribution of ions in the energy range 5 eV=e–32 keV=e. Each sweep consists of 62 contiguous energy channels.

3.2.3 The CIS Operational Modes The CIS instruments have a large amount of flexibility, either in the selection of the operational mode or in the reduction of the data necessary to fit the available telemetry bandwidth. CIS can thus operate in any combination of the six Spacecraft Telemetry Modes (three Normal Telemetry Modes, NM1-NM3, and three Burst Telemetry Modes, BM1-BM3) and the 16 CIS Operational Modes. These 16 modes (Table 3.1) can be grouped into solar wind tracking modes, solar wind study modes with the priority on the upstreaming ions, magnetospheric modes, magnetosheath modes, an RPA mode and a calibration and test mode. These modes correspond to different energy sweeping schemes and different combinations of telemetry products transmitted. Onboard calculated moments are always transmitted to the telemetry with a high-time resolution (1 spin). A combination of 2-D and 3-D ion distribution functions, plus other telemetry products, are transmitted in parallel to onboard calculated

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I. Dandouras et al. Table 3.1 CIS operational modes CIS mode Mode name 0 SW-1 Solar wind/SW tracking – mode 1 1 SW-2 Solar wind/3D upstreaming ions – mode 2 2 SW-3 Solar wind/SW tracking – mode 3 3 SW-4 Solar wind/3D upstreaming ions – mode 4 4 SW-C1 Solar wind/SW tracking – data compression – mode 1 5 SW-C2 Solar wind/3D upstreaming ions – data compression-mode 2 6 RPA RPA mode 7 PROM PROM operation 8 MAG-1 Magnetosphere – mode 1 9 MAG-2 Magnetosphere – mode 2 10 MAG-3 Magnetosphere – mode 3 11 MAG-4 Magnetosphere/Magnetosheath – mode 1 12 MAG-5 Magnetosheath – mode 2 13 MAG-C1 Magnetosphere – data compression – mode 1 14 MAG-C2 Magnetosheath – data compression – mode 2 15 CAL Calibration/test mode

moments, with a mode-dependent and product-dependent time resolution. The table in Fig. 3.2 gives a typical example of CODIF telemetry products transmitted during the NM1 and the BM1 spacecraft telemetry modes, for the 16 CIS modes, and the corresponding time resolution for each product, in number of spins. The actual tables are supplied in the CIS calibration files (cf. Section 3.3.5). Mode change is performed by time-tagged commands, according to the plasma populations anticipated along the Cluster orbit. Although during the first 2 years of operations various CIS mode selection rules have been in use, since 2003 the most commonly used modes are mode 8 (MAG-1) and 13 (MAG-C1) in the magnetosphere, mode 12 (MAG-5) and 14 (MAG-C2) in the magnetosheath, and mode 3 (SW-4) and 5 (SW-C2) in the solar wind. Mode 10 (MAG-3) is also used in the magnetosphere for providing full resolution HIA data at the expense of CODIF data, as e.g. onboard sc1 since the end of 2004 (cf. Section 3.2.4). The RPA mode is operated about once per month, either on all spacecraft or on selected spacecraft. Magnetospheric modes stay relatively simple, i.e. the full energy-angle ranges are systematically covered. For HIA the different telemetry products (including moments) are deduced from the 62E 128 energy solid angle count rate matrices accumulated on the “high G” section. For CODIF they are deduced from the sensitivity side selected by command. Solar wind tracking modes allow a precise and fast measurement (4 s) of the ion flow parameters (HC , HeCC ). For that, in the solar wind, for HIA the energy sweep range is automatically reduced when the field-of-view of the “low g” section is facing the 45ı sector centred in the solar wind direction. This energy sweep range is adapted every spin (Modes 0, 2, 4), centred on the main solar wind velocity by using a criterion based on the HC thermal and bulk velocities computed during the previous spin (solar wind beam tracking). This allows a higher energy resolution for the solar wind beam data.


Fig. 3.2 CODIF Telemetry Products transmitted in various modes and corresponding time resolution, in number of spins

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Fig. 3.3 Schematic of the CIS-2 (HIA) energy-sweep scheme, as a function of the instrument field-of-view orientation in the spin plane: solar wind modes (modes 0–5). Note that, at any given spin phase, the high-sensitivity side field-of-view is looking at the diametrically opposite direction with respect to the low-sensitivity side field-of-view, indicated in the schematic

During solar wind modes with the priority on the upstreaming ions (Modes 1, 3, 5) solar wind beam tracking is performed by HIA only once every 16 spins (exact value can vary depending on mode number). During the remaining 15/16 spins a broader energy sweep is used for the solar wind detection by the “low g” section, allowing at the same time the detection of upstreaming ions by the “high G” section, which is then looking in the anti-sunward direction. Detailed 3-D distributions for the solar wind (“low g” section) are then transmitted to the telemetry only during solar wind beam tracking (once every 16 spins), but onboard calculated solar-wind moments are transmitted every spin. Moreover, detailed 3-D distributions from the “high G” section (e.g. for upstreaming ions and/or for interplanetary disturbances) are included in the basic products transmitted to the telemetry. Outside this 45ı sector, the full energy sweep range is used (solar wind modes and solar wind modes with the priority on the upstreaming ions). However, when the field-of-view of the “high G” section is facing the 45ı sector centred in the solar wind direction (Fig. 3.3), the energy sweep stops (and “freezes”) above the solar wind alpha particles energy, to avoid a quick degradation of the MCPs by the intense solar wind beam (modes 0–5). For CODIF, the reduced energy-sweep principle is also used during modes 0–5, when the field-of-view of the “high G” section is facing the 45ı sector centred in the solar wind direction. Complete energy sweeping is used in the remaining part of the spin (Fig. 3.4). Magnetosheath modes are like magnetospheric modes. However, starting from 1 November 2003, the energy sweep scheme has been redefined for CODIF. With the new CODIF Magnetosheath Modes (modes 12 and 14), the energy sweeps are

Cluster Ion Spectrometry (CIS) Data in the Cluster Active Archive (CAA) log E

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Fig. 3.4 Schematic of the CIS-1 (CODIF) energy-sweep scheme, for solar wind modes, as a function of the spin phase: high-sensitivity side field-of-view orientation (upper panel), and lowsensitivity side field-of-view orientation (bottom panel). The energy “freeze”, during the reduced energy sweeps, is at about 2 keV

truncated and “frozen” at about 2 keV for 16 out of 32 sweeps (when the highsensitivity side faces the magnetosheath mainstream flow), to save the MCP lifetime.

3.2.4 CIS Instrument Status The overall experiment performance, after about 8 years of operation in space, is good. The particle detection efficiency degradation, due to the MCP gain fatigue mechanism [9], is moderate for the HIA instrument. Actual efficiencies (first half 2008) are reduced to about 77% of the initial HIA detection efficiencies on Cluster sc1 (spacecraft 1), and are almost the same as the initial ones for HIA on sc3. However, the physical degradation of the MCPs is in reality higher, but it is in some extent compensated by applying increased high voltages on the MCP plates, to restore secondary electron gain in the MCP channels despite the physical degradation of their emissive surfaces. For CODIF the efficiency degradation is more pronounced, due to the operational principle of this instrument, requiring the detection of both the ion (“stop” timeof-flight signal) and of the electrons emitted by the carbon foil (“start” time-offlight signal), plus a “position” signal, to validate the detection of an ion. Actual efficiencies for CODIF are now reduced, on the average, to less than about 10% of the initial detection efficiencies on Cluster sc4, and to less than about 5% on sc3

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I. Dandouras et al. Table 3.2 CIS instrument status SC 1 SC 2 CODIF Operations until Not operational October 2004 HIA

Normal operations

SC 3 One deficient MCP quadrant (cf. Section 3.3.8) Normal operations

SC 4 Normal operations

Switched OFF

(cf. Section 3.3.5). In spite of these values, the CODIF performance and ability to still collect data of quality adequate for addressing most of its scientific objectives is remarkable. When processing the raw instrument data to convert them into higher-level data in physical units, these efficiency degradations are compensated by the calibration values used, supplied in the calibration files (cf. Section 3.3.5). However, these calibrations cannot correct for the degraded signal-to-noise ratio induced by the reduced particle counting statistics, particularly when measurements are performed in lowdensity plasmas. The CODIF instrument onboard Cluster sc1 is switched off since 25 October 2004, due to an MCP high voltage anomaly. Onboard Cluster sc3, the CODIF instrument presents one deficient MCP quadrant (southward looking directions on the high-sensitivity side, cf. Section 3.3.8). The HIA instrument is switched off on Cluster sc4, but could be switched on if necessary. On this spacecraft, due to an electrostatic analyser high voltage issue, the HIA energy sweep range is limited between 5 and 400 eV=e. The CIS experiment is not operational on Cluster sc2. Table 3.2 summarises the CIS instrument status, at the time of this writing (2008).

3.3 CIS-CAA Archival Products For the archival of the CIS data a multi-level approach has been adopted [2, 4]. The CAA archival includes processed raw data (Level 1 data), moments of the distribution functions (Level 2 data), and calibrated high-resolution data in a variety of physical units (Level 3 data). Furthermore, the calibration files and high-level processing software are also archived. This approach provides “ready to use” high-resolution data products, archived in ASCII (CEF-2 format), which are expected to have a long lifetime. However, should a user wish to re-analyse the raw data and the instrument calibrations, he will also be able to do it. The CIS data archive includes also experiment documentation, graphical products for browsing through the data, and data caveats. In order to help the user, a CIS Data Selection Guide has been also provided as appendix in the CIS-CAA ICD and in the User Guide to the CIS Measurements in the CAA.

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3.3.1 CIS Level 1 Data CIS Level 1 data are decommutated, decompressed, and time-tagged telemetry data. They are in raw instrument units (no corrections for MCP efficiencies etc.), represent the complete CIS Telemetry, and are the input for all higher-level processing. CIS Level 1 data, together with the CIS calibration files, are in particular the input files for the “cl” software (cf. Section 3.3.6). These data are organised in one file per telemetry product – spacecraft – day, and each file is a time-series of equal-length records. Each data record is complete: time tag, product type, mode info, etc. Data are in IEEE integers or floats.

3.3.2 CIS Level 2 Data CIS Level 2 data are moments of the particle distribution functions: ion density, velocity (in the GSE reference frame), temperature (parallel and perpendicular components, obtained by diagonalising the pressure tensor). For CODIF, which has a higher upper energy limit than HIA, the pressure is also supplied in addition. They correspond to the Prime Parameters from the Cluster Science Data System [1]: onboard calculated moments, then reprocessed on ground (total efficiency calibration adjustments, coordinate transformations etc.). Onboard calculated moments provide 1-spin time resolution, and are calculated from the full angular and energy resolution 3-D ion distributions. In addition to the onboard calculated moments, CIS Level 2 data include also CODIF moments calculated on the ground from the 3-D ion distributions. These provide better calibration adjustments (per anode efficiency) and are thus more accurate, but have a reduced time and energy resolution. HIA on the ground calculated moments are not supplied, because the same anode calibrations would be used as for the onboard calculated ones, but with a degraded time, energy and angular resolution (no added value). A software package has also been developed and is available for download at the CAA web site, allowing the user to interactively calculate partial (or total) moments of the ion distributions, for selected energy and solid angle ranges: CODIF (all 4 ion species) and HIA data (cf. Section 3.3.6). Onboard calculated moments and on the ground calculated moments from the 3-D ion distributions are thus complementary. A data selection guide, to help the CAA user select the most appropriate dataset, is given in Appendix 1 of the CAACIS Interface Control Document [2] and in the User Guide to the CIS Measurements in the CAA. The way moments are calculated from the 3-D ion distribution functions is described in Appendix 2 of the CAA-CIS Interface Control Document.

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3.3.3 CIS Level 3 Data CIS Level 3 data are processed high-resolution data: 3-D ion distributions. They are produced by correcting the Level 1 data for detector efficiencies, geometric factors and other information available from the calibration tables, and give measurements in several physical units (in separate files):

(Differential) Particle flux (Differential) Particle energy flux Particle phase space density Corrected-for-efficiency particle count rate Raw particle counts

ions cm2 s1 sr1 keV1 keV cm2 s1 sr1 keV1 ions s3 km6 ions s1 Number of ions per counter bin

These Level 3 archival files are constructed by joining files from similar telemetry data products (same ion species, different angular, energy or time resolution). Figure 3.5 shows how these files are organised as a function of:

The instrument (HIA or CODIF) The operational mode (magnetospheric, solar wind, or RPA) The instrument sensitivity side (HS or LS) The ion species (for CODIF only)

The 3-D distributions are in the ISR2 pseudo-GSE reference frame (X sunward, Z is the spacecraft axis and northward pointing). They give the complete 16 azimuth 8 elevation D 128 solid angles matrix, and remove the reduction to a total of 88 solid angles in the telemetry products, where adjacent solid angles near the polar directions have been binned together (for some CIS telemetry products). This is achieved by sub-diving each of these binned-together solid angles into the original 2 or 4 solid angles, and distributing the corresponding particle counts in an equal way. Solid angles, defined in the distributions, correspond to particle arrival directions (direction of travel of the particle). HS CODIF

LS

3 types x 4 ion species x 5 physical units = 60 datasets

RPA CIS HS_MAG HIA

HS_SW

3 types x 5 physical units = 15 datasets

LS_SW

Fig. 3.5 CIS level 3 data archival scheme for the 3-D ion distributions

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In addition to the 3-D distributions, pitch-angle distributions (PADs) are also provided. These are calculated on the ground from the 3-D distributions and the magnetic field direction (spacecraft reference frame), are given in particle flux units as a function of the particle energy and pitch-angle (2-D distributions), and their resolution is in 16 equal angular sectors covering the pitch angle range from 0ı to 180ı . Besides these 2-D and 3-D distributions, some uncalibrated CODIF data sets are also included in the CIS Level 3 data: files with onboard selected ion detection events, MCP monitor rates, and low-angular resolution distributions in 64 m=q ranges. These data sets are useful for monitoring instrument performance against eventual background and ion mass species separation, or for searching for minority ion species. Level 3 archival files are labelled with metadata, i.e. information that describes the dataset and its contents, so as to be easily understandable by the CAA user. These metadata follow the specifications given in the Cluster Metadata Dictionary [6], which has been produced for the CAA project by the CAA Metadata Working Group and the CDPP, the French Plasma Physics Data Centre (http://cdpp.cesr.fr/).

3.3.4 CIS Graphical Data Products The CIS graphical data archived are 6-h energy-time ion spectrograms. They are preformatted displays: PNG graphic files embedded in HTML pages, and they are given at two levels of resolution: browsing and detailed. These spectrograms are supplied separately for each spacecraft. Figure 3.6 shows an example of a CIS energy-time spectrogram. It includes, from top to bottom, HIA data from the low-sensitivity side (ions in the 45ı 45ı sector centred in the solar wind direction), HIA data from the high-sensitivity side (separately for four azimuthal sectors: ions arriving in the 90ı 180ı sector with a field-of-view pointing in the sun, dusk, tail, and dawn direction respectively), omnidirectional CODIF data for HC , HeC and OC ions respectively, ion velocity components measured by HIA, and ion densities measured by HIA and by CODIF. Instrument operational mode and spacecraft telemetry mode data are also included, as well as spacecraft coordinates. As can be seen in the HIA mode panel, at the top, the instrument was initially in a solar wind – upstreaming ions mode (mode 3). The solar wind narrow-energy beam is clearly identified in the low-sensitivity side HIA spectrogram, while at the same time the high-sensitivity side HIA spectrogram for ions arriving from the sunward looking direction does not detect the solar wind beam. This is due to the energy-sweep scheme adopted during these modes, that stops (and “freezes”) above the solar wind alpha particles energy, as explained in Section 3.2.3. Some high-energy upstreaming ions are however visible at that time, in the high-sensitivity side HIA spectrograms, as well as in the CODIF HC spectrogram, which was then operating at the high-sensitivity side. Note that CODIF also does not detect the solar wind beam, for the same reason: the energy-sweep scheme adopted during these modes (cf. Fig. 3.4), but solar wind beam data are supplied by

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Fig. 3.6 CIS energy-time ion spectrogram. See text for details

13/Feb/2001

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16 HIA Mode 8 0 10000 1000 100 10000 1000 100 10 10000 1000 100 10 10000 1000 100 10 10000 1000 100 10 16 CODIF Mode 8 0 High CODIF G Low 10000 1000 100 10 10000 1000 100 10 10000 1000 100 10 400 200 0 –200 –400 –600 100.00 10.00 1.00 0.10 0.01 100.0000 10.0000 1.0000 0.1000 0.0100 0.0010 0.0001 12:00 13:00 14:00 15:00 16:00 14.09 12.38 11.39 13.28 14.83 XGSE 1.42 0.62 0.21 1.02 1.81 YGSE –5.72 –6.78 –5.30 –6.12 –6.47 ZGSE 15.28 13.25 15.85 14.66 13.98 DIST Produced by CESR, Printing date: 16/Oct/2007

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VzH1_HIA_GSM NH1_HIA NHe2_HIA NH1_CODIF N01_CODIF NHe1_CODIF NHe2_CODIF 17:00 18:00 9.10 10.30 –0.59 –0.19 –7.02 –7.20 12.47 11.62 vue_web_new.cl

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HIA. At 12:40 UT the instrument, while in the solar wind, was switched into mode 12 (magnetosheath mode). Both instruments switched then to an omnidirectional full energy sweep scheme (cf. Section 3.2.3), and the low-sensitivity side of HIA ceased collecting data. The solar wind beam became then detectable in the sunward looking direction spectrogram from the HIA high-sensitivity side (but with a lower energy resolution), and in the CODIF data, collected then from the high-sensitivity instrument side, but with a strong saturation in the solar wind beam energies. Note, however, the ability of the CODIF high-sensitivity side to detect the relatively weak fluxes of the upstreaming ion populations. The energy flux of these upstreaming ions is a factor of 2;000 lower than the energy flux of the solar wind beam ions, as this beam population is measured by the low-sensitivity side of HIA. At 14:40 UT the spacecraft entered in the magnetosheath, as revealed by the broader energy distribution of the detected ions (bow shock heating) and by the anisotropic flow shown in the four directional HIA spectrograms. These energy-time ion spectrograms are also available through the CIS home page: http://cluster.cesr.fr:8000/.

3.3.5 CIS Calibration Files CIS calibration files are ASCII files, self-documented (including comments), machine-readable and human-readable. They include parameters such as: Geometric factors MCP ion detection efficiencies: for each of the four main ions species, separately

for each anode, and including the polynomial coefficients for the efficiency energy dependence An overall instrument efficiency (called also absolute efficiency), for each of the four main ions species and separately for each instrument sensitivity side CODIF post-acceleration high voltage values Energy sweep tables for the various modes During how many spacecraft spins each 3-D ion distribution is accumulated, for the various modes

The way these calibration factors are used to convert instrument raw particle counts to higher-level data in physical units, such as particle flux or particle energy flux, and then to calculate the moments of the ion distribution functions, is described in Appendix 2 of the CAA-CIS Interface Control Document [2]. Both CODIF and HIA have been very well calibrated before launch, in vacuum test facilities [10]. However, due to the in-flight evolution of the MCP detection efficiencies as a function of time, the CIS calibration files are updated regularly. A calibrations catalogue file, which is provided with the calibration files, serves as a pointer to which calibration files to use for each data time period. This catalogue file evolves in an incremental way through the mission, to take into account the existence of new calibration files, which correspond to the instrument particle detection efficiency evolution, or other changes in the instrument.

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Fig. 3.7 CODIF high-sensitivity side absolute efficiency evolution for Cluster spacecraft 4, normalised to the efficiency at the start of the mission

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Calibration files include thus parameters that have been determined during ground calibrations in vacuum test facilities and are stable through the mission (e.g. instrument angle response, electrostatic analyser constant used in the calculation of the energy sweep tables, etc.), parameters that change gradually through the mission (e.g. particle detection efficiencies), and parameters that can be changed during the mission by command (e.g. upload of new spin accumulation tables for 3-D ion distributions in the various modes). All of them are equally important in converting raw data into physical units, and are used together. Figure 3.7 shows an example for the evolution, as a function of time, of the CODIF high-sensitivity side absolute efficiency for Cluster spacecraft 4, normalised to the efficiency at the start of the mission. Some sharp efficiency increases that are observed are due to an increased high voltage applied to the MCP, in order to compensate, as much as possible, for the efficiency decrease due to the well-known gain fatigue mechanism (cf. Section 3.2.4). However, as can be seen, the effects of such a high-voltage boost on the efficiency of the instrument are limited in time. Updating the calibration files for the detection efficiency evolution, with respect to the pre-launch calibrations, is a multi-step process, and is performed about once per year. The HIA ion density values are compared and cross-calibrated with the electron density values supplied by the Whisper sounder experiment [5]. This is performed in the magnetosheath for the high-sensitivity side and in the solar wind for the low-sensitivity side, i.e. in the plasma environment where each of the two sides has the optimum performance, and where the plasma energy spectrum is within the energy domain covered by the instrument. It should be noted also that the HIA anodes relative efficiencies are remarkably stable, i.e. the efficiency drift is very homogeneous between the anodes (11:25ı or 5:625ı sectors).

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The CODIF calibrations updating is a more complex process. It involves the determination of the start-MCP efficiency, the stop-MCP efficiency, the fraction of coincidences between the “start” time-of-flight signal and the “stop” time-of-flight signal that also have a “single position” signal, allowing thus to calculate the total efficiency. In addition, the efficiencies of the individual anodes (22:5ı sectors) have to be cross-calibrated, since they slowly drift relative to each other, and this is performed by using time periods when the ion distributions are expected to be gyrotropic. CODIF calibrations involve also separate efficiencies determination for HC and OC ions. The resulting CODIF HC measurements are finally cross-checked with the HIA measurements, for periods when the plasma is composed mainly from HC ions. CODIF data are also cross-checked with the high-energy ion data supplied by the RAPID experiment [12], for periods where energetic plasma is present in the energy range of both instruments.

3.3.6 CIS Data Processing Software The CIS data processing software to be archived is composed of two packages: The CIS 3D MOM software, specially developed for the CAA, allows the user

to read the CIS Level 3 files, available at the CAA, and interactively calculate partial or total moments of the ion distributions, for selected energy and solid angle ranges. The input is 3-D ion distribution functions, in CEF-2 format and in corrected-for-efficiency particle count rate units, and the output is ion density, bulk velocity, pressure tensor and temperature, also in CEF-2 format and in the ISR2 pseudo-GSE reference frame. It is written in C and it can be used for either CODIF or HIA data. The cl software, written in IDL, and developed initially for the CIS team. It reads Level 1 CIS data and calibration files; is interactive, and can generate a large variety of high-resolution graphics (spectrograms, distribution functions, PADs . . . ) in several physical units. It can also export the results as ASCII (CEF) data files. In addition to the CIS data, this software can also read generic CDF and CEF data files, for correlation studies. These software packages are available “as documents”, for installation and execution on the end user’s machine.

3.3.7 CIS Documentation The CIS documentation for the CAA includes: The CIS-CAA Interface Control Document (ICD), including the appendices

“CIS Data Selection Guide” and “CIS: Particle Counts to Flux and to Moments of the Ion Distribution Function” [2]

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A description of the instrument [10] The User Guide to the CIS Measurements in the CAA Calibration documentation The present paper

3.3.8 CIS Data Caveats CIS caveat files include both general caveats for the CIS data, and caveats for specific data intervals. Given the complexity of an ion spectrometer, and the variety of its operational modes, each one being optimised for a different plasma region or measurement objective, consultation of the data caveats by the end user will always be a necessary step in the data analysis (independently of the data level). The CIS caveats are also available at the CIS home page, at http://cluster.cesr.fr: 8000/index.php?page=caveats&langue=en. Following are some of the most important caveats, which the user of the CIS data should be aware of. The calculated density values are in reality ion partial density values in the energy

domain covered by the instrument, typically 25 eV/e to 40 keV/e for CODIF and 5 eV/e to 32 keV/e for HIA. In the presence of cold plasma at energies below the instrument energy threshold, or of hot plasma at energies above the instrument upper energy limit, this partial density is evidently lower than the total plasma density. In the presence of hot plasma at energies above the instrument upper energy limit the result is also underestimated ion bulk velocity, temperature and pressure values. The instrument energy domain is always defined with respect to the spacecraft potential. Spacecraft charging to a positive floating potential, as can be the case in low density plasmas when the ASPOC ion emitter for spacecraft potential control is not operating [11], repels the low-energy ions which in these cases cannot be detected by CIS (cf. for example Section 6.10 of Rème et al. [10], and Section 3.4 of Dandouras et al. [3]). This effect results in a further increase of the difference between the partial density, measured by CIS, and the total plasma density. In addition to the finite energy range, the accuracy of the computed moments is also affected by the finite energy and angular resolution of the two instruments. This is in particular the case for narrow-energy distributions (cold plasmas or cold beams), and/or narrow solid angle beams. CODIF is more sensitive to this effect, due to its coarser energy and angular resolution. Adequate counting statistics are essential for reliable results. For density calculations, in the case of isotropic plasma distributions, HIA “hits” a lower limit density value of the order of 0:01–0:02 cm3 . CODIF continues to supply density values down to about 0:001–0:002 cm3 , although with very poor counting statistics in these cases, which do not allow a reliable calculation of the higherorder moments.

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Ion measurements are sensitive to possible detector saturation in the presence

of high ion fluxes (instrument dead time effects). The most striking example is the strongly underestimated solar wind density and magnetosheath density by the CODIF high-sensitivity side, while the instrument is operating in a magnetospheric mode. However, these saturation effects are phase space dependent: the detector can be saturated only in a limited energy range and for particles arriving in a given solid angle, where the highest counting rates occur (e.g. solar wind beam), but at the same time can supply reliable measurements in the remaining phase space, as are for example the upstreaming ion populations discussed in Section 3.3.4 (CODIF data spectrogram). Note that HIA data acquired in a magnetospheric mode can also suffer from partial detector saturation when in the solar wind: slightly underestimated densities, by a factor depending on the solar wind density and temperature [7]. Eventual instrument background counts due to penetrating particles, from the radiation belts around perigee passes or during SEP (Solar Energetic Particles) events, can result in an overestimation of the measured fluxes, and the resulting density values. This effect is stronger for HIA, whereas for CODIF it is mitigated by the time-of-flight technique, which requires both a “start” signal and a “stop” signal, in the correct time-of-flight window, to validate the detection of an ion. The entire velocity phase space, corresponding to the instrument energy domain, is not covered during all modes (cf. for example the spectrogram discussed in Section 3.3.4). This is the case during solar wind modes, and during some magnetosheath modes (CODIF data acquired after 1 November 2003 during modes 12 and 14). The result is: ı Incorrect HIA moment values in the magnetosheath when the instrument is in a solar wind mode (modes 0–5) ı Incorrect CODIF moment values when data come from the high-sensitivity side and the instrument is in a solar wind mode (modes 0–5) ı Incorrect CODIF moment values when data come from the high-sensitivity side and the instrument is in mode 12 or 14, for data acquired after 1 November 2003 CIS mode information is supplied in the spectrograms (cf. Section 3.3.4) and in the Level 3 data (cis mode variable). CODIF data in the solar wind, if acquired from the low-sensitivity side but with

the instrument operating in a magnetospheric mode, can suffer from cross-talk with the high counting rates of the high-sensitivity side, which is then saturated by the solar wind. The result is then overestimated densities and underestimated velocities. The Vz term of the ion bulk velocity is very sensitive to the anode crosscalibrations, and in particular to those of the anodes looking in directions away from the spacecraft spin plane (polar anodes). In some cases the efficiency calibration coefficients cannot completely compensate for strongly asymmetrically decreased efficiencies of such polar anodes, which results in a residual offset of Vz . This is in particular the case of CODIF onboard Cluster sc3, where one

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MCP quadrant (southward looking directions on the high-sensitivity side) suffers from a strongly decreased particle detection efficiency. This asymmetric efficiency degradation amplified with time, and for data acquired after 23 February 2003 it cannot anymore be corrected. As a result the Vz velocity component is highly unreliable (strong offset), and the density suffers from the fact that the instrument under-detects the ions in one hemisphere of the phase space. CODIF mass-separated data can suffer from spillover between neighboring mass channels. HeCC data, in particular, are usually contaminated by HC ions, resulting in over-estimated HeCC densities. CODIF OC data can be contaminated by penetrating particles in the radiation belts. They can also be slightly contaminated by HC ions in very high HC flux plasmas, as for example in the magnetosheath. The latter is due to occasionally two uncorrelated HC ions, one generating only a “start” time-of-flight signal and the other generating only a “stop” time-of-flight signal, and the time difference between the two being that of an OC ion. Presence of ions other than HC in the HIA data results in underestimated densities and in overestimated temperatures and pressures. During short eclipses the absence of a Sun reference pulse completely desynchronises the HIA data, which become useless, whereas the CODIF data are acquired using an extrapolated Sun reference pulse, and are thus still usable. During long eclipses CIS is off. Determinations of the evolution of the MCPs detection efficiency are statistical (based on the analysis of a number of data intervals). Detector ageing is accompanied by a degradation of the signal-to-noise ratio. Operation incidents can occasionally result, for short periods, in missing data products, in incorrect MCP high voltage and/or discriminator settings, which reduce the accuracy of the collected data, etc. These are flagged in the caveats for specific data intervals.

3.4 Conclusion The CIS experiment, due to its unique features, is a versatile instrument package, capable of obtaining full three-dimensional ion distributions with a time resolution of one spacecraft spin and with mass-per-charge composition determination. The quality of the data supplied by CIS has resulted, until now, in the publication of more than 300 scientific papers in refereed journals, based on the analysis of these data. These papers, and the results they present, constitute the ultimate validation of the data supplied by the two complementary instruments composing the CIS experiment, CODIF and HIA. The Cluster Active Archive will preserve these data in the long-term, so that they are usable by the scientific community. For the CIS data archived there a multilevel approach has been adopted, including both processed raw data and calibrated

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high-resolution data in a variety of physical units. The CIS data archive includes also experiment documentation, graphical products for browsing through the data, and data caveats. Given the complexity of an ion spectrometer, and the variety of its operational modes, each one being optimised for a different plasma region or measurement objective, the user has to be careful in selecting for his analysis the appropriate data set and instrument mode. In order to help the user in this task, a User Guide to the CIS Measurements in the CAA has been provided. Consultation of the data caveats by the user will also always be a necessary step in the data analysis. Acknowledgements The CIS Team is grateful to ESA, for the support supplied in operating the instrument and in preparing the CIS data for the CAA. CIS archival activities at CESR are jointly funded by ESA, by CNES and by CNRS. Activities in the USA are funded by NASA.

References 1. Daly, P.W. et al.: Users Guide to the Cluster Science Data System. DS–MPA–TN–0015 (2002) 2. Dandouras, I., A. Barthe: Cluster Active Archive: Interface Control Document for CIS. CAACIS-ICD-0001 (2007). http://caa.estec.esa.int/caa/instr doc.xml 3. Dandouras, I., V. Pierrard, J. Goldstein, C. Vallat, G. K. Parks, H. Rème, C. Gouillart, F. Sevestre, M. McCarthy, L. M. Kistler, B. Klecker, A. Korth, M. B. Bavassano-Cattaneo, P. Escoubet, A. Masson: Multipoint observations of ionic structures in the Plasmasphere by CLUSTER-CIS and comparisons with IMAGE-EUV observations and with Model Simulations. In: AGU Monograph: Inner Magnetosphere Interactions: New Perspectives from Imaging, 159, 23–53, 10.1029/159GM03 (2005) 4. Dandouras, I., A. Barthe, E. Penou, H. Rème, S. McCaffrey, C. Vallat, L.M. Kistler, and the CIS Team: Archival of the Cluster Ion Spectrometry (CIS) Data in the Cluster Active Archive (CAA). In: Proceeding of the Cluster and Double Star Symposium-5th Anniversary of Cluster in Space, ESA SP-598, Noordwjik (2006) 5. Décréau, P.M.E., P. Fergeau, V. Krasnoselskikh, E. Le Guirriec, M. Lévêque, Ph. Martin, O. Randriamboarison, J.L. Rauch, F.X. Sené, H.C. Séran, J.G. Trotignon, P. Canu, N. Cornilleau, H. de Féraudy, H. Alleyne, K. Yearby, P.B. Mögensen, G. Gustafsson, M. André, D.C. Gurnett, F. Darrouzet, J. Lemaire, C.C. Harvey, P. Travnicek: Early results from the Whisper instrument on Cluster: an overview. Ann. Geophys., 19, 1241 (2001) 6. Harvey, C.C., A.J. Allen, F. Dériot, C. Huc, M. Nonon-Latapie, C.H. Perry, S.J. Schwartz, T. Eriksson, S. McCaffrey: Cluster Metadata Dictionary. CAA-CDPP-TN-0002 (2008) 7. Martz, C., J.A. Sauvaud, H. Rème : Accuracy of ion distribution measurements and related parameters using the Cluster CIS experiment. In: Spatio-Temporal Analysis for Resolving Plasma Turbulence (START), ESA WPP-047, 229 (1993) 8. Perry, C., T. Eriksson, P. Escoubet, S. Esson, H. Laakso, S. McCaffrey, T. Sanderson, H. Bowen, A. Allen, C. Harvey: The ESA Cluster Active Archive. In: Proceeding of the Cluster and Double Star Symposium-5th Anniversary of Cluster in Space, ESA SP-598, Noordwjik (2006) 9. Prince, R.H., J.A. Cross: Gain Fatigue Mechanism in Channel Electron Multipliers. Rev. Sci. Instrum., 42, 66; DOI:10.1063/1.1684879 (1971) 10. Rème, H., C. Aoustin, J.M. Bosqued, I. Dandouras, B. Lavraud, J.A. Sauvaud, A. Barthe, J. Bouyssou, Th. Camus, O. Coeur-Joly, A. Cros, J. Cuvilo, F. Ducay, Y. Garbarowitz, J.L. Medale, E. Penou, H. Perrier, D. Romefort, J. Rouzaud, C. Vallat, D. Alcaydé, C. Jacquey, C. Mazelle, C. dâUston, E. Möbius, L.M. Kistler, K. Crocker, M. Granoff, C. Mouikis,

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M. Popecki, M. Vosbury, B. Klecker, D. Hovestadt, H. Kucharek, E. Kuenneth, G. Paschmann, M. Scholer, N. Sckopke, E. Seidenschwang, C.W. Carlson, D.W. Curtis, C. Ingraham, R.P. Lin, J.P. McFadden, G.K. Parks, T. Phan, V. Formisano, E. Amata, M.B. Bavassano-Cattaneo, P. Baldetti, R. Bruno, G. Chionchio, A. Di Lellis, M.F. Marcucci, G. Pallocchia, A. Korth, P.W. Daly, B. Graeve, H. Rosenbauer, V. Vasyliunas, M. McCarthy, M. Wilber, L. Eliasson, R. Lundin, S. Olsen, E.G. Shelley, S. Fuselier, A.G. Ghielmetti, W. Lennartsson, C.P. Escoubet, H. Balsiger, R. Friedel, J-B. Cao, R. A. Kovrazhkin, I. Papamastorakis, R. Pellat, J. Scudder, B. Sonnerup: First multispacecraft ion measurements in and near the Earth’s magnetosphere with the identical Cluster ion spectrometry (CIS) experiment. Ann. Geophys., 19, 1303 (2001) 11. Torkar, K., W. Riedler, C.P. Escoubet, M. Fehringer, R. Schmidt, R.J.L. Grard, H. Arends, F. Rüdenauer, W. Steiger, B.T. Narheim, K. Svenes, R. Torbert, M. André, A. Fazakerley, R. Goldstein, R.C. Olsen, A. Pedersen, E. Whipple, H. Zhao: Active spacecraft potential control for Cluster implementation and first results. Ann. Geophys., 19, 1289 (2001) 12. Wilken, B., P.W. Daly, U. Mall, K. Aarsnes, D.N. Baker, R.D. Belian, J.B. Blake, H. Borg, J. Büchner, M. Carter, J.F. Fennell, R. Friedel, T.A. Fritz, F. Gliem, M. Grande, K. Kecskemety, G. Kettmann, A. Korth, S. Livi, S. McKenna-Lawlor, K. Mursula, B. Nikutowski, C.H. Perry, Z.Y. Pu, J. Roeder, G.D. Reeves, E.T. Sarris, I. Sandahl, F. Søraas, J. Woch, Q.-G. Zong: First results from the RAPID imaging energetic particle spectrometer on board Cluster. Ann. Geophys., 19, 1355 (2001)

Chapter 4

Digital Wave Processor Products in the Cluster Active Archive K.H. Yearby, H.St.C. Alleyne, S.N. Walker, I. Bates, M.P. Gough, A. Buckley, and T.D. Carozzi

Abstract The Digital Wave Processor (DWP) is the central control and data processing instrument for the Cluster Wave Experiment Consortium. DWP products in the Cluster Active Archive (CAA) provide a mainly supporting function for the rest of the consortium. This includes a time correction dataset which allows the standard timing accuracy of 2 ms to be improved to around 20 s, and experiment command and status datasets which show what commands have been sent to the experiments, and the resulting status. DWP also contains a particle correlator experiment that computes the auto-correlation of electron counts received by the PEACE electron experiment via an inter-experiment link.

4.1 Introduction The DWP instrument is the central control and data processing unit for the Wave Experiment Consortium (WEC) which comprises the EFW, STAFF, WHISPER and WIDEBAND instruments. Pedersen et al. [8] give an overview of the WEC, while Woolliscroft et al. [9] describe the DWP instrument. A block diagram of the consortium is shown in Fig. 4.1). For nominal operations, all commanding and telemetry acquisition for these instruments is routed via DWP, except for WIDEBAND telemetry to NASA’s Deep Space Network (DSN) and the Czech Republic’s Panska Ves station. Time synchronisation of WEC modes is controlled by DWP, and the WEC science telemetry is dynamically allocated between the WEC instruments according to the requirements of each WEC mode. Housekeeping data for all WEC instruments is acquired by DWP. In addition DWP contains a particle correlator experiment which computes K.H. Yearby (), H.St.C. Alleyne, S.N. Walker, and I. Bates Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK e-mail: [email protected]; [email protected]; [email protected] M.P. Gough, A. Buckley, and T.D. Carozzi Space Science Group, University of Sussex, Falmer, Brighton, BN1 9QH, UK e-mail: [email protected]; [email protected]; [email protected]


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STAFF Wave Analyser

Inter-experimental links to other instruments of the Cluster scientific payload Spacecraft telecommand interface

STAFF Spectrum Analyser

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DWP

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WEC Power supply

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Fig. 4.1 Block diagram of the WEC showing DWP in the centre of the consortium

the auto-correlation of electron counts received by the PEACE experiment [7]. The correlator was designed to detect modulations and short time particle bursts in the electron population as an indicator of wave-particle interactions. The DWP products in the CAA consist of the following datasets: Time correction data (C1 CP DWP TCOR). Enable the standard 2 ms timing ac-

curacy to be improved to 20 s Summary of the status of the Wave Experiment Consortium (C1 CP DWP

LOG). One record for each interval that the WEC operates in the same mode. A total of 64 parameters including: instrument modes, telemetry use statistics, errors and anomalies, summary of voltage and temperature housekeeping A listing of the command sequences uplinked to the Wave Experiment Consortium (CM CD DWP UT PIOR) High resolution particle correlator data (C1 CP DWP COR FX and C1 CP DWP COR ST) Documentation and software Their production and interpretation is outlined in the following sections.

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4.2 Time Correction Data 4.2.1 Introduction The STAFF and EFW experiments include magnetic and electric field wave data at frequencies up to 180 Hz in burst mode [2, 6]. Inter-spacecraft comparison of this data requires high timing accuracy – for example 1ı of phase at 180 Hz is 15 s. The standard timing accuracy of the Cluster mission is 2 ms, and in the worst case, this corresponds to a 4 ms error between spacecraft which is 260ı of phase at 180 Hz. In the normal bit rate, for which the maximum frequency is 10 Hz, the maximum phase error becomes 12ı . Fortunately a considerable improvement in timing accuracy is possible. To understand how this can be achieved it is first necessary to explain how the standard time stamping of Cluster data is performed by the European Space Operations Centre (ESOC). Most Cluster data is not acquired from the spacecraft in real time, but is recorded on an onboard solid state recorder. All data released to experimenters (both recorded onboard and acquired in real time) are time stamped using an onboard clock which is calibrated to UTC using a time correlation process. Until recently, the error of this onboard clock was allowed to increase to the ˙2 ms limit before a new calibration was applied. The time correlation process uses the real time data which is time stamped by the ground stations with the Earth Receive Time. By subtracting various delays, including the propagation time from spacecraft to ground, the Spacecraft Event Time (SCET) is obtained. The total error for real time data is estimated to be 11 s. During each real time pass, the difference (DIFF) between the SCET measured by the onboard clock, and that derived from the Earth Receive Time is monitored. When the difference exceeds 2 ms a new time correlation is performed. This process is described in detail in the ESOC report CL-OPS-TN-1004-OPS-OPC provided to the DWP team as a private communication, but this should be available from the CAA in due course. The DIFF measurements can be used to apply a correction to the onboard clock to bring its accuracy close to that of the real time data. The DIFF is slowly varying, so a simple linear interpolation can be used to estimate the DIFF between real time passes. An independent set of DIFF measurements are also available during real time data acquisition for the Wideband experiment [5] from the ground stations of DSN and Panska Ves. Detailed analysis of the time stamps has revealed that a second correction is needed. When data are recorded onboard, the onboard time counter recorded in the data packets is not precisely correlated with the timing reference pulse distributed to the experiments but may be subject to an offset which is fixed for each period of the same telemetry mode. This term is called OFFSET and specifies the difference between the time of the reference pulse and the onboard time stamp recorded in the data packets. It applies only to data recorded onboard, and is zero for real time data. OFFSET normally ranges ˙180 s for normal mode data, and ˙30 s in burst modes.

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From 2007 November 23, a new procedure has been adopted at ESOC. A time correlation is performed during every nominal pass, instead of waiting until the DIFF reaches 2 ms. DIFF is now usually less than 20 s, but this is not guaranteed. While a correction for the OFFSET term is in principle still needed, for burst mode data (when the most accurate timing is needed), this is less than 30 s, so overall timing will usually be accurate to ˙50 s. This corresponds to 100 s between spacecraft or 6ı of phase at 180 Hz which may be good enough for many purposes. It will still be possible to use the time correction dataset when the highest possible accuracy is needed.

4.2.2 Production The DWP team use the time difference measured by ESOC and DSN to prepare the time correction dataset. Both ESOC and DSN timing are sometimes subject to errors due to ground station configuration problems, so these data are subject to a manual validation process, illustrated in Fig. 4.2. It is observed that most of the points fall close to a smooth curve which is taken to be the correct value. The result is a set of DIFF measurements valid at specific points in time (during ESA or DSN ground station passes). The OFFSET term is determined by analysis of the time stamps of the housekeeping telemetry. The onboard time (OBT) is first converted to its raw 56 bit binary format. The telemetry format generator issues the reference pulse every 5.15222168 s, which is exactly 86439936 OBT counts. Therefore OBT modulo 86439936 should be constant. In practice the OBT modulo changes at every telemetry mode change,

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Cluster SC1 ESOC & WBD DIFF for January 2002 ESOC DIFF WBD diff Valid DIFF

0 –500 –1000 –1500 –2000 –2500 –3000 2002-01-01 2002-01-06 2002-01-11 2002-01-16 2002-01-21 2002-01-26 2002-01-31 Date

Fig. 4.2 Plot of the DIFF values measured by ESOC (C) and DSN ( ). The solid line represents the assumed correct value used to prepare the time corrections

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but tends to return to the same value for each period of real time telemetry. The deviation from the real time value is the OFFSET. Finally, the DIFF and OFFSET values are merged into the TCOR files. Linear interpolation of the original DIFF dataset is used to obtain values at the times of OFFSET changes.

4.2.3 Validation Validation of the TCOR dataset is performed by computing the difference between the time stamps of successive HK formats. The maximum, minimum, mean, and standard deviation from the nominal value are computed for each 24 h period. Values larger than about 3 s indicate an error in the production. These values are removed for the first issue of the dataset.

4.2.4 Caveats Users of the time correction dataset should be aware of its limitations. Most importantly, TCOR data is not available at all times. In the first issue of the dataset, any data that fails validation is simply deleted from the files. TCOR coverage is typically around 90%. Applications requiring accurate timing should confirm that TCOR data is available at the relevant time. Time corrections are provided at the start and end of each period of the same telemetry mode. Time corrections at other times may be obtained by interpolation subject to certain rules. The OFFSET term is constant throughout each period, and the same value will be written in the records at the start and end of the period. If the OFFSET values before and after the required time are different, or either has the fill value of –1e31, then OFFSET is not available for that period. No interpolation between different OFFSET values is allowed. The DIFF may be obtained by linear interpolation of the DIFF values immediately before and after the required time. However, if either DIFF has the fill value of –1e31, then DIFF is not available for that period. It is not allowed to interpolate over a fill value.

4.2.5 Application For WEC data, the time corrections may be applied using the latest version of the Telemetry Extraction and Decommutation (TED) package (see Section 4.5). This is done automatically once TED and the TCOR files are correctly installed. By default, TED 2.5 produces Decommutated Science Data (DSD) files with all time corrections applied. A new bit in the diagnostic word (HKTCOR CORRECTED) will be set when time corrections have been successfully applied. This bit should be checked by applications requiring accurate timing.

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It is also in principle possible to apply time corrections to calibrated high level science data, provided that micro-second level precision has been maintained during the production of that data. The basic method is to obtain the DIFF and OFFSET at the required time, and add these to the data time tag.

4.3 Experiment Status and Commanding Datasets 4.3.1 Status Log (DWP LOG) The status log contains information regarding the overall status of the WEC instruments. The dataset contains one record for each interval that the WEC operates in the same mode. Each record has a total of 64 parameters including:

Time interval Instrument modes Telemetry use statistics Errors and anomalies Summary of voltage and temperature housekeeping

The dataset is produced by automatic analysis of WEC telemetry, and validated by visual inspection. Figure 4.3 shows a typical record from this dataset. Interval: Mode desc.: STAFF SA: Whisper:

2002-01-01T09:57:21Z/2002-01-01T23:34:45Z, (9519 formats) NBR 52s recurrence mode (SWECJ275) NM1, NM1b 4F/CB1050, 1A/AD12500E

TM mode: Model tag: Log event: DWP config: TM overflows: DWP errors: STA SA errors: Correlator:

NM CD09 MACRO FULL, FULL, FULL 0 0 0 ( 42 zeros) COR0, MAR

WEC current: STAFF SA +6V: STAFF SA +5V: STAFF SC +9V: STAFF SC +6V: Wideband +6V:

538.7869 6.0886 5.4880 9.1271 5.7319 6.0566

DWP temp: STAFF SA: Wideband: EFW TM: STAFF SA TM: Correl TM: Unused TM: Total TM:

± 15.2694 ± 0.0013 ± 0.0169 ± 0.0037 ± 0.0105 ± 0.0064

23.45 °C 24.11 °C 26.15 °C 1472 1640 135 81 5217

bps bps bps bps bps

WEC mode: NM52 Clock: 900.0208 Hz SEU count: 0 Checksum: 0000 AP overflows: 0 Whisper errors: 0 STA SC errors: 0 Fixed level: 15 DWP voltage: STAFF SA -6V:

4.8900 ± 0.0536 -5.9049 ± 0.0023

STAFF SC -9V: STAFF SC -6V:

-9.1652 ± 0.0117 -5.7730 ± 0.0310

Whisper temp: STAFF SC:

33.48 °C 20.45 °C

Whisper TM: STAFF SC TM: Wideband TM: TM overhead:

902 960 0 28

bps bps bps bps

Fig. 4.3 One record from the WEC status log dataset showing period from 09:57 to 23:34 on 1 January 2002 for spacecraft 1 (the spacecraft identification is contained within the metadata not shown in this figure)

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4.3.2 Commanding (DWP UT PIOR) This dataset is a record of the command sequences and parameters that have been used to control the WEC. A single dataset covers the four Cluster spacecraft, with a spacecraft mask field used to indicate which spacecraft each command sequence applies to. Normally, all four spacecraft are commanded in the same way, so this format is concise, and helps to highlight exceptions. Such exceptions include special commanding needed to allow for the partial failure of some electric field antennae.

4.4 Particle Correlator Datasets 4.4.1 Description The particle correlator experiment computes the Auto-Correlation Functions (ACF) of electron counts received by the PEACE HEEA sensor via an inter-experiment link. The ACFs are constructed in correlator electron energy bands which correspond to either two or four PEACE energy levels. Constraints of processing and WEC telemetry allows ACFs for only two of the possible 15 energy bands to be processed at any particular time. One of these energy bands is pre-selected while the other available band steps sequentially through the remaining 14 energies, once per spin. Individual ACFs are constructed within separate 1.111 ms DWP clock cycles. The time series of electron counts is of duration 732 s and comprises 61 “count bins” of 12 s duration. Zero to 31 lags are performed on each individual time series to produce a 32-point ACF. Individual ACFs based on separate 1.111 ms DWP clock cycles are summed lag-for-lag on board and the summed ACF is transmitted in telelmetry. This gives the particle correlator the following characteristics: Frequency range 1.4–41.6 KHz in 32 frequency bands and DC to 4 Hz based on successive ACF outputs Energy range 0.6 eV to 26 keV in 15 energy bands (PEACE mode dependent)

The correlator data consists of two identically formatted datasets, one for the fixed energy band (DWP COR FX), and the other for the stepped energy band (DWP COR ST). The full specification is given in Section 5.1 of the DWP CAA ICD [3]. The ACF amplitude is given in counts squared per unit time. The count rate obtained depends on both the particle flux (physical effect) and the geometric factor of the sensor and gain of the micro-channel plates (instrumental effects). It was decided that it was not feasible to provide CAA correlator ACF amplitudes recalibrated to take account of the varying HEEA sensor gain. However, all necessary supporting data (calibrated energy level, lag shift duration and look direction) are included. Results from this experiment were presented by Buckley et al. [1] and Gough et al. [4].

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4.4.2 Caveats Some artifacts are illustrated in Fig. 4.4 which shows the validation plot for 23 April 2002, spacecraft 3. Correlator data is present only when the PEACE HEEA sensor is in use. In the figure, data is absent when PEACE is switched off around perigee (2–4 UTC). In addition there are some periods where, although HEEA is on, the particle count rates are so low that the ACFs are mostly zeros (12 UTC onwards). The energy range corresponds to that being scanned by the PEACE HEEA sensor at any particular time. The energy may be undefined if the PEACE and correlator sweep modes were not compatible (i.e. ACFs acquired at widely different energies have been summed together and no unique energy calibration is possible). The behaviour of the polar angle depends on how PEACE selects the polar zone for the correlator. Early in the mission, the polar zone was selected according to the magnetic field direction, so the polar angle tends to stay on a single value for long periods. Later, the zone stepped through the 12 possible zones, at one step per spin. The azimuth angle is averaged over a spin except in burst modes, where there may be 4, 8, or 16 summed ACFs output per spin. The period 8 to 12 UTC shows a sloping ACF which is due to steep edges in the energy spectrum causing a rapid change in count rate with time during the energy

40 20 0 40

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20 0 30 20 10 0

Azim polar log ev

fix kHz

step kHz

Cluster/DSP DWP correlator summary plot: spacecraft: 3, date: 2002-04-23 File: C3_CP_DWP_COR_FX_20020423_V01, Valid records: 18236, invalid: 0 File: C3_CP_DWP_COR_ST_20020423_V01, Valid records: 18286, invalid: 0 Averaged spectrum (stepped, fixed) and ACF

4 2 –0 –0 360 180 –0

Averaged count rate, versus energy, polar angle and azimuth

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Fig. 4.4 Correlator data validation plot for 23 April 2002, spacecraft 3. The top two panels show the Fourier transform of the ACF for the stepped and fixed energy bands, respectively. The next panel is the ACF itself, summed over fixed and stepped energies. The lower three panels show the count rate as a function of energy level, polar angle and azimuth angle (undefined in this case)

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sweep. This period also shows a correlation at 36 s period (variable, and different on each S/C) and associated high frequency interference line. This effect is present whenever the count rate is very high, and is believed to be caused by a modulation of the gain of the detectors.

4.5 Software The WEC telemetry extraction and decommutation (TED) software is archived for reference purposes only. No DWP software runs in the archive. The latest version is 2.5.0.108 and appears satisfactory for those using it. This version includes support for using the TCOR dataset to obtain 20 s timing accuracy. The TED software is the first stage in the processing of WEC science data by all WEC teams, with the exception of Wideband data telemetered directly to DSN or Panska Ves. It can be used in two ways: 1. As a stand alone application (levelone) reading the RDM, extracting the data for one or more WEC instruments, and writing it to decommutated science data (DSD) files 2. As a library, allowing application software to read the WEC RDM directly Several earlier versions of TED exist and may still be in use by WEC teams. Version 2.4.3 is satisfactory where the standard 2 ms timing accuracy is sufficient. It does not support the use of time correction files. TED version 3 was a major rewrite which unfortunately introduced several new problems, and was therefore abandoned. Version 2.5.0 was based on version 2.4.3 and correctly supported the time correction files. It contained one bug affecting only Wideband data obtained in the burst mode (BM2) which was corrected in version 2.5.0.108. Version 2.5.0.108 is available from the CAA on the DWP documentation page in file: http://caa.estec.esa.int/documents/teams/DWP/ted-2.5.0.108.tar.gz

References 1. Buckley, A.M., Gough, M.P., Alleyne, H., Yearby, K.H., Walker, S.N.: First measurements of electron modulations by the Particle Correlator experiments on Cluster. ESA Spec. Publ. 492, 19–26 (2001) 2. Cornilleau-Wehrlin, N., Chauveau, P., Louis, S., Meyer, A., Nappa, J.M., Perraut, S., Rezeau, L., Robert, P., Roux, A., de Villedary, C., de Conchy Y., Friel, L., Harvey, C.C., Hubert, D., Lacombe, C., Manning, R., Wouters, F., Lefeuvre, F., Parrot, M., Pinçon, J.L., Poirier, B., Kofman,W., and Louarn, Ph.: The CLUSTER Spatio-Temporal Analysis of Field Fluctuations (STAFF) Experiment. Space Sci. Rev. 79, 107–136 (1997) 3. DWP team: Cluster Active Archive: Interface Control Document for DWP. Cluster Active Archive. http://caa.estec.esa.int/caa/instr doc.xml (2005), Accessed 28 May 2008. 4. Gough, M.P., Buckley, A.M., Carozzi, T.D., and Beloff, N.: Experimental Studies of Wave Particle Interactions in Space Using Particle Correlators: Results & Future Developments. Adv. Space Res. 32, 407–416 (2003)

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5. Gurnett, D.A., Huff, R.L., Kirchner, D.L.: The wide-band plasma wave investigation. Space Sci. Rev. 79, 195–208 (1997) 6. Gustafsson, G., Bostrom, R., Holback, B., Holmgren, G., Lundgren, A., Stasiewicz, K., Ahlen, L., Mozer, F.S., Pankow, D., Harvey, P., Berg, P., Ulrich, R., Pedersen, A., Schmidt, R., Butler, A., Fransen, A.W.C., Klinge, D., Thomsen, M., Falthammar, C.G., Lindqvist, P.A., Christenson, S., Holtet, J., Lybekk, B., Sten, T.A., Tanskanen, P., Lappalainen, K., Wygant, J.: The electric field and wave experiment for the Cluster mission. Space Sci. Rev. 79, 137–156 (1997) 7. Johnstone, A.D., Alsop, C., Burge, S., Carter, P.J., Coates, A.J., Coker, A.J., Fazakerley, A.N., Grande, M., Gowen, R.A., Gurgiolo, C., Hancock, B.K., Narheim, B., Preece, A., Sheather, P.H., Winningham, J.D., Woodliffe, R.D.: Peace: A Plasma Electron and Current Experiment. Space Sci. Rev. 79, 351–398 (1997) 8. Pedersen, A., Cornilleau-Wehrlin, N., de la Porte, B., Roux, A., Bouabdellah, A., Décréau, P.M.E., Lefeuvre, F., Sené, F.X., Gurnett, D., R. Huff, R., Gustafsson, G., Holmgren, G., Woolliscroft, L.J.C., Thompson, J.A., and Davies, P.H.N.: The Wave Experiment Consortium (WEC). Space Sci. Rev. 79, 93–106 (1997) 9. Woolliscroft, L.J.C., Alleyne, H.St.C., Dunford, C.M., Sumner, A., Thompson, J.A., Walker, S.N., Yearby, K.H., Buckley, A., Chapman, S., Gough, M.P., and the DWP Co-investigators: The digital wave processing experiment on Cluster. Space Sci. Rev. 79, 209–231 (1997)

Chapter 5

EDI Data Products in the Cluster Active Archive E. Georgescu, P. Puhl-Quinn, H. Vaith, M. Chutter, J. Quinn, G. Paschmann, and R. Torbert

Abstract The Electron Drift Instrument (EDI) contribution to the Cluster Active Archive (CAA) is described. Presented are descriptions of the EDI instrument, the various CAA/EDI data products, the CAA ingestion schedule and the current EDI status. An example of a science application is given for one of the main EDI data products available in the CAA.

5.1 Introduction The contribution of the Electron Drift Instrument (EDI) to the CAA is completely described by the Interface Control Document (ICD) available online [1]. The ICD contains, in addition to the description of the convention on data formats, metadata and delivery to the archive, a section on instrument description, dealing with the scientific objectives of the EDI experiment, a hardware overview, and the description of the data processing chain and of the data products. This paper presents the most interesting aspects of this document for the user of the archive. It briefly describes the EDI experiment, the data processing chain and the EDI data products in the archive and it gives an example of scientific use of one of the main data products. EDI delivers data products and documentation to the archive. The data range E. Georgescu () Max-Planck-Institute for Solar Research, Katlenburg-Lindau, Germany e-mail: [email protected] P. Puhl-Quinn, H. Vaith, M. Chutter, and R. Torbert University of New Hampshire, Durham, USA e-mail: [email protected]; [email protected]; [email protected]; [email protected] J. Quinn Boston University, Boston, MA, USA e-mail: [email protected] G. Paschmann Max-Planck-Institute for Extraterrestrial Physics, Garching, Germany e-mail: [email protected]


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from the complete set of raw data to auxiliary and final products. The documentation refers to the already mentioned ICD, to the instrument user manual, instrument reference papers and software scripts.

5.2 Instrument Overview The EDI instrument and its modes of operation are described in detail by Paschmann et al. [2] and Quinn et al. [3]. EDI was designed to measure the electric field E? perpendicular to the ambient magnetic field B, when the gradient of B in the plane perpendicular to it can be neglected. This is done in an active mode using the electron drift technique. EDI also operates in a passive mode, whereby ambient electrons are detected.

5.2.1 Electric Field Measurement The aim is to determine the drift velocity of the injected electrons Vd induced by an electric field E? and/or a magnetic-field gradient rB? . Under the assumption that the rB? -drift can be ignored, the electric field can be computed according to: E? Š Vd B

(5.1)

The basis of the electron-drift technique is the injection of weak beams of electrons perpendicularly to the ambient magnetic field and their detection after one or more gyrations. In the presence of a drift velocity, the circular electron orbits are distorted into cycloids. Their shape depends on whether the beam is injected with a component parallel or anti-parallel to the drift velocity. The lengths of the two orbits and the electron travel times differ. To be able to realize both types of orbits simultaneously, EDI uses two guns and two detectors. Figure 5.1 shows examples of these two orbits in the plane perpendicular to B, which we refer to as the B? -plane. The instrument records the positions and firing directions of the guns and the times of flight of the electrons. The magnetic field information is received through the inter-experimental link from the FGM (flux-gate magnetometer). The drift velocity can be determined by two methods: triangulation and time-offlight. (a) The basis of the triangulation technique, explained in detail in [3], is the determination of the ‘drift-step’ vector d which is the displacement of the electrons after a gyro time Tg . The drift velocity Vd is: Vd D d=Tg

(5.2)

The location in the B? -plane, at which electrons reach the detector after one gyration, can be viewed as the ‘target’ for the electron beams.

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Fig. 5.1 Principle of operation for EDI

(b) The time-of-flight technique uses the difference of time-of-flight for the electrons emitted with velocity components parallel and anti-parallel to the drift velocity. The electrons emitted with their velocity directed with a component parallel to Vd have a time-of-flight T2 that is shorter than Tg while the electrons emitted in the opposite direction have a time-of-flight T1 that is longer than Tg : T1;2 D Tg .1 ˙ Vd =Ve /

(5.3)

where Ve is the electron velocity, which depends on the initial kinetic energy. From Eq. 5.3 it follows immediately that the difference between the two times-of-flight T D T1 –T2 provides a measure of the drift velocity magnitude, Vd Vd D T Ve =.2Tg /

(5.4)

while their sum is twice the gyro time: T1 C T2 D 2Tg

(5.5)

Equation 5.4 is the basic equation of the time-of-flight technique. Since Tg D 2me =.eB/

(5.6)

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where me and e are the mass and the charge of the electron, the time-of-flight measurements allow B to be determined as well. The triangulation and time-of-flight techniques complement each other ideally. While triangulation naturally becomes increasingly inaccurate if the target moves further and further away, the time-of-flight technique becomes more accurate because, according to Eq. 5.4, T increases with increasing drift step, and thus becomes easier to measure. EDI consists of two gun-detector units (GDUs) and a controller unit. The GDUs are mounted on opposite sides of the spacecraft and have oppositely directed fields of view. The guns are capable of firing in any direction within more than a hemisphere to accommodate arbitrary magnetic and electric field directions. Similarly, the detectors can detect beams coming from any selectable direction within more than a hemisphere. Electron energies can be switched between 0.5 and 1.0 keV. In order to measure the electron times-of-flight, as well as to distinguish beam electrons from the background of ambient electrons, the electron beams are amplitudemodulated with a pseudo-noise (PN) code. To find the beam directions that will hit the detector, EDI sweeps each beam in the plane perpendicular to B at a fixed angular rate (typically 0:2ı =ms) until a signal has been acquired by the detector. Once signal has been acquired, the beams are swept back and forth to stay on target; this operational mode is called windshield-wiper (WW). As the times when the beams hit their detectors are neither synchronized with the telemetry nor equidistant, EDI does not have a fixed time-resolution.

5.2.2 Ambient Electron Monitoring When the electron beams are off, the EDI detectors allow for ambient electron measurements with very high sensitivity and time resolution, albeit at fixed energies of 0.5 or 1.0 keV. In this mode the two detectors which are facing opposite hemispheres are looking strictly into opposite directions. Either both detectors are looking in the plane perpendicular to B (pitch angle of 90ı ), or one detector is looking along B while the other is looking antiparallel to B (pitch angles of 0ı and 180ı ). When looking in the plane perpendicular to B the two directions within the plane are determined by the cross product of the magnetic field vector B with a selectable but fixed vector P that is constant in the spinning spacecraft frame of reference. When looking parallel/antiparallel to B the two detectors switch roles every half spin of the spacecraft as the tip of the B vector spins outside the field of view of one detector and into the field of view of the other detector. In nominal telemetry mode (NM) there are 16 counts per detector and per second. Each count is accumulated over approximately 16 ms (1/64 s). In Burst mode (BM1) there are 128 counts per detector and per second, and the accumulation time is approximately 8 ms (1/128 s). Counts are accumulated synchronously by the two detectors and each counts pair is stored in telemetry with its corresponding look direction, expressed in spinning spacecraft coordinates (azimuth and polar angle). As the two look directions are antiparallel only one set of angles needs to be transmitted. As the spacecraft is spinning the

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look directions need to be maintained in order to point at a fixed pitch angle. The look directions reported in telemetry correspond to those used at the center of the respective sample accumulation time window. Full resolution AED (Ambient Electron Data) starting October 2004 have been delivered for ingestion in the CAA. Before this time, the detectors’ configuration for ambient operations and the correction procedures were evolving continuously and hence an ambient electron data product is not available.

5.2.3 Operations and Limitations EDI operations are limited by low magnetic fields and/or high background electron fluxes. Low magnetic field requires high beam currents to overcome the beam divergence along large gyro orbits, and to get sufficient signal-to-background ratio. However large beam currents, in conjunction with the beam-modulation and – coding, lead to interference with the electric wave measurements by the WHISPER instrument. Moreover, the smaller the magnetic field gets, the higher the requirement for very precise on-board magnetometer calibrations. Last but not least, rapid timevariations in magnetic and/or electric fields, as well as large fluxes of background electrons can also cause loss of track. Because of the noted interference with the WHISPER measurements, EDI beam operations have been subject to a 6-orbit cycle, where high beam currents (up to 300 nA) were allowed in only two out of six orbits, while currents were limited to about 100 nA in another orbit and no beam operation was allowed outside 4 h of perigee in the remaining three orbits. The code repetition frequency and beam current is delivered to the wave instruments as CRF (Code Repetition Frequency) auxiliary data product to help them recognize and correct for this interference.

5.3 Data Processing Chain The data processing chain consists of onboard, ground and science processing. The onboard processing writes to telemetry the measured quantities and instrument parameters. A schematic representation of the data processing chain is given in Fig. 5.2. The telemetry data consists of three types: (1) housekeeping (HK TM); (2) science normal mode (NM TM); and (3) science burst mode (BM TM). They are input into the EDI ground-processing chain after having a DDS-header (Data Disposition System, described in [5]) attached during the ground-processing performed at ESOC. The ground processing software consists of Merged Science File (MSF) production and the Pick-Library. The first merges the TM-packets and orders them in time and the second extracts the quantities needed by the science processing as input. The output of the science processing consists of time series of physical quantities contained in the science data products, as discussed in detail in the next section.

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EDI Data Processing Chain and Output ONBOARD SW

OUTPUT

HK TM

GROUND SW

(ESOC)

SCIENCE OUTPUT

SW

RDM

wwconv (c) caa_editof (IDL)

NM TM

OUTPUT EGD

qstat (c)

QSTAT

EDI_PISO (IDL)

PP PPplus MPD

MSF BM TM MSF (GCDC) FGM Data PICK LIBRARY (IDL) AEC

SW

Software TBA for documention (white on green)

DATA

SurveyPlot (IDL)

C3-3h Survey Plots

AE (IDL)

AED

Data product TBA = to be archived (white on blue)

Fig. 5.2 EDI data processing chain and output

The CRF and CLIST (CaveatLIST) auxiliary products used for cross-calibration with other instruments are not represented. They are produced from the MSF-files using the Pick-Library and an IDL main program that is archived for documentation. The software, archived for documentation only, is represented with white text on green background and the data products with white on blue (violet).

5.4 Instrument Data Products As we have learned from the instrument description section EDI operates in two modes: (1) an active one called WW (windshield wiper), or, EF (electric field), where electrons emitted by the guns are detected; and (2) a passive one called ambient electron mode (AE), where the guns are not emitting. Whenever EDI operates in its active mode, the electric field and the drift velocities of the electrons are measured. The data are analyzed with two techniques: triangulation and timeof-flight. The technique which gives better results based on some error criteria produces the winners, the other the losers. All results are assigned a quality flag (good/caution/bad).

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In addition to the main data products, raw and auxiliary data are being archived.

Raw data consist of merged science files (MSF); they are obtained by merging the housekeeping and science (burst (BM) and normal (NM) mode) telemetry files. They are in binary format and are input for the Pick-Library that is used by all science processing programs. Auxiliary are either data used internally by the main data production software (QSTAT) or data dedicated to intercalibration (EGD, CRF) or time-interval lists of the EDI operation modes (CLIST). – QSTAT contains a table of 24 rows (for each hour of the day) and 6 columns (for each 10 min of an hour) with detection efficiencies. The detection efficiency is defined as the percentage of the number of spin periods with at least 4 successful measurements per spin to the total number of spin periods. – AEC (ambient electron correction file) are used to correct raw, ambient electron counts for the internal, theta/phi dependence of the individual detectors. Transformation of the corrected counts to a particle flux is a non-trivial matter, and has only been performed (to-date) on a case-by-case basis. – CLIST files contain a listing of time intervals with the two possible operation modes of EDI: WW and AE. – EGD parameters are measurement time tags with microsecond precision, timeof-flight (TOF) and its error (sigma TOF) in microseconds, and the label of the used detector unit (DU). Using Eq. 5.6 the magnetic field magnitude can be determined and compared with FGM or WHISPER measurements for crosscalibration. An example of use of the EDI CAA auxiliary data is given in [4], where the QSTAT and EGD datasets were used to check and improve the calibration of the flux-gate magnetometer (FGM).

Main data products contain: – For the WW mode: time series of the three components of the electron drift velocity and of the three components of the electric field in Cartesian GSE coordinate system (corrected for spacecraft motion) with different qualities and time resolution (PP, PPP, MPD) – For the AE mode: time series of ambient electron counts for the three pitch angles .0ı ; 90ıo ; 180ıo /, the detector look direction in the spacecraft frame and in GSE and the status for AE mode – Overview plot of the main parameters for both modes for every 3 h for one reference spacecraft (usually C3)

The data products, their acronyms, contents, qualities, resolutions, time ranges and formats are summarized in Table 5.1. For the time ranges, following abbreviations have been used: d: day, mo: month, h: hour. Note that they are differences between the CAA acronyms and the group of letters appearing in the file and parameter names (e.g. the D for data was left away for MPD and AED).

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Table 5.1 EDI data products in the CAA CAA Data type Nr acronym Format (mode) 1 PP CDF MAIN

CEF

(WW)

2

PPP

CDF

MAIN (WW)

3

MPD

CDF CEF

MAIN (WW)

4

AED

CDF CEF

MAIN (AE)

5

3hSPLOT

PNG

MAIN Graphics (AE + WW)

6

EGD

CEF

Auxiliary (WW)

7

QSTAT

ASCII

Auxiliary (WW)

8

CLIST

CEF

Auxiliary (WW/AE)

9

AEC

ASCII

Auxiliary (AE)

10

CRF

CEF

Auxiliary (WW)

11

MSF

Binary

RAW

Name, content (C), quality (Q), time resolution (R) Prime Parameter C: electric field, drift velocity, status and errors Q: winners, good/caution R: spin (4 s) Prime Parameter plus C: electric field, drift velocity, status, errors, drift step (see Table 5.2) Q: winners + losers good/caution/bad R: spin (4 s) Merged Parameter Data C: electric field, drift velocity, status and errors R: 1–4 s Q: winners, good/caution/bad Ambient Electron Data C: ambient electron counts at 0ı ; 90ı ; 180ı pitch angles R: full 3-hourly Survey plots C: MPD, AED and CLIST parameters for one spacecraft (usually C3) Electron Gyrotime Data C: Electron time-of-flight, error and GDU-flag R: full Quality STATistics C: EDI detection efficiency (beam tracking performance), R: 10 min Caveat List C: Time intervals of EDI operation modes (WW/AE) AE Correction files Used to correct raw, ambient electron counts for theta/phi Code Repetition Frequency C: code repetition frequency, beam current index R: telemetry (5:12 s) Merged Science Files C: Merged HK + NM + BM

Time range 1d

1d

1d

1d

3h

1d

1d

1 mo

1d

1d

1d

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Table 5.2 EDI PP (MPD) and PPP parameters for CDF and CEF files (WW operation mode) CEF fPPjMPg CDF- fPPjMPg PP-Plus file parameters (CDF) parameters (winners and losers) C1 CP EDI fPPjMPg (“winners” only) time tags Epoch Epoch Half interval Status Status Status V ed xyz gse V ed xyz gse V ed xyz gse E xyz gse E xyz gse E xyz gse Reduced chi sq Reduced chi sq Reduced chi sq Drift step mag Drift step mag error inertial Drift step azi error inertial Nbeam Status loser V ed xyz gse loser E xyz gse loser Reduced chi sq loser Drift step mag loser Drift step mag error inertial loser Drift step azi error inertial loser Nbeam loser

Table 5.2 gives an overview of the WW-mode main data parameters. The first two columns describe the contents of the PP and MP files for both CEF and CDF formats. The third column describes the contents of the PP-Plus files, which are only available in CDF format. The PP-Plus files are meant for experts who want to compare the results of both “winner” and “loser” methods. The differences between the CEF and CDF files for PP or MPD are in time parameters. The CEF files have “time tags” variable instead of “Epoch”. The MP data have an additional half-interval parameter to account for the mixed resolution. The exact nature and quality of the data is indicated in the seven EDI status bytes described in detail in [5]. Status[0] byte is the data quality flag as defined for all Cluster experiments: 0, 1, and 2 for bad, use with caution and good data, respectively. The others define the percentage of 1 keV beams used in entire spin (Status[1]), the percentage of the highest quality beams used in entire spin (Status[2]), the chosen “winner” method among Triangulation/Time-offlight/simultaneous-time-of-flight with the ambiguity flag of the choice (Status[3]), percentage of Triangulation outliers (Status[4]), and the magnitude error (as a percentage) and azimuthal error (in degrees) on the drift step in the spacecraft frame (Status[5] and Status[6], respectively). The following caveats must be considered:

The measured electron drift velocity cannot always be separated into the electric-field and magnetic gradient induced parts; in such cases the computed electric fields are subject to contamination by magnetic gradient effects.

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E. Georgescu et al. Table 5.3 Ambient electron data parameters CEF variable name CDF variable name ( C# CP EDI AE) Epoch C# EDI AE time tags C1 CP EDI AE C1 CP EDI AE C1 CP EDI AE AE status C# Status AE theta CL# Theta index AE phi D1 CL# Phi index AE counts CL# GDU1 PA 90 counts GDU1 PA 90 AE counts CL# GDU2 PA 90 counts GDU2 PA 90 AE counts CL# GDU1 PA 180 counts GDU1 PA 180 AE counts CL# GDU2 PA 0 counts GDU2 PA 0 AE counts CL# GDU1 PA 0 counts GDU1 PA 0 AE counts CL# GDU2 PA 180 counts GDU2 PA 180 AE D1 GSE CL# D1 xyz gse

The data quality is variable, and it is therefore mandatory that the status bytes be consulted before interpreting the data. The number of samples in the averages is variable.

Note that all EDI electric field and drift velocities delivered to the CAA, regardless of product, are in the inertial frame. Table 5.3 shows the AED parameters. These are raw data counts and in order to transform them in relative particle fluxes the theta and phi dependence must firstly be removed by using the AEC files. The AEC files contain a list of correction factors for the phi and theta angles of the look directions. The 6 “count” variables are signed 2-byte integers. The fill value for these counts is -32,768. The theta variable is the same for both EDI detectors and contains an index between 0 and 138; each step corresponds to 0:703125ı. The phi variable contains an index between 0 and 127 and each step corresponds to 2:8125ı . The reported phi is the azimuth look direction for detector 1. The phi for detector 2 is opposite, i.e. phi2 D 64 – phi1, and then adjusted so that it is between 0 and 127 if necessary. Only 2 bits of the status byte are used. Bit 0 indicates the energy: 1 is used for 1 keV, and 0 is used for 0.5 keV. Bit 1 indicates sub mode: if it is set, the data is from BM1 data; otherwise, the data is from NM123 or BM2. AE D1 GSE CL# (or D1 xyz gse C# CP EDI AE) is the detector 1 look direction in Cartesian GSE coordinates, where #=1, 2, 3 is the spacecraft id. The ambient electron counts must be divided by 2 in NM (normal mode) because the NM accumulation interval is twice that of BM1. The following caveats must be considered:

The raw-data counts have to be corrected for the angular dependence of the efficiency. The status byte and the AEC-files must be used as described above. Ambient electron data are available since October 2004 on C1, C2 and C3, see CLIST files for time intervals. The EDI instrument on C2 is working only in ambient mode.

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5.5 Example of Science Application An example of using EDI electric field data in the inner magnetosphere is described in this section. The primary electric field science product delivered to the CAA by the EDI team is the variable time-resolution Merged Parameter Data, or, MPD, as indicated in Table 5.1. This product is found at the CAA after selecting “EDI” as the “Experiment”, and then “Science” as the data category. The MPD data is available in either CDF or CEF formats, which is indicated in the product name as either C1 CE EDI MP CDF or C1 CP EDI MP, respectively (using spacecraft 1, or, C1, as an example). As noted earlier, the MPD data has a variable time-resolution of 1, 2 or 4 s. This differs from the PP dataset (i.e., C1 CP EDI PP, which is located under the “CSDS” data category) time-resolution of 4 s (spin-resolution). Another important difference between the MPD and PP datasets is that while the poorest quality data (i.e., quality D “BAD” data) has been filtered out of the PP dataset, it remains in the MPD dataset. The “BAD” data exists in the MPD dataset because it is useful for the advanced user who might be studying data quality itself. Therefore, it is necessary for occasional users to apply their own quality filter on the MPD dataset if desired. This can be done using the variable “Status C1 CP EDI MP”, or, Status, for short. As mentioned in the previous chapter the 0th byte of the Status is the quality flag and 0 indicates “BAD” data. It is recommended that the CAA user filter out the “BAD” data. Figure 5.3 shows MPD data from Cluster 1 on 08-Apr-2004. Plotted in the left-hand column (Panels a–c) is electric field data, which has the variable name “E xyz gse C1 CP EDI MP” in the MPD dataset. From top to bottom are the x, y and z components in GSE coordinates (Ex ; Ey and Ez , respectively). The “BAD” data has been filtered out. The MPD dataset contains electric fields and drift velocities in the inertial frame (i.e., the spacecraft motion has been removed). This hour of data, from 06:45 to 07:45 UT, encompasses perigee and the crossing of the magnetic equator in the pre-midnight MLT range. The two large electric field structures with peak magnitudes approaching 25 mV/m at approximately 06:58 and 07:28 UT were identified in [6] as subauroral ion drift (SAID) channels. This identification was facilitated by looking at the data in a more useful coordinate system than GSE. The electric field measured by EDI is only the perpendicular component, and therefore is only a two dimensional vector in a coordinate system with one of its axes along the magnetic field. This type of coordinate system is known as a “magnetic field-aligned” system, or, MFA system. Using the magnetic field data from the FGM experiment and the Cluster position data from the AUX data files, it is possible to construct an MFA system. In the inner magnetosphere, the magnetic field, B, and the position vector, P, form roughly a meridional plane. The MFA system constructed for this example has B lying along the z-axis while the x-axis lies in this meridional plane and points outward. The y-axis completes the coordinate system and points generally eastward. At the magnetic equator, for instance, the z-axis points northward (aligned), the y-axis points eastward (azimuthal) and the x-axis points outward (radial).

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Ez [mV/m]

c

Er [mV/m]

0 –10 –20

e

20 10 0 –10

Ea [mV/m]

Ey [mV/m]

b

20 10

–20

f

20 10 0 –10 –20

UT: 06:45 07:00 MLT: 22:00 21:55 R: 4.46 4.30 MLAT: –10.78 –2.81 08-Apr-2004

EDI Electric Field in MFA

d

E|| [mV/m]

Ex [mV/m]

a

20 10 0 –10 –20 20 10 0 –10 –20 20 10 0 –10 –20

07:15 21:50 4.18 5.72

07:30 21:43 4.10 14.66

07:45 21:36 4.06 23.84

06:45 22:00 4.46 –10.78

07:00 21:55 4.30 –2.81

07:15 21:50 4.18 5.72

07:30 21:43 4.10 14.66

07:45 21:36 4.06 23.84

Fig. 5.3 EDI electric field data from Cluster 1 on 08 April 2004. Plotted in the left-hand column are the x, y and z components of the perpendicular electric field in GSE coordinates. This is Merged Parameter Data (MPD), available at the CAA. Ephemeris data are tabulated underneath the UT labels. Plotted in the right-hand column are these same data in an alternative, magnetic field-aligned (MFA) coordinate system. From top to bottom are the radial, azimuthal and parallel components

The right-hand column of Fig. 5.3 (Panels d–f) shows the electric field data transformed into this MFA system. From top to bottom are the radial .Er /, azimuthal .Ea / and parallel Ejj components. By definition, the parallel component is identically zero (Panel f). In the MFA system, the electric field is close to being purely radially outward (Panel a). This is a defining characteristic of magnetospheric SAID electric fields. When mapped to ionospheric heights, the SAID field is directed poleward. The SAID electric field orientation and morphology produces a westward drift channel extending from the southern to northern ionosphere at subauroral latitudes. Subsequent SAID observations by Cluster have been reported in [7].

5.6 Summary of EDI Contribution EDI contributes to the Cluster Active Archive with data (raw, auxiliary and main products) and documentation. The main data products contain:

Time series of the following physical quantities (with errors and data qualities): (a) E D electric field vector in GSE, (b) V D drift velocity vector in GSE,

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(c) N D high resolution ambient electron counts at 0ı , 90ı and 180ı pitch angles, at fixed energy (0.5 or 1.0 keV). The time resolution is between 1 and 4 s except for (c). Graphics: Survey plots of the physical quantities and operation modes for one reference spacecraft (usually C3) with 3 h time range.

The auxiliary data contain time series of:

QSTAT: EDI detection efficiencies (10 min resolution) EGD: electron time-of-flight (full resolution, not regularly spaced) CLIST: listing of instrument operation mode time intervals CRF: code repetition frequencies, beam current indices, 5 s resolution AEC: correction tables for the AE mode

The documentation consists of:

ICD – a complete description of the EDI contribution to the CAA Instrument Reference Papers and User Manual Program Scripts

EDI data production and delivery are conforming to the ICD and is an ongoing activity. Currently all data for 2001–2005 were delivered and ingested. The data for 2006–2009 are going to be delivered until mid 2010. Note that all data files in the CAA contain in their headers caveats with general information for the user regarding the mission, the observatory, the instrument and the dataset. These state for instance that EDI didn’t work on Cluster 4 or that AED are available starting October 2004 and that C2 works only in ambient mode since April 2004. Acknowledgments The authors wish to thank the CAA team for their efforts in building the archive.

References 1. http://caa.estec.esa.int/documents/ICD/CAA EDI ICD V13.pdf 2. Paschmann G. et al., The Electron Drift Instrument on Cluster: overview of first results, Annales Geophysicae (2001) 19: 1273–1288 3. Quinn, J. M., Cluster EDI convection measurements across the high-latitude plasma sheet boundary at midnight, Annales Geophysicae (2001) 19: 1669–1681 4. Georgescu E. et al., Use of EDI Time-of-Flight Data for FGM Calibration Check on CLUSTER, Proceedings of the Cluster and Double Star Symposium 5th Anniversary of Cluster in Space, ESTEC, Noordwijk, ESA SP-598, 2005 5. “Users Guide to the Cluster Science Data System”, DS–MPA–TN–0015, issue3, 2008, ftp://ftp.estec.esa.nl/pub/csds/task for/users guide/csds guide 3 0.pdf 6. Puhl-Quinn, P. A., H. Matsui, E. Mishin, C. Mouikis, L. Kistler, Y. Khotyaintsev, P. M. E. Decreau, and E. Lucek (2007), Cluster and DMSP observations of SAID electric fields, J. Geophys. Res., 112, A05219, doi:10.1029/2006JA012065 7. Mishin, E. V. and P. A. Puhl-Quinn (2007), SAID: Plasmaspheric short-circuit of substorm injections, Geophys. Res. Lett., Vol. 34, L24101, doi: 10.1029/2007LG031925

Chapter 6

The EFW Data in the CAA Y. Khotyaintsev, P.-A. Lindqvist, A. Eriksson, and M. André

Abstract The Electric Field and Waves (EFW) instrument measures the 2D electric field (in the spacecraft spin plane) and spacecraft potential with sampling rates, on some occasions, up to 36,000 samples/s. We present a summary of the CAA data products produced from the EFW measurements. We briefly describe the production pipeline from the raw data to final data products and discuss the most common caveats.

6.1 Introduction The Cluster Active Archive (CAA) was created to archive all data from the Cluster mission. Emphasis is on providing the scientific community with calibrated high resolution science data. This paper describes the CAA products from the EFW instrument. It gives some brief information on the instrument, followed by a description of all EFW parameters available in CAA. Some important things to keep in mind when using the data are given in Section 6.5. For those interested, there is also a section describing some of the processing details of the electric field data.

6.2 Measured Quantities, Coordinate Systems A detailed description of the EFW instrument can be found in Gustafsson et al. [5]. We first briefly describe the raw quantities measured by the instrument which correspond to Level 1 products in the CAA. The detector of the instrument consists of four spherical sensors numbered 1 to 4 deployed orthogonally on 44 m long wire booms in the spin plane of the spacecraft. The potential drop between Y. Khotyaintsev (), A. Eriksson, and M. André Swedish Institute of Space Physics, Uppsala, Sweden e-mail: [email protected] P.-A. Lindqvist Royal Institute of Technology, Stockholm, Sweden


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two sensors, separated by 88 m tip-tip (62 m in case of P32, see Section 6.5.2) is measured to provide an electric field measurement (CAA quantities P12/P32 and P34). The probe difference signals are normally routed through 10 Hz low-pass filters if sampled at 25 s1 , and through 180 Hz low-pass filters when sampled at 450 s1 (see Section 6.5 for the exceptions). The potential difference between each sensor and the spacecraft (CAA quantities P1, P2, P3 and P4) is measured separately with a sampling frequency of 5 s1 after routing through low-pass filters with a cut-off frequency of 10 Hz. The unfiltered analog output signals from the spherical sensor preamplifiers are also provided to the wave instruments (STAFF, WHISPER and WBD) for analysis of high frequency wave phenomena. The EFW instrument measures the electric field only in the spacecraft spin plane, therefore a spin-plane oriented coordinate system is best suited for scientific studies involving the electric field. The ISR2 (Inverted Spin Reference) system, also known as DSI (Despun System Inverted), is such a system. The X and Y axes are in the spin plane, with X pointing as near sunward as possible and Y perpendicular to the sunward direction, positive towards dusk. The Z-axis is along the (negative) spacecraft spin axis, towards the north ecliptic. The coordinate system is called “Inverted” because the actual spin axis of Cluster is pointing towards the south ecliptic. The difference between ISR2 (DSI) and the GSE (Geocentric Solar Ecliptic) is a tilt of 2ı to 7ı of the Z-axis performed in order to avoid shading of the EFW probes by the spacecraft.

6.3 Science Data Products As already mentioned the raw EFW data correspond to the Level 1 products in the CAA. They are archived for reference purpose only. In this section we discuss the science data represented by Level 2 (full resolution) and Level 3 (4 s resolution) products in the CAA. For a complete list of the EFW products see Lindqvist and Khotyaintsev [6]. The spacecraft potential (P) is here defined as the average of all available probes, measured relative to the spacecraft. It relates linearly to true spacecraft potential Vsc with respect to the surrounding plasmas, approximately as Vsc D 1:23 P C 0:7 V [1]. We here keep the opposite sign in order to get a quantity approximately logarithmically co-varying with the plasma density (see Section 6.5). If all four probes are available, the average is done over all 4 probes. If only two or three probes are available, the average is done over 2 probes (P1 and P2, or P3 and P4). If only one probe is available, this quantity is the value of that probe. The number of probes used for P is given in the Parameter caveats. The electric field vector (Ex and Ey / in the spin plane is represented by the quantity E. For Level 2 data it is computed using 2, 3 or 4 probes. When 4 probes are available, the computation of E is straightforward. When 3 probes are available, the computation is also mathematically straightforward, but the electric field has larger errors since the measured components are not orthogonal. When only 2 probes

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are available, only one component of the electric field is measured in the spinning system, and thus E will have a strong spin modulation (see Section 6.5.2). For Level 3 data E is computed from a least-squares fit of a sine wave to one probe pair (P12 or P34) over 4 s (approximately one spin). The least-squares fit is normally done on P34, if available, otherwise on P12. The result is two components of the electric field (Ex and Ey / and a measure of the standard deviation of the raw data points from a sine wave (Sigma). The details of production are described in the next section. EINERT is the electric field vector in the spin plane in the inertial reference frame. It is computed from E by subtracting the spacecraft motion induced electric field vSC xB, where vSC is velocity of the spacecraft with respect to the center of the Earth. EGSE is the full 3-dimensional electric field vector in the GSE coordinate system. It is computed from EINERT by first computing the third (non-measured axial) component of the electric field using the zero parallel electric field assumption, E B D 0, and then transforming the full 3D vector into the GSE coordinate system. These computations are only done when the magnetic field direction is more than 15ı away from the spin plane and jBZ j is larger than 2 nT. Otherwise the error in the computed electric field component becomes too large. The plasma convection velocity VGSE is computed from EGSE and the magnetic field B as VGSE D .EGSE B/=B2 . This computation relies on the availability of EGSE, which in turn depends on the orientation and magnitude of B.

6.4 Production of the Electric Field Data Here we describe the processing chain of the electric field data. At the initial stage of production we remove intervals with: bad data due to issues with electronics, probe saturations due to low plasma density, and non-optimal bias current settings. Usually, only a few minutes of data are removed from each orbit for these reasons. However, large data gaps may occasionally occur. If the spacecraft is in the solar wind we attempt to correct for the wakes usually present in the raw data (see Section 6.5.3). In the presence of a constant ambient electric field, the raw data signal (probe potential difference) is a sine wave where the amplitude and phase give the electric field magnitude and direction. A least-squares fit to the raw data of the form y D A C B sin .!t/ C C cos .!t/ C D sin .2!t/ C E cos .2!t/ C : : : is done once every 4 s .2=! 4 s is the spacecraft spin period), and gives the following output: The sine and cosine terms, B and C (the electric field in ISR2). The raw data DC offset, A. Ideally, the DC level of the raw data should be zero,

however small differences between the probe surfaces and in the electronics create a DC offset in the raw data. If not corrected, it shows up as a signal at the spin frequency in the despun electric field.

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The standard deviation of the raw data from the fitted sine wave. Higher order terms, D, E, . . . , may be used for diagnostics of data quality.

The electric field (computed from B and C ) and the standard deviation are available in the CAA as Level 3 E. The raw data DC offset (A) is used for processing the Level 2 data. It is applied to P12/P32 and P34 prior to despinning. Variations in the electric field cause small changes of the DC offset, and therefore the DC offset is smoothed using a weighted average over seven spins [6]. Intervals containing WHISPER pulses are blanked prior to despinning (see Section 6.5.6). Another offset which is applied during despinning is the so called Delta offset, which is the difference between the electric fields in ISR2 obtained from the least-squares fit procedure for individual probe pairs, P12/P32 and P34. This offset comes from slow evolution of the probe characteristics with time. A value averaged over several orbits is used. At this stage both the Level 2 (from despinning) and Level 3 (from least-squares fit) electric fields contain systematic errors, namely an amplitude factor and a DC offset, which need to be corrected for. The ambient electric field is “short-circuited” by the presence of the spacecraft and wire booms. This is caused by the spacecraft potential, which is also the potential of the wire booms, extending out to a large distance from the spacecraft. On the basis of simulations and comparisons with other Cluster instruments it has been determined that the measured electric field magnitude needs to be multiplied by a factor of 1.1 to get the real electric field (see also appendix 4 in Lindqvist and Khotyaintsev [6], Cully et al. [1]). This value is routinely applied for all spacecraft and for the entire mission. However, this factor depends on plasma environment, and in some cases may deviate from the value used. In case of Cluster it can vary in a range from 1.0 to 1:2. The spacecraft, wire booms and probes emit photoelectrons, which create an excess of negative charge on the sunward side. This will be measured by the EFW instrument as a spurious sunward electric field, generally referred to as the sunward DC offset. The offset varies slowly with time and plasma conditions around the spacecraft, and is slightly different for the different spacecraft. Its magnitude is determined by comparisons with other measurements, performed by Electron Drift Instrument (EDI) and Cluster Ion Spectrometry experiment (CIS). The values of the offsets that have been subtracted from the data in the CAA are given in the Parameter caveats. The photoelectron asymmetry responsible for the sunward DC offset by definition gives an offset in the sunward direction only. However, results of comparisons with other instruments have at times shown an offset of a fraction of mV/m also in the duskward direction, which is not yet well understood. In most cases the duskward offset is negligible. Prior to delivery to the CAA we attempt to identify and blank intervals with suspected spurious fields in various magnetospheric regions (see Sections 6.5.4 and 6.5.5).

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6.5 Caveats Much effort has been spent on calibrating the data and removing spurious effects to give a useful database for scientific analysis. In spite of this, there will always be data in the CAA which are not of optimum quality, and this section attempts to describe some of the potential problems in the data the CAA user must be aware of.

6.5.1 10 Hz Filter Failure on C2 The 10 Hz filter on probe 3 on C2 failed on 25 July 2001. As a workaround for this, the 180 Hz filter has been used for the difference signals sampled at 25 s1 (sc nominal mode), which has no effect on the 4 s resolution data or on the burst mode data. There is a marginal effect on the 25 s1 data in those situations with large amplitude electric field fluctuations present between 10 and 180 Hz, when these fluctuations alias into frequencies below 10 Hz. After the filter failure, probe 3 on C2 is also not used for computation of the spacecraft potential.

6.5.2 Probe 1 Failure on C1, C2 and C4 Normally, the spin plane electric field is computed using the orthogonal signals P12 and P34. However, a failure occurred on probe 1 on C1 (28 December 2001), on C3 (29 July 2002), and on C2 (13 May 2007). After this, it is no longer possible to measure P12, but a workaround was implemented in the flight software to use P32 instead, the so-called asymmetric mode. This was fully implemented on 29 September 2003 on C1 and C3, and on 24 November 2007 on C2. In the intermediate period (Jan 2002–Sep 2003 for SC1, Aug 2002–Sep 2003 for SC3, and May–Nov 2007 for SC2), full resolution data are available only from one probe pair, which means that they contain a strong spin modulation, and must be used for overview purposes only. The 4-second resolution electric field data are not affected. Data produced from P32 and P34 also have a lower quality with a significant error signal around 0.25 and 0.75 Hz. Figure 6.1 shows examples of the electric fields obtained in the cases of: (1) orthogonal signals P12 and P34, (2) P34 only, (3) the asymmetric configuration.

6.5.3 Solar Wind Wakes The streaming solar wind creates a negatively charged wake behind the spacecraft, in the anti-sunward direction. As the individual probes enter and exit this wake, there is a dip in the probe potential, and thus a spike in the raw data signal twice per spin

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Fig. 6.1 Examples of spectra and time series (X and Y components in ISR2, circles show 4 s data) of electric field obtained in different instrument configurations on Cluster 1. Panels show (top) normal configuration – both p12 and p34 are present, (middle) p34 only and (bottom) asymmetric configuration – p32 and p34

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Fig. 6.2 Electric field measurements in the solar wind by Cluster 1. The two upper panels show spectra of Ex before and after wake correction. The bottom panel shows raw (blue) and corrected (green) data from p12. Here and in the other figures P12 and P34 are given in units of electric field, i.e. the measured potential difference divided by the boom length

on each probe pair (see blue curve on the bottom panel in Fig. 6.2). In the despun electric field data this shows up as a negative spike in the sunward component, Ex, four times per spin. The resulting spectrum of the electric field (top panel in Fig. 6.2) has a strong signal at 4x the spin frequency (1 Hz) and multiples thereof. An algorithm has been developed to correct for the solar wind wake in the electric field data before submission to the CAA [4]. While doing a good job (results of the correction shown in middle and bottom panels in Fig. 6.2), the algorithm is not always perfect, so the problem with solar wind wake should be kept in mind as soon as spikes at four times per spin period (signal at 1 Hz) are encountered in the data.

6.5.4 Cold Ion Drift Wakes In the low-density plasma encountered for example in the tail lobes, above the polar caps and in the low latitude dayside magnetosphere the spacecraft potential is

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Fig. 6.3 Electric field measurements in the polar cap by Cluster 3. The middle panels show Ex and Ey measured by EFW (blue) and EDI (black). Large deviations in Ex are caused by a wake. The upper panel shows 4 spin periods of non-sinusoidal raw p34 data inside the wake region. The bottom panel shows the spacecraft potential. ASPOC is turned on at 04:24 UT

usually of the order of several tens of volts. A cold ion population flowing in such plasma environments will see effectively much thicker booms (several meters instead of a few mm), creating a large negatively charged wake behind the booms in the direction of flow [2, 3]. Figure 6.3 shows an example of such a wake, defined by a large deviation of Ex measured by the EFW and EDI. When ASPOC is operating, the spacecraft potential is kept at a much lower value and the problem of wakes due to cold ion drift is much less severe. In comparison to the solar wind wake the ion drift wake is broader and more diffuse. For a relatively small wake the raw data are non-sinusoidal (see top panel in Fig. 6.3). For large wake they can become sinusoidal again and look very similar to those created by a real ambient electric field. The CAA production software attempts to detect such ion wakes by looking at a combination of parameters, such as spacecraft potential, magnetic field direction, and the relation between different electric field components. For small magnetic field elevations (B direction is within 15ı from the spin plane) we check for the ratio between the components of E along the projection of B into the spin plane and perpendicular to it. For larger elevations we look at the ratio between the measured

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(spin plane) and unmeasured (perpendicular to the spin plane) components of E? , where E? is computed under assumption of zero parallel electric field, E B D 0. Higher ratios indicate a higher probability of the wake being present in the data. At present there is no algorithm to correct the data, and the bad intervals are removed from Level 2 and Level 3 data. Since it is sometimes difficult to discern between these wakes and a real electric field, analysis of the electric field should be done with caution in regions with possible cold ion drifts.

6.5.5 Plasmasphere

Raw p34 [mV/m]

During comparisons of electric field measurements made by EFW and EDI in the inner magnetosphere, it was found that EFW sometimes measures a spurious field of the order of 1–2 mV/m, mostly in the sunward direction (Fig. 6.4, see also Figure 1c in Puhl-Quinn et al. [8]). The raw data signal is often non-

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corotation −0.5 −1 −1.5

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Fig. 6.4 Electric field measurements in the plasmasphere by Cluster 1. The middle panels show Ex and Ey in ISR2 measured by EFW (blue) and EDI (black) as well as the co-rotation electric field (red). The upper panel shows 4 spin periods of non-sinusoidal raw p34 data. The bottom panel shows the spacecraft potential

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sinusoidal (top panel). This problem is not quantitatively understood, but apparently depends on simultaneously acting phenomena: (a) the dense plasmaspheric plasma can sometimes be so high as to give a random electron current to the probes almost as large as the applied bias current, driving the probe away from its vacuum potential with respect to the plasma; (b) the wake created by the spacecraft makes the random current and the resulting error dependent on the spin phase and hence gives an apparent DC field in a non-spinning reference frame; and (c) small differences in probe surfaces and bias circuitry will make this effect slightly different between the probes, further complicating the result. A first principles error treatment is therefore complex. Nevertheless, an empirical algorithm has been developed to detect the bad data. The algorithm uses a comparison between the measured electric field and the expected field if the ambient plasma were to co-rotate with Earth, and is applied only in regions of high density as indicated by the spacecraft potential (Sc Pot > 1:5 V). The problematic intervals are removed in the CAA data. Users studying the electric field in the inner magnetosphere should be aware of this problem, since the detection of bad data is not always perfect.

6.5.6 WHISPER Operations The WHISPER instrument regularly (often at a repetition period of 52 or 104 s in the normal mode) emits waves of certain frequencies to detect resonances in the ambient plasma. These active soundings are seen in the EFW data (the vertical stripes in the spectra in Fig. 6.2 are for example cause by WHISPER pulses) and are removed automatically in the CAA data by testing for a “sounder active” flag in the telemetry. There are some residual effects after removing the active sounding periods, mainly seen as small spikes in the Level 3 potential data (for details see appendix 5 in Lindqvist and Khotyaintsev [6].

6.5.7 ASPOC Operations The ASPOC instrument attempts to keep the spacecraft potential at a low value, primarily to enable low-energy ion and electron measurements by the particle instruments. In the absence of ASPOC the spacecraft potential often reaches several tens of V in the low-density plasmas encountered by Cluster. With ASPOC operating, the spacecraft potential is brought down to the order of 5–8 V. An example of ASPOC turning on is shown in the bottom panel of Fig. 6.3. As already mentioned, a positive side-effect of this is that the electric field measurements are most often improved since the wake effects associated with large spacecraft potentials in the polar cap are drastically reduced. However, while ASPOC alleviates spacecraft cold plasma wakes, there are also cases when the EFW data are adversely affected by

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ASPOC. First, with ASPOC on, the sunward offset in the magnetosphere is more variable than with ASPOC off. This is not yet understood. Second, with ASPOC on, the noise level sometimes increases significantly at low frequencies. As ASPOC never has been operational on all four s/c, a general advice is that when using EFW data from a s/c with ASPOC on, always look out for ASPOC-related effects on the EFW data by comparing to the measurements from a nearby Cluster s/c with ASPOC off. The spacecraft potential is often used as a proxy for ambient plasma density variations [7]. The data quantity in the CAA is the probe potential measured with respect to the spacecraft potential, which is most often a negative quantity. More negative probe potential corresponds to more positive spacecraft potential which also usually corresponds to lower ambient plasma density. Though the conversion of the spacecraft potential to density can be used at reduced accuracy also when ASPOC is on [9], it works best when ASPOC is off and the spacecraft potential is allowed to float freely. Any use of the spacecraft potential to determine plasma density must take into account whether ASPOC was operating or not. ASPOC is not operational on C1.

6.5.8 EDI Operations EDI measures the ambient electric field by emitting a beam of electrons and detecting the drift step as the electrons gyrate around the ambient magnetic field. The emitted beam current contributes to increasing the spacecraft potential, particularly in a low density plasma. During some periods in the beginning of the mission, the emitted EDI beam current was larger than expected, in particular on C2, so there is a tendency for the spacecraft potential to be larger than on the other spacecraft. It also affects the EFW electric field measurements in that there is a larger risk of saturating the measurements, which happens when the spacecraft potential reaches 70 V. However, after April, 2004, the EDI guns on C2 were turned off in favor of running the instrument in an alternative, “ambient” mode and they no longer cause problems.

6.6 Summary We presented a summary of EFW products in the CAA. We stress that a spin-plane oriented coordinate system (for example ISR2) is best suited for scientific studies involving the electric field. The uncertainty of the electric field measurement is generally less than the greater of 1 mV/m or 10% of the measured value. Accuracies better than 1 mV/m can be achieved by detailed analysis of calibration factors and errors in specific events. We have also listed the most important caveats a user of the electric field data must be aware of.

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References 1. Cully C. M., R. E. Ergun, and A. I. Eriksson, Electrostatic structure around spacecraft in tenuous plasmas, J. Geophys. Res. 112, A09211 (2007). doi:10.1029/2007JA012269 2. Engwall, E., A. I. Eriksson, and J. Forest, Wake formation behind positively charged spacecraft in flowing tenuous plasmas, Phys. Plasmas 13, 062904 (2006). doi: 10.1063/1.2199207 3. Eriksson, A. I., M. André, B. Klecker, H. Laakso, P.-A. Lindqvist, F. Mozer, G. Paschmann, A. Pedersen, J. Quinn, R. Torbert, K. Torkar, and H. Vaith, Electric field measurements on Cluster: comparing the double-probe and electron drift techniques, Ann. Geophys. 24, 275–289 (2006) 4. Eriksson, A. I., Y. Khotyaintsev, and P.-A. Lindqvist, Spacecraft wakes in the solar wind, In Proceedings of the 10th Spacecraft Charging Technology Conference (SCTC-10), (2007) URL: http://www.space.irfu.se/aie/publ/Eriksson2007b.pdf ˚ en, F. 5. Gustafsson, G., R. Boström, B. Holback, G. Holmgren, A. Lundgren, K. Stasiewicz, L. Ahl´ S. Mozer, D. Pankow, P. Harvey, P. Berg, R. Ulrich, A. Pedersen, R. Schmidt, A. Butler, A. W. C. Fransen, D. Klinge, M. Thomsen, C.-G. Fälthammar, P.-A. Lindqvist, S. Christenson, J. Holtet, B. Lybekk, T. A. Sten, P. Tanskanen, K. Lappalainen, and J. Wygant, The Electric Field and Wave Experiment for the Cluster Mission, Space Sci. Rev. 79, 137–156 (1997) 6. Lindqvist, P.-A. and Y. Khotyaintsev, Cluster Active Archive: Interface control document for EFW, ESA document CAA-EFW-ICD-0001 (2007), URL : http://caa.estec.esa.int/caa/ instr doc.xml 7. Pedersen, A., B. Lybekk, M. André, A. Eriksson, A. Masson, F. S. Mozer, P.-A. Lindqvist, P. M. E. Décréau, I. Dandouras, J.-A. Sauvaud, A. Fazakerley, M. Taylor, G. Paschmann, K. R. Svenes, K. Torkar, and E. Whipple, Electron density estimations derived from spacecraft potential measurements on Cluster in tenuous plasma regions, J. Geophys. Res. 113, A07S33 (2008). doi: 10.1029/2007JA012636 8. Puhl-Quinn, P. A., H. Matsui, V. K. Jordanova, Y. Khotyaintsev, and P.-A. Lindqvist, An effort to derive a convection electric field model in the inner-magnetosphere: Merging Cluster EDI and EFW data, J. Atmosph. Solar-Terr. Phys., 70, 564–573 (2007). doi: 10.1016/ j.jastp.2007.08.069 9. Torkar, K., A.I. Eriksson, P.-A. Lindqvist, and W. Steiger, Long-term study of active spacecraft potential control, IEEE Trans Plasma Science, 70, 2294–2300 (2008)

Chapter 7

FGM Data Products in the CAA J.M. Gloag, E.A. Lucek, L.-N. Alconcel, A. Balogh, P. Brown, C.M. Carr, C.N. Dunford, T. Oddy, and J. Soucek

Abstract Set out in this paper is a description of the magnetic field and supporting data products that the FGM team have generated and submitted to the Cluster Active Archive. A significant amount of effort has been put into the calibration and validation of the magnetic field data products and details of the calibration techniques used to produce these data are given here. The quality control tools used to validate the extensive magnetometer dataset and the quality indicators used to label the data itself (namely the caveat and accuracy) files are described. A summary of overall magnetometer calibration status, accuracy level and conclusions from the analysis work undertaken so far is also included.

7.1 FGM Instrument Description The FGM instrument consists of two three-axis fluxgate magnetometer (FGM) sensors located on a radial boom and an onboard data processing unit. The outboard sensor (OB) is located on the end of a 5.2 m boom and the inboard sensor is located 1.5 m in from the end of the boom. Each of the four Cluster spacecraft carries an identical FGM instrument and a full description of the hardware can be found in Balogh et al. [1, 2]. In flight either sensor can be designated as the primary sensor for acquiring the main data stream of the magnetic field vectors and since the J.M. Gloag, E.A. Lucek (), L.-N. Alconcel, P. Brown, C.M. Carr, C.N. Dunford, and T. Oddy Space and Atmospheric Physics, The Blackett Laboratory, Imperial College, London SW7 2BW, UK e-mail: [email protected] A. Balogh Space and Atmospheric Physics, The Blackett Laboratory, Imperial College, London SW7 2BW, UK and International Space Science Institute (ISSI), Hallerstrasse 6, 3012 Bern, Switzerland J. Soucek Department of Space Physics, Institute of Atmospheric Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic


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J.M. Gloag et al. Table 7.1 FGM operating ranges Range number Range (nT) 2 64 to C63:97 3 256 to C255:87 4 1;024 to C1;023:5 5 4;096 to C4;094 7 65;536 to C65;504

Resolution (nT) 7:8 103 3:1 103 0.125 0.5 8

beginning of nominal operations in 2001 the OB sensor has been set as primary on all four spacecraft. The instrument is designed to be highly failure-tolerant through a full redundancy of all its functions. The wide range of magnetic field values to be sampled across the different regions encountered in the Cluster orbits necessitates the use of instrument ranging in order to prevent saturation of the fluxgates during perigee pass while at the same time providing high resolution in the solar wind where the ambient field is typically a few nT. The sensors measure the three components of the field in seven ranges, although only four of these (numbered 2–5) are used on Cluster, with full scales and corresponding digital resolutions as shown in Table 7.1. Another range (range 7) was used only for ground testing. The instrument data processing unit automatically switches the ranges by continually monitoring each component of the measured magnetic field vector. There are two telemetry modes in common use with a rate derived from the instrument raw sample rate of 201.75 vectors/s. In normal mode the data are digitally filtered and decimated down to 22.416 vectors/s and in burst mode the data are filtered and decimated to 67.249 vectors/s. In both cases the digital filter is an FIR (Finite Impulse Response) filter derived from a Gaussian shaped impulse response. The fluxgate sensors are most sensitive in the range (0–10) Hz. The signal chain from the sensor acquisition to the telemetered data stream has two filter stages – an anti-aliasing analogue filter on the output of the raw sensor voltage and the DPU implemented digital filter(s) described above (See also Figures 5 and 6 in Balogh [2]). The following section of this paper introduces the challenges of calibrating the magnetometer data. After an introduction and overview of the in-flight calibration procedure there are sections which give an introduction and useful practical insights into the implementation of the different calibration analyses required to produce the highest quality FGM data. Section 7.3 introduces FGM data products which have been submitted to the CAA, sets out the data production procedure and finally describes the quality control procedure for the FGM data products.

7.2 The FGM Calibration Procedure for CAA Data Products The calibration problem for a fluxgate magnetometer can be most clearly expressed in terms of the calibration equation. This is shown in Eq. 7.1 to relate the magnetic

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field in a calibrated orthogonal coordinate system in nT to the magnetic field in the fluxgate sensor coordinate system in engineering units. 0

1 0 10 1 0 1 BS1 Bx G1 cos 1 G1 sin 1 cos 1 G1 sin 1 sin 1 O1 @ BS2 A D @ G2 cos 2 G2 sin 2 cos 2 G2 sin 2 sin 2 A @ By A C @ O2 A BS3 G3 cos 3 G3 sin 3 cos 3 G3 sin 3 sin 3 Bz O3 (7.1) There are three sets of physical calibration parameters in the calibration equation. There are the sensor aligned offsets O1 , O2 , O3 which alter the overall level of the magnetic field, the gains G1 , G2 , G3 which scale the field and the angles ™1 , ™2 , ™3 , ®1 , ®2 , ®3 which transform from the almost orthogonal sensor coordinate system to an exactly orthogonal coordinate system. The subscripts s1, s2, s3 refer to the sensor coordinate system and the subscripts x, y, z refer to an orthogonal coordinate system. The equation has been written so that the s1 direction is in the spin axis sensor direction which is consistent with FGM on Cluster and the x direction is in precisely the spin axis direction. The aim is to determine values for these 12 calibration parameters. However there is no single way to solve this calibration equation and in reality several different analysis methods are employed to gain as much information about the 12 calibration parameters as possible. The type of analysis that can be done depends on details of a particular spacecraft mission such as whether it is a spinning spacecraft or three-axis stabilised and what type of space plasma regions are encountered. In addition some of the ground calibration values are used as input which can provide a starting point for some of the analysis. The approach taken for the calibration of Cluster FGM for the CAA is to start each analysis period with a well defined starting point and work with the physical calibration parameters as much as possible when performing the calibration analyses in order to make the results at each stage as transparent as possible. What are meant here by physical calibration parameters are the sensor offsets gains and misalignment angles. Each of the four instrument ranges used during Cluster FGM flight operations have a different set of calibration parameters, which means that for any particular analysis period there are 48 calibration parameters (i.e. 4 ranges 12 parameters for each range) to be determined. As a general guide to the physical calibration parameters it can be noted that the sensor offsets tend to vary over the shortest timescales. It is possible to see very small changes in offsets over times scales as short as minutes or hours but the more significant changes tend to be seen over weeks or months. As the offsets only change the overall level of the magnetic field, they tend to be more important in the lower instrument ranges where the magnetic field is lower. The gains and misalignment angles can be considered together as generally they change by much smaller amounts over longer time scales of months. One notable exception to this is when the spacecraft go through eclipses and the sudden changes in temperature can cause gains and misalignment angles to change significantly over the period of minutes and hours. Both gains and angles tend to be more important at the higher end of ranges and in the higher ranges as they are both multiplying factors to the field.

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7.2.1 Overview of the Calibration Procedure Figure 7.1 shows an overview of the CAA calibration procedure. The central calibration method is the Fourier analysis technique, based on Kepko et al. [4]. This technique is applicable on Cluster as the spacecraft are spin stabilised and it is used to calculate the bulk of the calibration parameters. The range 2 spin axis offset is required as an input to the Fourier analysis which means this needs to be determined first. During the solar wind season the range 2 spin axis offset can be determined using the solar wind analysis and during the tail season a linear interpolation is made for the correction to the spin axis to the next solar wind season. It is possible to use the EDI (Electron Drift Instrument, Paschmann et al. [7]) data to monitor the magnetic field magnitude and make sure that no large deviations from the interpolated spin axis offset occur during the tail season. After the Fourier analysis has been performed there are still a number of calibration parameters that have not been estimated. Due to a number of these parameters being incorrect at this stage it may be possible to observe jumps in the magnetic field at instrument range changes. It is possible to use the measurement of these jumps at range changes to refine a number of calibration parameters. Under very specific conditions (see Section 7.2.5) it is possible to apply an inter-spacecraft calibration analysis to the data in order to determine a further set of parameters but it is very rarely the case that the correct conditions exist. The standard calibration files produced to calibrate the data for submission to the CAA are valid for the period of an orbit from perigee to perigee. These calibration files have had input from the solar wind analysis, Fourier analysis and range change analysis and are produced for every orbit of data submitted to the CAA. A small number of files have also had the results of inter-spacecraft

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Fig. 7.1 A diagram illustrating an overview of the calibration procedure used to generate the calibration parameters that are applied to the FGM data products submitted to the CAA

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calibration analysis incorporated into the parameters. It is possible for some calibration parameters to change on shorter timescales than an orbit which results in small residual observable signals in the calibrated data. The final calibration analysis is designed to produce a refinement to the orbit calibration and take account of the short timescale changes in a particular set of calibration parameters. Due to the intensity of processing and validation required to produce these calibration refinement parameters, only a subset of prioritised data periods are being considered for this analysis, and to date no FGM data within the CAA have calibrated using this method. Therefore we do not describe it in detail here. In the following sections an outline of each of the other calibration techniques is given. These descriptions do not aim to rigorously define the basis of each technique but instead the aim is to give an insight into the challenges of implementing these analyses in practice.

7.2.2 The Solar Wind Analysis The determination of offsets for non-spinning axes is generally considered to be one of the more challenging calibration tasks. However if several hours of solar wind data are available with the physical properties described below then it is possible to obtain corrections to these type of offsets to very high accuracy. The general idea is to exploit a particular natural property of the solar wind as done by Hedgecock [3], for example. The solar wind contains short period fluctuations which are predominantly rotational in nature. These fluctuations are therefore observed as changes in field direction. This means that measurements made in any particular non-spinning axis being considered should have on average no correlation with the measured magnetic field magnitude. However if an offset exists on a non-spinning axis then measurements of the magnetic field on this axis will have a correlation with the magnetic field magnitude. The offset on this axis is then estimated by determining a field value that when removed from the magnetic field on the axis under consideration results in a zero correlation between this corrected field and the magnetic field magnitude. In reality compressive fluctuations are also observed in the solar wind to a certain extent and the key to applying this calibration method successfully and accurately is in the selection of data periods to be used in the calibration analysis. The implementation of the solar wind calibration analysis used in the calibration procedure for producing Cluster FGM data for the CAA was originally developed by FGM CoIs at UCLA (H.K. Schwarzl, K. Khurana, M. Kivelson, 2005, private communication) who have also collaborated with us on its implementation at Imperial College. The data selection scheme is applied to data for an analysis period which have been split into bins of a fixed width. Each bin is also overlapped by a fixed time period. The length of analysis period, bin widths and overlap periods are discussed in the next paragraph. The data in the non-spinning axis being considered for calibration first has an artificial positive offset applied to it and the correlation coefficient between this field and the magnetic field magnitude is calculated for each bin. The data in

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the same axis then has the same artificial offset applied in the negative direction and the correlation coefficient calculated for each bin. In order for this method to work most effectively it is important that the artificial offset is greater than the offset correction being calculated. This means that there can be some trial and error involved in deciding on what value to give this artificial offset. The data selection parameters can then be calculated by taking the absolute value of the difference between the two correlation coefficients for each bin. The greater the value of the data selection parameter, the more Alfvénic the fluctuations are in that particular data bin and the more suitable the data are for use in the solar wind calibration analysis. The data selection parameters are then put into descending order and the bins that fall in the top 75th, 80th, 85th, 90th and 95th percentile boundaries are taken forward as the five sets of bins to be used in the calibration analysis. The procedure is applied to data from each of the four spacecraft independently. The period of time used for a particular analysis is usually 2 weeks but can be 1 month if less solar wind data are available. The analysis is normally done for three sets of bin widths and overlaps and then all the calibration results considered together to decide what correction to the spin axis offset is most suitable. The following combinations of bin width and overlap are used: (3,600, 200 s); (900, 50 s); (200, 20 s). The solar wind analysis is an iterative process and the input data to the analysis is calibrated using calibration from an orbit which is immediately before the analysis period being considered. This means that the analysis data is in an orthogonalised coordinate system with one axis precisely in the spin axis direction. The spin axis offset corrections are therefore also in this orthogonalised coordinate system. The spin axis offset corrections for the first iteration are generated by taking the median value of the corrections determined in each of the five percentile groups of bins containing the top 75th, 80th, 85th, 90th and 95th percentile bins from the data selection analysis. The final offset correction for this iteration is then calculated by taking the mean of these five median values. The next iteration then repeats the process using data which has been modified using the offset correction from the present iteration. Usually a stable result is established in three to five iterations. As stated already, this final offset correction is in an orthogonalised coordinate system. However this value should then be applied as a correction to the input sensor offset so must be transformed into the sensor coordinate system in order to do this. It is this corrected sensor offset which is required as an input to the Fourier analysis calibration. The results generated using different data bin widths generally give slightly different results and occasionally, if there is particularly little data for instance, the longest bin widths may not give good results. In order to check that the best spin axis offset corrections have been chosen the data are visually validated at this stage. The four spacecraft data are plotted together with the chosen spin axis offset corrections applied. It is expected that in the solar wind the four spacecraft data will lie on top of each other. There is always a level of natural variation in each spacecraft data but on average and particularly when the data are quiet it should not be possible to observe a significant systematic difference in one or more spacecraft spin axis data. If this is observed the use of a different spin axis offset correction should be considered for the affected spacecraft.

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Once the standard solar wind calibration has been performed successfully it is possible to further refine the spin axis offset corrections by considering the four spacecraft data together. A set of equations can be written which relate differences in the spin axis field between every combination of spacecraft to the refinements in spin axis offsets for each spacecraft. Singular value decomposition can be used to solve this set of equations for the refinements to the spin axis offsets for each spacecraft. In practice it is found that this technique can only be used rarely because exceptionally quiet solar wind data are required. It is important to visually identify the systematic small differences between the four spacecraft field in smooth field regions and then confirm that the results of this refinement analysis are consistent with these differences. This ensures that the analysis is determining refinements to the spin axis offsets and is not simply producing a measure of fluctuations in the field between spacecraft.

7.2.3 The Fourier Analysis Technique The Fourier calibration analysis [4] is central to the calibration procedure and based on the fact that a number of calibration parameters, if incorrect can produce spin signals in the despun magnetic field data. If the calibration Eq. 7.1 is linearised, has the despin matrix applied to it and then the Fourier transform applied to it as described in Kepko et al. [4], it is found that a set of the calibration parameters are directly related to first and second harmonic spin signals in the despun data. Measurement of these signals in the data can therefore be used to calculate estimates to a set of calibration parameters. The first harmonic signal in the spin axis magnetic field can be used to estimate the spin axis elevation and azimuthal angles. The first harmonic signal in the spin plane magnetic field can be used to estimate the two spin plane offsets and two spin plane elevation angles. Finally the second harmonic signal in the spin plane magnetic field component can be used to estimate the ratio of the spin plane gains and the relative spin plane azimuthal angles. The total, final estimates of the calibration parameters may not be small but the results come from a linearised set of equations. Therefore the final set of calibration parameters are made by using an iterative approach where at each iteration the new estimates of the calibration parameters are applied to the data to be used in the next iteration. For each iteration the calibration parameters are estimated using least squares analysis applied to the equations that come from the manipulations made to the calibration equation described above. Data selection is an important step to ensure the best results are obtained. The data are split into approximately two minute bins and each instrument range is calibrated separately. Normal mode FGM data at 22 Hz time resolution is used. It is essential that the data bins are chopped to size so that their length is an exact integer number of the spacecraft spin periods. The best data bins for use in the analysis are those which have generally low levels of fluctuations, field which is reasonably constant over the bin width but that also have good signal to noise on the spin signals

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that are to be removed. However it is also important that there is a good spread of magnetic field magnitude and direction over the full set of bins so a compromise on these conditions is required. Three tests are made on the data bins in order to choose the best ones for analysis. The first calculates the median power spectral density between 0.1 and 1 Hz and the data that exhibit the highest level of fluctuations are removed. The second test calculates the standard deviations for each of the remaining data bins and these statistics used to remove the data bins with the most change in field over the bin width. The third test uses the calculation of the signal to noise ratio of the first harmonic signal to find the intervals with the clearest spin signals. Each of these tests are carried out on the spin axis and spin plane data bins independently. Fourier analysis is applied to data from a full orbit defined from perigee to perigee. Data quality for calibration varies from orbit to orbit in terms of coverage and data characteristics. For instance if a large amount of data in a particular range is sheath data which contains high levels of fluctuations over a wide band of frequencies it can be difficult to measure the spin signal associated with certain calibration parameters. Some calibration parameters change over shorter time scales than others. Generally speaking, the angles and gains tend to change over a longer timescale than the offsets. Under normal circumstances offsets can change by small amounts over the period of an orbit but angles tend to be reasonably constant for many orbits. However during events such as eclipses when the temperature drops and then rises significantly all the calibration parameters can change on a timescale significantly shorter than an orbit. In these circumstances the analysis results is the determination of average calibration parameters over the period of the orbit and it is sometimes clear from the least squares fitting routine that there are multiple solutions which correspond to different parts of the orbit. The starting point for this Fourier analysis is to use a calibration file which has the range 2 spin axis offset predetermined using the solar wind analysis for instance and the range 3–5 spin axis offsets input from a previous orbit within 1 month. The spin plane offsets are set to zeros and the gains are set to the ground determined values. Finally the angles are set to 0ı or 90ı in such a way as to align the three sensor axes in an orthogonal set. The initial results are evaluated for calibration quality. The first check is to create a table of all the spin axis angles that have been determined for each range. These angles should only change relatively slowly through time which means that if large variations are seen on any particular orbits it may be the case that the data quality was not sufficient to obtain good results. This can often be the case in range 2 as there tend to be larger levels of fluctuations in this data and the angle errors don’t produce as big a signal in lower field magnitudes. In practise the best orbits for calibration within a month are identified and the spin axis angles used from these in the orbits where the data are not as good for calibration. Secondly a calibration report is automatically produced for each orbit and spacecraft containing information about the three data selection tests and plots of the least square results from the first iteration. It is also recorded here if there are not enough data intervals to perform the analysis on a particular range. Finally spectrograms are generated for the spin axis field and spin plane magnitude field

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using the calibration parameters calculated at this stage. All this information together can be used to decide what calibration parameters may need to be substituted into one orbit calibration from another orbit where the data were more suitable for performing the analysis. In our implementation of the Fourier analysis technique, a first analysis is performed on a months worth of orbits. The set of spin axis angles for all orbits and ranges are used to determine which orbits are the best for calibration purposes and spin axis angles substituted from these best orbits to those where the analysis was less successful. If any orbits have too low data coverage in a particular range then the full set of calibration for that range is substituted from an adjacent good orbit. The spectrograms are then rerun with the updated calibration and then these are compared to the original spectrograms to make sure an improvement has been made. There may be more than one possibility for updating certain calibration parameters. All possible improvements are tried and then the calibration that produces the best spectrogram is chosen to be the calibration for that orbit. If a particular problem still remains with the calibration for a certain orbit then the automatically produced calibration report described previously can be used to try and establish the problem with the orbit. One point to note is that there is a spacecraft generated field on spacecraft 1 which manifests as a small first and second harmonic spin signal in the spin axis field. This cannot be removed with this calibration analysis but it has been found that the major part of the signal is in the imaginary component of the first harmonic spin signal so the real part is used to estimate the spin axis angles successfully. It should also be noted that the spin axis angles can be more precisely determined in the higher ranges because the angles produce a bigger signal in higher magnetic fields and also because the data tends to be quieter in the higher ranges. This means that the angles from the higher ranges can be used as guidance for the lower ranges if the data in the lower ranges are not good quality for calibration. It is possible for the calibration to vary within an orbit. The calibration from this analysis is effectively an average calibration over the period of an orbit and the calibration refinement method is required to remove the residual spin tone caused by these short timescale variations of calibration parameters. Figure 7.2 presents example spectrograms for a complete orbit of spacecraft 2 data from February 2006. Figure 7.2a is the spectra prior to Fourier analysis and Fig. 7.2b is the spectra produced following the analysis. The red lines and white lines overlaid on the plots mark out demarcations of instrument range switches with the long middle period corresponding to range 2 data. Looking at the period immediately following the 02/08 time marker in Fig. 7.2a where the instrument range switches from 2 to 3 it can be seen that there is significant increase in power at 0.25 and 0.5 Hz indicating that the initial range 3 calibration is incorrect. Following the Fourier analysis this power burst is identified as unnatural and corrected by the re-calculated calibration parameters.

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7.2.4 The Range Change Analysis Following the range 2 spin axis offset determination and the application of the Fourier analysis method there are still a number of calibration parameters which may not be correct. If the natural fluctuations in the data are small enough it may be possible to see small jumps in the magnetic field across instrument range changes when the calibration at this stage is used. These jumps are an indication that some calibration parameters are incorrect as the data should be continuous across the range changes. A method was developed by FGM CoIs at UCLA (H.K. Schwarzl, K. Khurana, M. Kivelson, 2005, private communication) to use these jumps at range changes in order to correct a subset of calibration parameters. Through collaboration with these FGM CoIs at UCLA this range change calibration analysis has been implemented at Imperial College. The analysis is performed in the spin plane and the spin axis magnetic field separately. In the spin plane a jump in the field at a range change can be ascribed to a gain error and an error in azimuthal angle. In the spin axis a jump in the field at a range change can be accounted for by a gain error and an offset error. A set of equations can be derived which relate these calibration parameters to the jumps in the field observed at the range changes. In order to cause the smallest change to the overall field the gain corrections are applied to the lower range in both the spin axis and spin plane and the other parameters are applied to the upper range, the offset in the case of the spin axis and the azimuthal angle in the case of the spin plane. The implementation of this range change analysis involves creating analysis tools which are used to plot the data close to range changes, select which range changes are most suitable for the analysis and measure the jump in each component of the

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magnetic field. The period of data used for analysis is generally 2 weeks or 1 month, which usually has enough suitable range changes to give good results although occasionally slightly longer periods of time need to be considered. The calibration of changes between ranges 2 and 3 is usually the most difficult because the data often have a significant amount of natural signal compared with the size of the jumps being measured. Ideally the data either side of the range change should be smooth and the jump in the field to be measured should be clear. The data tend to be smoother close to range changes between ranges 3 and 4 which means that more jumps in the field can be used and generally it is possible to do the analysis with 2 weeks of data. The range 2 and 3 calibration is done first, the data reprocessed with the new calibration and then the range 3–4 calibration done. When all the ranges have been calibrated the data are reprocessed again and both the range 2–3 and 3–4 changes are compared with the original data to make sure that the tweaks to the calibration have been successful. This is an important step because when correcting the range 3 and 4 calibration small jumps may be reintroduced at the range 2 and 3 changes. One important point to note is that when doing the spin axis calibration it is important to make sure that the spin axis has a good range of magnetic field values. This is because the calculation of the calibration corrections involves a linear fit so the larger the range of field values, the more accurate the gradient and offset of this fit. An example of time series data from spacecraft 2 before and after the range change analysis is shown in Fig. 7.3. The upper plots show a range change from 4 to 5 for each vector component Bx, By and Bz. One can see there is a discontinuity where the range change occurs due to a calibration error. The lower plots display the same range change plotted following re-calibration of the time series using the parameter modifications determined during the analysis.

7.2.5 Inter-Spacecraft Calibration It is possible to use the four spacecraft data together to perform inter-spacecraft calibration and a method for doing this was developed by Khurana et al. [5]. The method demonstrates that if the assumption can be made for a period of data that the Curl of the magnetic field vector should be zero and it is taken that the divergence of the magnetic field is zero then it is possible to estimate a correction to a set of calibration parameters. This is done by minimising the Curl and divergence of the magnetic field in regions of magnetic field where the current density and therefore Curl of the magnetic field is expected to be zero. Using this technique it is possible to calculate a set of misorientation angles, a set of spin axis gain corrections and a set of spin axis offset corrections for three spacecraft relative to a pre-chosen mother spacecraft. This method has been implemented by FGM CoIs at UCLA (H.K. Schwarzl, K. Khurana, M. Kivelson, 2005, private communication) and a collaboration with these CoIs has lead to an implementation of this technique at Imperial College. Data selection is of prime importance when implementing this calibration technique and the initial task is to choose general data periods when the current density is

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Fig. 7.3 A typical figure generated during the range change analysis. The data are from 30th of January 2009. The upper three plots correspond to a range 4–5 jump for each field component utilising the calibration file produced by the Fourier analysis step. The lower panel shows the same jumps after the corrected file has been further modified by the range change analysis. We can see on all three components that the jump offset has been reduced to almost zero and the data are now continuous across the range change

expected to be zero, for example, in the magneto-tail lobe regions. The lobe regions are located by finding the point where the magnetic field in the x-axis of the J2k coordinate system (Geocentric inertial reference frame using the Julian Epoch of Jan. 1, 2000) smoothly moves through zero and by considering the data either side of this point in the magneto-tail. Data is then selected where the Curl of the magnetic field is smooth, the magnetic field in the x-axis of the J2k coordinate system is smooth, the inter-spacecraft distances are less than 4,000 km and the Q-factor [8] for the spacecraft tetrahedral is greater than 2. In practice the most successful results between spacecraft have been obtained in the tail season of 2003 when the inter-spacecraft distances were of the order 100 km. It was also found that more stable results were found when only solving for the spin axis gain corrections and spin axis offset corrections. Generally between 2 weeks and 1 month of data are considered when performing the data selection for the inter-spacecraft calibration analysis. When the minimisation analysis has been performed checks are made to determine if good results have been obtained. The Curl and divergence of the magnetic field are calculated, which should be small, considered and the changes to the calibration parameters made after the last three or four iterations are checked to make sure a

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stable solution has been achieved. A visual check is made to make sure the four spacecraft spin axis field values are close together in the regions selected for the analysis. The inter-spacecraft calibration is rewarding in that it yields corrections to calibration parameters which could otherwise not be estimated.

7.3 The FGM Data Products 7.3.1 Primary Data Products The primary FGM data products consist of magnetic field data products at three different time resolutions. Each of the three data products are processed independently and are calibrated using the same calibration file. Each calibration file is valid for the period of one orbit defined from perigee to perigee. The highest resolution magnetic field data product (Cx CP FGM FULL) contains data which has no time averaging applied. If the instrument is in normal mode the data is at approximately 22 Hz resolution and if it is in burst mode the data is at approximately 67 Hz resolution. The second magnetic field data product (Cx CP FGM 5VPS) is averaged to a time resolution of 5 vectors/s and the third magnetic field data product (Cx CP FGM SPIN) is averaged over one spacecraft spin where the spin phase for averaging is the same as that used for the Prime Parameter data (26:367ı). Each of the three primary data products have the same format below the CEF-2 (Cluster Exchange Format, version 2) header which consists of the following columns of data: ISO time; half time interval/s; magnetic field vector (3 components)/nT; magnetic field magnitude/nT; spacecraft position (3 components)/km; instrument range; telemetry mode. The magnetic field components and the spacecraft position are in the GSE coordinate system. An example 5 lines of 5 vectors/s data directly below the CEF-2 header for the cluster 4 spacecraft is shown below. DATA_UNTIL = EOF 2003-02-01T07:00:00.100Z,0.1,9.070,-20.395,2.979,22.519,104287.6,63758.5,1468.6,2,22 2003-02-01T07:00:00.300Z,0.1,8.972,-20.451,2.665,22.491,104287.7,63758.4,1468.4,2,22 2003-02-01T07:00:00.500Z,0.1,8.819,-20.501,2.418,22.448,104287.8,63758.4,1468.2,2,22 2003-02-01T07:00:00.700Z,0.1,8.635,-20.526,2.290,22.386,104287.9,63758.4,1468.0,2,22 2003-02-01T07:00:00.900Z,0.1,8.426,-20.608,2.326,22.385,104288.0,63758.3,1467.8,2,22

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7.3.2 Support Data Products There are several support data products produced for the FGM data which give additional information about the magnetic field data products or about the calibration used to generate the data. There are two data products which give information about data gaps in the FGM data. The first product (Cx CQ FGM GAPF) lists the data gaps that are introduced at the processing stage which may be due to times when no data were taken for instance. The second product (Cx CQ FGM VALF) lists time periods where invalid data have been removed at the data validation stage.

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Caveat files (Cx CQ FGM CAVF) are produced for periods of data when the calibration is known to be changing on short timescales near eclipses and for other events when visible effects have been observed in the data. Calibration accuracy files (Cx CQ FGM CALA) contain detailed information on the accuracy of the magnetic field data products and can be used to select periods of data which would be particularly good for a certain type of analysis from an accuracy point of view.

7.3.3 Calibration Files The calibration files (Cx CC FGM CALF) contain the nine elements of the 3 3 calibration matrix and the three offsets for each instrument range which are used to transform the FGM data from uncalibrated data in the sensor coordinate system to calibrated data in an orthogonal coordinate system. Each of the calibration files are valid for the period of one orbit and are produced for each spacecraft for every orbit where magnetic field data products have been submitted to the CAA. There are several different calibration analyses that are used to produce these standard orbit calibration files including the use of inter-spacecraft comparisons and which methods are employed at a particular point in time depends on properties of the data that are available at that time.

7.3.4 The Data Production Procedure There are several steps involved with producing the FGM data products. The first and most time intensive step is to determine calibration parameters for every orbit for which data is submitted to the CAA. The procedure for producing these calibration parameters is described in the next section. The next step is to validate the data which is also a time intensive step and is discussed in detail below. The data are then processed from raw data into calibrated data in the GSE coordinate system. In order to do this processing the calibration files are applied to the data and other auxiliary data are used to transform the data into its final form. Finally the data products are submitted to the CAA. Further information on the production and quality control procedures along with further information about the data products can be found in the FGM ICD (Interface Control Document), the newest version of which can be found in the CAA, Lucek et al. [6].

7.3.5 Quality Control for FGM Data Products Submitted to the CAA The outcome of the calibration procedure is one calibration file for each spacecraft for each orbit. However as already outlined some calibration parameters are

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necessarily derived from periods of data much longer than an orbit, typically of 2 weeks or 1 month. Each calibration method is unable to track changes in calibration parameters that occur on a timescale shorter than the data interval used to estimate the calibration coefficients. If the changes in calibration parameters are large, then the effects will be visible in the final magnetic data product. Therefore FGM calibration analysis does not always result in perfect calibration. The accuracy of the calibration depends on a number of factors including: Data coverage – extensive data gaps can have a strong negative impact on the

calibration. Data characteristics – most corrections to the calibration parameters are small.

Therefore power within the natural signal can make it difficult to identify the correction required to the calibration matrix. Spread of B and jBj within the data – The majority of calibration techniques require measurements over a range of magnetic field magnitudes and directions. A narrow spread in either of these can adversely impact the quality of the calibration. The time over which the calibration is calculated depends on each of these three factors. Poor data coverage might, for example, suggest that using data over a longer period would be helpful. However, all the calibration methods assume that the underlying calibration parameters do not change over the period of data being analysed. If there is a change in calibration parameters during the interval of analysis, then since only a single estimate of the parameters is derived, some part of that period will be less well calibrated. The quality control system for the FGM data products has three parts to it. The first is the validation procedure which is applied to all periods of data which are submitted to the CAA. The validation procedure is based on visual inspection of the 5 vectors/s data product. Semi-automated software searches for possible spikes in the data and these spikes are then visually inspected to determine whether they are invalid data (and therefore removed) or a natural feature. High resolution data may be inspected if the 5 vectors/s data are inconclusive. The start and end times of the periods of invalid data to be removed are recorded using the validation tools and then the data processed to remove these intervals. At this point the validation gap files (VALF) are produced which contain the start and end times for data periods removed at the validation stage. The second aspect of quality control is in the form of caveat files (CAVF). CAVF files are generated for intervals of data when the calibration procedure is compromised, often for one of the reasons listed in the previous section. The signatures of poor calibration at this level are generally either a visible signal at the spacecraft spin frequency, or a spread of magnetic field values between the four spacecraft while they are in a region when we would expect all spacecraft to measure the same average magnetic field. The latter is most commonly seen in the solar wind.

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Within a CAVF file for a particular spacecraft for a particular interval, the signature of poor calibration, and (where possible) the cause are given. Common reasons for caveats are: 1. Spacecraft eclipses, where the temperature change experienced by the instrument during short or particularly long eclipses can often lead to a small but significant change in calibration parameters during that orbit. This leads to a larger than normal residual spin tone in the data that can be identified at the validation stage. 2. Spacecraft manoeuvres can also cause changes in the calibration parameters, leading to a similar signature as in 1. 3. An unexplained spread in sensor spin axis magnetic field data exceeding 0.25 nT is seen between the four spacecraft. This signature can generally only be seen in the solar wind where the magnetic field magnitude is low, and the magnetic field data are very quiet. This can arise if the spin axis offset changes during the 2 weeks or 1 month over which the spin axis offset calibration method is applied. However, poor data coverage might also influence the accuracy with which the spin axis offset can be estimated. 4. Unexplained instances where higher than normal spin tone is observed. These occur occasionally. Finally the third aspect of the quality control are the Calibration Accuracy files (CALA). CALA files give information on the accuracy of the calibration used to process each data interval. Three different categories of calibration accuracy parameters are recorded for users of the data: The first category is a set of parameters that are derived from the solar wind calibration analysis. Recorded here are the median values of the differences in spin axis magnetic field between all combinations of the four Cluster spacecraft. Also recorded are the standard deviations associated with the differences, calculated for each of the spacecraft combinations. The values are calculated over the period of each solar wind analysis, which is either 2 weeks or a month. The idea behind using these parameters is that after the solar wind analysis has been performed independently for each spacecraft it is expected that the spin axis field measurements from the four spacecraft would lie on top of each other when the spacecraft are in the solar wind. The measured differences in spin axis magnetic field between each spacecraft combination therefore indicates how well this calibration has been performed in a particular region or may indicate if the calibration is changing within a certain period. An example of when you might be interested in these parameters is if a study is being done which uses inter-spacecraft comparisons. The median parameters would give an indication of the accuracy of these inter-spacecraft comparisons in low field regions. The second category of calibration parameters are connected with the calibration analysis performed at range changes. The principal used in this method is that the magnetic field should not change as a result of the instrument changing range. Only a subset of range changes can be used to measure this effect, because the power in the science signal needs to be low enough for the small jump in B associated with the error in calibration parameters to be observed. The parameters

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recorded in the files are the residual jump in the magnetic field magnitudes for each spacecraft at both range 2-to-3 and 3-to-4 changes after the calibration has been performed. Only the range changes that are selected in the calibration analysis are used here, as data close to other range changes may contain too much natural signal for it to be possible to measure the accuracy parameters. In addition the residual angle deflection in magnetic field after the calibration analysis has been performed is also recorded for range 2-to-3 and 3-to-4 changes. All of these parameters are an average value taken over the period of a month. These parameters are important if analysis is being performed on data in higher field regions where the fluxgate magnetometer is in a higher instrument range. The parameters give an indication of how successful the range change analysis has been in a particular region and therefore an idea of the accuracy of the magnetic field data in the higher ranges. A user of the data can identify times when range changes occur from the primary data products described in Section 7.3.1. As shown in the sample of data at the end of Section 7.3.1 the second to last column of data is the instrument range so when these numbers change from one sample to the next, a range change has occurred. The third category of calibration accuracy parameters are extracted from the Fourier analysis calibration. They comprise of hourly averaged values of the residual first harmonic signal (spin frequency) to noise ratio in the spin axis and spin plane and the residual second harmonic signal (twice spin frequency) to noise ratio in the spin plane after the calibration has been performed. The residual power spectral density after calibration are also recorded for the corresponding first and second harmonic signal to noise ratios. These parameters demonstrate how well the Fourier analysis calibration has been done for a particular orbit or whether the calibration is changing within an orbit. More generally, these calibration accuracy parameters give an indication of how well a particular orbit is calibrated. Factors which influence how well it is possible to calibrate a particular orbit include the data coverage in each instrument range and also the type and level of physical signal in the data which is often connected with the magnetospheric region being encountered at the time. As the Fourier analysis method is applied to every orbit, the hourly averaged calibration accuracy values described above demonstrate how suitable the data available in a particular orbit is for producing a good set of calibration parameters. In addition to these parameters a single score value is also recorded in the calibration accuracy files for each category. The score values are on a scale of 1–4 (1 being the best) and are based on the long-term distributions of each parameter. A score is assigned for a particular period of time by considering in which quartile of the long-term distribution the parameter falls for that period. For each category of parameters an average score value is determined for a period and rounded to the nearest score value. In this way a single score value for each category is determined for each period of time. This simple scoring system makes it possible to run a rough filter on a proposed set of data periods in order to extract which periods are most suitable for a particular type of analysis.

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Fig. 7.4 Time series plot showing a typical piece of FGM data in the solar wind submitted to the CAA. We can recognise this data set as well calibrated due to the fact the traces lie directly on top of each other in quiet regions together with the absence of spin tone. The four traces correspond to each of the spacecraft using the conventional Cluster colours (C1 Black, C2 Red, C3 Green and C4 Magenta)

An example of a validated FGM time series plot is shown in Fig. 7.4. The panels correspond to , ', Bx, By, Bz, and jBj with all four spacecraft traces displayed in the traditional Cluster colours. The data is taken from a solar wind interval from the same orbit (863) as that of the spectrograms used in Fig. 7.2 although only 47 min of data are plotted in order to show the fine structure within the time series. We can see that in regions where the background field is smooth the four traces lie on top of each other indicating that the data is well calibrated whereas during sudden field changes the spacecraft traces are not overlaid reflecting the fact that different spacecraft do not encounter the discontinuity at the same time.

7.4 Conclusion This paper gives an introduction to the FGM data products submitted to the CAA along with a description of how the data were produced and an outline of the quality control procedures used to ensure the integrity of the data. This is the first time that such a high quality of calibration has been applied across large multi-spacecraft magnetometer datasets and it has so far resulted in an exceptional magnetic field data set in the CAA. The routinely achieved accuracy level for well calibrated science data in instrument ranges 2, 3 and 4 is between 0.1–0.2 nT in regions where jBj < 200 nT and better than 0.4 nT in regions where jBj > 200 nT. Spin tone may be seen in the data

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on occasion. This usually indicates a small residual error in the calibration, typically due to calibration drifts occurring on timescales much shorter than that of a single orbit. The highest case of spin tone occurs during perigee pass during passage through maximum jBj, where it may reach up to 0.4 nT. Where it occurs elsewhere during an orbit it will generally be less than 0.1 nT. If an extreme amount of spin tone (i.e. greater than 1 nT) is observed within a period of interest (a given range), a caveat will be produced along with the data that forewarns the user as to the nature of the excessive spin tone. The presence of spin tone in an FGM time series inevitably means its spectrogram will show residual power at spin (0:25 Hz) and twice spin (0:5 Hz) frequencies. Generally speaking if a particular narrow band signal is seen at either of these frequencies, it is likely that it arises from small calibration errors and is not natural in origin. This derives from the fact that it is not possible to distinguish power between natural signal and calibration error at these frequencies. 2 4 p The instrument noise level above 1 Hz is of the order 1 10 nT =Hz.10pT= Hz/. This may be compared with a digital resolution of 7.8 pT in the highest resolution range 2. Highest resolution data in burst mode are primarily designed for use in time series analysis, for example discontinuity analyses at the bow shock or magnetopause. CAA users wishing to study waves in the frequency range above 10 Hz should note that FGM is a DC instrument, and that filters within the instrument will significantly attenuate wave power above this frequency. It is recommended that data from the STAFF instrument be used to analyse waves in this frequency range. The FGM team does not recommend the use of 67 Hz for spectrograms. If a user of the data at a later date is interested in attempting an improvement to a short period of data of particular interest then the only way to achieve this is to develop a good understanding of the in-flight calibration techniques which are used to produce the calibration files. The detailed sections set out in this paper on the different calibration analyses give a good starting point to gaining this calibration knowledge required. Although the details of specific algorithms will need to be looked up in other sources, the sections in this paper contain valuable practical knowledge on implementing the calibration procedures. Acknowledgments We would like to acknowledge the invaluable assistance of the FGM CoIs and FGM CoI teams who have contributed to the calibration effort. We would also like to thank M. Kivelson, K. Khurana and H.K. Schwarzl for their generosity in helping with the implementation at Imperial College of the calibration methods developed at UCLA.

References 1. Balogh A., M. W. Dunlop, S. W. H. Cowley, D. J. Southwood, J. G. Thomlinson and the Cluster magnetometer team: The Cluster magnetic field investigation, Space Sci. Rev., 79, 65, (1997) 2. Balogh A., C. M. Carr, M. H. Acuna, M. W. Dunlop, T. J. Beek, P. Brown, K.-H. Fornacon, E. Georgescu, K.-H. Glassmeier, J. Harris, G. Musmann, T. Oddy, and K. Schwingenschuh: The Cluster Magnetic Field Investigation: Overview of in-flight performance and initial results, Ann. Geophysicae., 19, 1207–1217 (2001)

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3. Hedgecock, P. C.: A correlation technique for magnetometer zero level determination, Space Sci. Inst., 1, 83–90 (1975) 4. Kepko, E. L., K. K. Khurana, M. G. Kivelson, R. C. Elphic, and C. T. Russell: Accurate determination of magnetic field gradients from four point vector measurements: I. Use of natural constraints on vector data obtained from a single spinning spacecraft, IEEE Transactions on Magnetics, 32, 377–385 (1996) 5. Khurana, K. K., E. L. Kepko, M. G. Kivelson, and R. C. Elphic: Accurate determination of magnetic field gradients from four point vector measurements: II. Use of natural constraints on vector data obtained from four spinning spacecraft, IEEE Transactions on Magnetics, 32, 5193–5205 (1996) 6. Lucek, E. A., J. M. Gloag, A. Balogh, C. Carr, Cluster Active Archive: Interface control document for FGM, http://caa.estec.esa.int/documents/ICD/CAA FGM ICD V40.pdf (2008) 7. Paschmann, G., J.M. Quinn, R.B. Torbert, H. Vaith, C.E. McIlwain, G. Haerendel, O.H. Bauer, T. Bauer, W. Baumjohann, W. Filliius, M. Förster, S. Frey, S.S. Kerr, C.A. Kletzing, P. Puhl-Quinn, and E.C. Whipple, The electron drift instrument on Cluster: overview of first results, Ann. Geophysicae, 19, 1273, (2001) 8. Robert, P., A. Roux, C. C. Harvey, M. W. Dunlop, P. W. Daly, and K.-H. Glassmeier: Tetrahedron Geometric Factors. In: Paschmann G. and P. W. Daly (Eds.) Analysis Methods for Multi-Spacecraft Data, pp. 323–348, ISSI, Bern (1998)

Chapter 8

PEACE Data in the Cluster Active Archive A.N. Fazakerley, A.D. Lahiff, R.J. Wilson, I. Rozum, C. Anekallu, M. West, and H. Bacai

Abstract We describe the data products of the Cluster Plasma Electron and Current Experiment (PEACE) instruments which have been produced for the Cluster Active Archive. This article is intended to introduce the PEACE instruments, the measured data and the data products provided through the CAA. We aim to help the researcher to choose the data products most suited to their needs and to avoid inadvertent misuse of the data.

8.1 Introduction The Plasma Electron and Current Experiment (PEACE) measurements of the thermal electron plasma population enable characterisation of the local plasma – its density, bulk flow, electron temperature – and electron pitch angle data reveal whether the local region is magnetically connected to regions of electron acceleration or lies between magnetic mirrors. PEACE electron data reveals whether electron pitch angle or energy scattering processes are active, for example as waveparticle interactions occur. Good quality moments of the electron distribution may also be used to study the contribution of electrons to currents in key regions (e.g., magnetotail current sheet, auroral regions, reconnection sites). The four spacecraft capability allows determination of the three-dimensional motion of plasma boundaries (which may not always have a corresponding magnetic signature) and probing A.N. Fazakerley (), A.D. Lahiff, I. Rozum, C. Anekallu, and H. Bacai Mullard Space Science Laboratory, University College London, UK e-mail: [email protected] R.J. Wilson Mullard Space Science Laboratory, University College London, UK and Now at Los Alamos National Laboratory, Los Alamos, USA M. West Mullard Space Science Laboratory, University College London, UK and Now at Royal Observatory, Belgium


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of three dimensional structures such as Flux Transfer Events or the magnetotail plasmasheet, where electrons on neighbouring field lines may have had quite different recent histories. The dataset is key to studies of plasma boundary regions (magnetopause, bowshock, cusp etc.) and how mass, momentum and energy are transferred across them. Each Cluster spacecraft carries an identical PEACE instrument, consisting of two sensors, HEEA and LEEA, and a data processing unit, the DPU. Below, we briefly describe a PEACE instrument and how it works, after which we introduce the Cluster Active Archive PEACE data products. Readers may also be interested in the PEACE Science User Guide available at the CAA website, which complements this paper.

8.2 The Cluster PEACE Instruments 8.2.1 Instrument Description The Low Energy Electron Analyser (LEEA) is designed to specialise in coverage of the very lowest electron energies (, 0) and the two other ones are below (i.e., BX < 0).

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Fig. 16.2 Partial view of the “Plot Data” interface when the visual event selection functionality is activated. Magnetic field and electron spectra of THEMIS-B and THAMIS-D are represented here. A plasmoid event has been selected and recorded in the time table THEMIS PLASMO

In the “Conditional Search” interface of AMDA (Fig. 16.2), the user first performs an automated search of the time intervals when the CLUSTER spacecraft encircled the neutral sheet as defined above. He/she edits the following criteria: BX1 BX2 BX3 BX4 > 0 AND min fBX1 ; BX2 ; BX3 ; BX4 g < 0 AND max fBX1 ; BX2 ; BX3 ; BX4 g > 0 AND XGSM1 < 10 He/she applies them to the CLUSTER data during the tail seasons, for example the one of the year 2002 (August to October). To avoid selecting too brief events, the

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Fig. 16.3 Partial view of the “Conditional Search” interface. The criteria edited in the “Search Condition” window corresponds to the use case presented in Section 16.4

filter is applied by computing on the fly 1 minute-averaged FGM data. AMDA then generates a first time table (hereafter TT1) listing all the time-periods when this neutral sheet encirclement condition is fulfilled. In the case of the 2002 tail season, 216 events are found. Starting from this time table TT1, the user can then undertake several possible actions. Some examples: Extraction of sub-database corresponding to CLUSTER neutral sheet

encirclement events. In the “My parameter” interface, the user can formulate additional parameters such as the plasma beta, the total pressure for example. Then, in the “Download Data” interface, he/she can select the parameters of interest for his/her study and then download them in merged files corresponding to the time-intervals recorded in the time-table TT1. So, he/she constitutes a

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Fig. 16.4 Partial view of the “My Time Tables” interface

Fig. 16.5 Illustration of the neutral sheet encirclement by the CLUSTER constellation. The profile of the BX component through the current sheet is shown on the right side of the right panel. BX is positive above the neutral sheet and negative below

sub-database of the CLUSTER neutral sheet encirclement events that he/she can statistically treat off-line with his/her own tools and software. In view of analysing the context of these events, the user can generate a new time table TT2 by extending the time intervals of TT1 and download the corresponding complementary sub-database.

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Extraction of corresponding sub-database of solar wind data. To download

the interplanetary data obtained by ACE, the user can first extend the Time-Table by 60 min and shift it by 45 min, corresponding to a rough averaged time-delay of solar wind propagation. (The on-the-fly computation of the solar wind propagation time-delay is an up-coming functionality of AMDA). Filtering the event collection with additional criteria. As explained in Section 16.3, the “Conditional Search” interface allows to perform successive searches. The user can use this possibility if for instance he/she wants to: (i) Find the events when all the CLUSTER spacecraft were embedded in the central plasma sheet (with a condition on the plasma beta parameter) (ii) Classify the events as a function of their location in the XYGSM plane, the observed flows, the wave activity level, the geomagnetic activity . . . (iii) Find the events when GEOTAIL and/or POLAR were also imbedded in the plasma sheet (with condition on their location and their plasma measurement) in order to perform multi-scale studies These automated searches would generate new time tables which could be thereafter used to constitute new sub-databases or to produce figures via the “Plot Data” interface.

16.5 Conclusion and Perspectives AMDA is a web-based service developed with the aim to help researchers in space physics. AMDA offers functionalities to access and analyse multi-dataset in a transparent fashion and allows perform event search. This tool has already been used in various studies [1–3]. AMDA is in continuous development. Future developments concern new analysis tools, new products, enhancement of interoperability and the creation/management of catalogues. AMDA is evolving in the Virtual Observatory paradigm. It gives a direct access to data from distant databases and includes a connection layer compliant with the SPASE (http://www.spase-group.org/) standards. AMDA produces, manipulates and uses time tables. The time tables can be seen as one of the primary brick to be used for the interoperable exchanges in space physics. This idea encouraged to start a collaboration between databases (AMDA and CAA) on one hand, and generic tools (QSAS and CL) on the other hand. Acknowledgements The authors would like to thank P. Louarn, C. Perry, T. Allen, S.F. Fung and D. Bilitza for helpful discussion and the CDPP User Committee for having tested AMDA.

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References 1. Génot V., E. Budnik, C. Jacquey, I. Dandouras, E. Lucek (2008a), Mirror mode events observed with Cluster in the Earth magnetosheath: statistical study and IMF/solar wind dependence, submitted to Advances in Geosciences (2008) 2. Génot V., E. Budnik, P. Hellinger, T. Passot, G. Belmont, P. Travnicek, P.-L. Sulem, E. Lucek, and I. Dandouras (2009), Mirror structures above and below the linear instability threshold: Cluster observations, fluid model and hybrid simulations, Ann. Geophys., 27, 2, 601–615 3. Louarn P., C. Jacquey, E. Budnik, and V. Genot (2006), The CDPP, FGM, CIS and STAFF teams, The active plasma sheet: definition of ‘events’ and statistical analysis, Proceedings of the 8th International Conference on Substorms, March 27–31, 2006, Banff Centre, Editors M. Syrjaeso and E. Donovan

Chapter 17

Cluster CAA Module for PaPCo ˚ J. Faden, A. Asnes, R. Friedel, M. Taylor, S. McCaffrey, C. Perry, and M.L. Goldstein

Abstract A PaPCo module for visualization of data from the CAA has been developed. This module retrieves data from the CAA web interface, and allows for discovery and plotting of new datasets. PaPCo is modular, open source IDL software that uses plug-in modules to bring new datasets on to a stack of time series plots (www.papco.org). PaPCo includes modules for plotting data from Cluster/PEACE and Cluster/RAPID, CDA Web data which includes Cluster Prime Parameters, and various modules from CRRES, POLAR, GPS, and many other spacecraft. The Cluster CAA module is presented, as well as a brief description of PaPCo’s use and installation procedure.

17.1 Introduction A CAA Module for the IDL plotting software “PaPCo” has been developed, allowing data from the CAA to be plotted and used for analysis. This article has two audiences: those who simply want to use the software to access data, and those who want to have full access to the capabilities and need developer documentation as well as user documentation.

J. Faden () Cottage Systems, Iowa City, IA, USA e-mail: [email protected] ˚ A. Asnes, M. Taylor, and S. McCaffrey ESA/ESTEC, Noordwijk, The Netherlands R. Friedel Los Alamos National Labs, Los Alamos, NM, USA C. Perry Rutherford Appleton Laboratory, Chilton, Didcot, Oxon, UK M.L. Goldstein NASA/GSFC, Greenbelt, MD, USA


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17.1.1 What Is PaPCo? PaPCo is modular, IDL-based software for making a stack of panels for analysis of data from various sources on a common time axis. Software modules created at many different institutions plug into the “PaPCo Core” to draw graphic data products on panels of the page. PaPCo was first developed for the CRRES mission in 1993 and has roughly 80 modules for instruments on over 15 spacecraft, and data sources like CDAWEB. PaPCo has been improved specifically for use with Cluster data over the past three years. Additionally, PaPCo has mature code for page layout, time axis controls, event list generation, batch processing, reformatting data and many other useful features. Most PaPCo modules now use PaPCo’s conventions for storing data. A dataset in this “internal data model” is a structure with the data itself stored in a multidimensional array, other datasets that tag the data dimensions and conventional name-value pairs to store metadata such as labels, physical units, typical ranges. Using this uniform model, modules can use PaPCo infrastructure for reducing and slicing data, caching, and accessing one another’s data.

17.1.2 CAA Module for PaPCo The CAA is a large store of useful datasets in a common data model. This allows for a PaPCo module to be created that can leverage off this store to provide a powerful tool for doing Cluster analysis. The module tries to achieve three goals. First, to provide a discovery capability that allows the user to discover useful data stored in the CAA. The analyst can browse list of roughly 800 available data sources, filtering the list by spacecraft, instrument and product type components of dataset identifiers. The dataset identifier and description are searchable using a simple regular expressions search. Also, we provide a “parameters search” which searches through descriptions and metadata for each plottable parameter within the datasets. Second, we automatically download data for the user using the Sinead McCaffrey’s “Command Line Interface,” an http-based interface for requesting data from the CAA. PaPCo’s File Cache Tool is used to show what is remotely and locally available, and availability plots can be made summarizing data availability. Third, data from the CAA is adapted to PaPCo’s internal model for plotting and slicing. High dimensionality datasets like PEACE 3DX can be viewed as TimeEnergy spectrograms, and then sliced to view pitch angle distributions. Data plotted by the module is available to other modules for further analysis, and codes written for the data model can be used.

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17.2 Using the Module The process of installing PaPCo is described later in this article, and for now we’ll assume that the software is installed with a version of the CAA module from the time of this writing. This section is intended to show the basic idea of how the module works, then in later sections we will look in depth at the module controls and installation process. The analyst launches PaPCo, and the PaPCo main widget appears. At the top left, a button labeled “Cluster CAA” (A) provides access to the “panel editor” for the CAA module (E), which is a GUI that adds and configures the plot panel (Fig. 17.1). The analyst operating the software clicks on Cluster CAA button (A), and the panel editor pops up, showing all available datasets. There are roughly 800 datasets at the time of this writing. The analyst then filters the list to locate the dataset for plotting, and selects the parameter to plot. For example, the analyst selects the parameter “N p C1 PP CIS,” which is CIS density data. The time axis range is controlled using the time control on the PaPCo main widget (B). For example, “9/13/2002” is entered to set the time axis to display data for that day. The analyst hits the “Draw” button (C) and several things will happen at this point. If this is the first time he is accessing the CAA, and he will need to enter his username and

Fig. 17.1 PaPCo Main Widget with CAA module panel editor. Pushing the module’s button (A) brings up its panel editor (E). This adds panels to the stack of panels to be plotted (D). Time is controlled on the main widget (B), and the Draw button (C) draws the page

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Fig. 17.2 PaPCo plot with data from PEACE, FGM, and CIS. A vertical slice at 14:58 shows slices of selected panels

password. The module checks to see what data is available, and if data is available, then a request is made to the CAA to download the data. The CAA may satisfy the request immediately and send over the data. In this case, data is sent over and copied into the local store of files. PaPCo routines for drawing line plots and spectrograms are used to display the data. Or, the CAA can “stage” the data request and module will automatically download the data later. The analyst can proceed while the request is staged and a empty panel indicates status. This process can be repeated to make a stack of plot panels (D) to compose a plot product (Fig. 17.2, right). Axis controls allow the analyst to scan along in time and zoom in on a feature of interest. The plot product can then be saved in a .papco file, printed, run as a batch process, etc, as with any PaPCo product. A complete description of PaPCo’s use and features is available on the PaPCo website, http://www.papco.org.

17.2.1 Slicing Data PaPCo modules can define “slicers” that allow the data to be inspected more deeply at a given time. For example, the analyst can click on a spectrogram to

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see an individual spectrum line plot for the time selected. Slicing can be thought of as throwing out the contextual dimension to inspect the details of the remaining dimensions. Slices can be quite complex. For example, slicing on a highly-dimensional PEACE spectrogram will show a pitch angle distribution of the data. PaPCo is able to slice multiple panels at once and several slices can be displayed side-by-side or plotted on the same axes (Fig. 17.2, left). Any dataset can be sliced, in general a reasonable view of the slice of data is displayed, using the axis ranges from the sliced plot. When this default view is too limited, the custom slicers can be written to create improved displays. Please refer to the PaPCo website for updates to this documentation, and demonstration videos of the software.

17.2.2 Panel Editor Clicking on the Cluster CAA button causes brings up its panel editor (Fig. 17.3). With the panel editor, the analyst adds new panels and edits existing panels. Each

Fig. 17.3 CAA Module Panel Editor is used to add and edit panels

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CAA panel has a dataset identifier and parameter identifier specifying what should be plotted, plus axis settings and plot style settings. The panel editor consists of four areas. At the top of the panel editor is a filter panel (F) that reduces the number of datasets listed in the dataset selector (D) below. Once a dataset is selected in the dataset selector, the plottable quantities within the dataset are displayed in the parameters selector (P) below. Remaining panels (S) control axis ranges and plot style. Note also, the terse descriptions of datasets and parameters are displayed below each selector (I). The “info” button displays a more complete dataset description. Once selections are made, the “Add and Close” button of the actions panel (Q) adds the panel to the stack of panels PaPCo plots. The filter panel allows the list of dataset IDs to be constrained by S/C, dataset type, and instrument. These are the three droplist widgets in the upper left of the filter panel (F). For example, setting these to C1, , PEA would constrain the list to PEACE datasets from the Cluster 1 spacecraft. The text widget labeled “search” performs a keyword search on dataset IDs and their terse descriptions. Only datasets containing the string are displayed. For example, the analyst might search for moments datasets by setting this to “moment” or use part of a dataset ID like “DEFlux.” This is a regular expression, and case is ignored. The checkbox labeled “limit to listed datasets” will limit the list of datasets to those that have already been downloaded. This allows the analyst to see just the datasets that he uses, without having to dig through hundreds of datasets that are not of interest. The filter panel text widget labeled “parameters search” performs an exhaustive search for parameters within the list of datasets. This further constrains the datasets list to those containing parameter descriptions that match the search. This can be a little slow, since a search of all datasets requires about 80,000 lines of text to be processed to complete the search. Matching parameters are marked with an asterisk ( ) in the parameters list. Last, (X) is an empty panel in the figure that is filled with additional widget controls for more complex datasets. These are called plug-in extensions and are described more below. For example, when vector quantities such a BGSE are selected, controls for selecting component or magnitude are inserted here.

17.2.3 Transferring Data from the CAA The Cluster CAA module automatically downloads data from the CAA for plotting. This is one of the more complex and useful aspects of the module. The CAA has a “Command Line Interface” that is a simple web interface, so we can then use PaPCo’s “wget” functionality to interact with the CAA. Note PaPCo can be put in off-line mode to prevent interaction with the server. PaPCo has a “File Cache” idiom, which is a set of remote data files that are parameterized in time, cached locally. Typically the remote source is an FTP or web site, and the file cache downloads files as requested into a local mirror of the

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Fig. 17.4 File Cache Tool showing locally and remotely available data. The “Get Selected” button is used for batch downloads

remote source. The File Cache Tool (Fig. 17.4) is a GUI that manages the file cache, allowing the analyst to browse the local and remote stores of data and download a number of files at once. We adapt the CAA Command Line Interface to make it appear to PaPCo as a remote store of data so that the file cache codes can be used. To enter the File Cache Tool, click on the “File Cache” button in the panel editor. Initially, the tool shows just the local files for the dataset, and the “list remote” button will perform a listing of the data in the CAA. The software may prompt for credentials at this point, and enter a username and password for the CAA. Note these can be stored permanently by using the “Config” button on the panel editor. After a short while, the CAA returns an availability listing for the dataset, and the File Cache Tool displays the listing. This listing is cached locally along with the data, and the “reset” button of the tool will retrieve a new listing. Note the CAA Command Line Interface allows clients to request arbitrary spans of data, and the module currently works with the CAA using day-long granules, without regard for how data was ingested into the CAA. The analyst can download data by selecting several remote files, then click on the “Get Selected” button. This posts a request for each day to the CAA. Its response

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will be either the files, or a message saying where the data will be when ready and a job ID. In this case, the staged request is marked with a “stage” file, and later attempts to get the data will check the stage file for the job ID and query CAA to see if the data is ready. When the data is ready, the data is then downloaded. If not, a message will be displayed. Queries to the CAA are limited to once per 120 s, because we don’t want to issue a query each time the page is redrawn. Data is downloaded as a .zip file, unpacked and then renamed to follow the conventions of the file cache. The tool can be used to delete data files once they are no longer useful.

17.3 Internal Mechanics PaPCo is open-source software and has a long history of being customized for particular applications. This section describes briefly technical aspects of the module for those who might consider using code or modifying the software for their own purposes. PAPCO BASE and PAPCO USER are configuration parameters that are set during the PaPCo installation process.

17.3.1 Reading and Plotting the Data Chris Perry’s IDL CEF reader is used to parse the CEF file. Data is read in and converted to PaPCo’s internal data model. Typically there is no information loss in the conversion, and using PaPCo’s model makes writing code for handling the data much simpler. Some datasets will necessarily have their dimensionality reduced to fit into more canonical data forms. For example, high-rank PEACE data is reduced to Flux (Time, Energy, Pitch Angle) so that distribution plots can be made using existing PaPCo software.

17.3.2 Datasets Database The dataset list comes from a local database of plottable parameters. Presently there is no mechanism to update this database, other than downloading a new version of the software. CAA is expected to add dataset discovery to its machine interface, and a future version will reflect changes in the available datasets. The database is distributed along with the module in a .zip file, and this file is unpacked into the user’s PAPCO USER area when the panel editor is first invoked. The database is implemented as a flat text file of line-separated records containing the dataset Ids and information about the dataset. This is PAPCO USER/caa catalog/caa datasets.tab. Each dataset has an XML description of its plottable parameters, and these are in PAPCO USER/caa catalog/db/.

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17.3.3 Plug-in Extensions Some datasets are not immediately useful for plotting. For some, calibrations need to be applied, a component must be selected, or the dimensionality is too high for plotting. This may be the most challenging element of the module, and this is where “power users” may want to write special plug-in code that extends the module to handle special cases. The plug-in is like a mini module within the CAA module that defines a widget controller and is called by the CAA module as data is loaded and plotted. Plug-ins are IDL objects that allow more complex datasets to work with the module. Complete documentation would be beyond the limits of this article, but example codes can be found within the module at PAPCO BASE/papco modules/cluster caa/ plugins.

17.3.4 Using PaPCo and the CAA Module to Access Data Within the module is code that can be used for IDL analysis outside of PaPCo. PaPCo must be initialized for the downloading to work. On the PaPCo website there are example codes showing how the module can be used read data from the CAA and perform queries.

17.4 Installing PaPCo PaPCo’s home on the web is http://www.papco.org. Instructions for downloading and installing PaPCo can be found there, as well as demonstration videos and more complete documentation. PaPCo is intended for use on Windows, Linux, Mac, and Solaris platforms. The full version runs on IDL 5.6 and newer. It will run under Runtime (unlicensed) IDL with minor limitations, mainly that only the core modules can be used since new code cannot be compiled at runtime. PaPCo is open-source software that is freely available for use and modification. The source and distributions can be found on SourceForge.net.

17.5 Conclusion The CAA Module for PaPCo provides a convenient and powerful tool that handles the details of finding data in the CAA, downloading and storing files, reading a new data format, and other minutia so the analyst can focus on science. Further,

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power users are enabled by providing access to the internals of the module. Data is provided in a uniform and flexible data model to support further analysis and future modules based on data from the CAA. Acknowledgments The author wishes to thank NASA/Goddard for continued support for PaPCo and the CAA Module.

Part III

Measurement Techniques and Calibration Routines

Chapter 18

Electron Density Estimation in the Magnetotail: a Multi-Instrument Approach A. Masson, O. Santol´ık, M.G.G.T. Taylor, C.P. Escoubet, A.N. Fazakerley, ˚ J. Pickett, A. Asnes, X. Vallières, H. Laakso, and J.-G. Trotignon

Abstract Electron density is a key physical quantity to characterize any plasma medium. Its measurement is thus essential to understand the physical processes occurring in the environment of a magnetized planet, both macroscopic and microscopic. Since 2000, the four satellites of the European Space Agency (ESA) Cluster mission have been orbiting the Earth from 4 RE to 20 RE and probing the density with several types of instruments. In the magnetotail, this rare combination of experiments is particularly useful since the electron density and the temperature fluctuate over several decades. Two of these experiments, a relaxation sounder and a high-time resolution wide-band receiver, have rarely been flown together in the far tail. Such wave data can be used as a means to estimate the electron density via the identification of triggered resonances or the cutoffs of natural wave emissions, typically with an accuracy of a few percent. For the first time in the magnetotail .20 RE /, the Z-mode is proposed as the theoretical interpretation of the cutoff observed on spectrograms of wave measurements when the plasma frequency is greater than the electron gyrofrequency. We present examples found in the main regions of the magnetotail, comparing simultaneous density estimation from active and passive wave measurements with a particle instrument and calibrated spacecraft-to-probe potential difference data. With these examples, we illustrate the benefit of a multi-instrument approach for the estimation of the electron density in the magnetotail and the care that should be taken when determining the electron density from wave data. ˚ A. Masson (), M.G.G.T. Taylor, C.P. Escoubet, A. Asnes, and H. Laakso ESA/ESTEC, D-SRE, Noordwijk, The Netherlands e-mail: [email protected] O. Santol´ık Institute of Atmospheric Physics and Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic A.N. Fazakerley UCL, Mullard Space Science Laboratory, Surrey, UK J. Pickett University of Iowa, Iowa, USA X. Vallières and J.-G. Trotignon LPCE/CNRS and Université d’Orléans, Orléans, France H. Laakso et al. (eds.), The Cluster Active Archive, Astrophysics and Space Science Proceedings, DOI 10.1007/978-90-481-3499-1 18, c Springer Science+Business Media B.V. 2010

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18.1 Introduction A precise estimation of the electron density in the Earth’s magnetic tail is needed to understand key physical phenomena at all spatial scales: from the microphysics of magnetic reconnection to the mechanisms of plasma entry into and within the tail. However, this estimation is not straightforward since the magnetotail is far from being a uniform medium, with electron density values ranging from 0.001 to 10 cm3 and electron temperature from a few 10’s of eV to several keV. To cover such a large range of plasma conditions, several scientific instruments are usually carried onboard a magnetospheric satellite to probe this key physical parameter. In the case of the ESA Cluster mission [8], four different types of instruments can be used to estimate it on each spacecraft: an electron experiment, an electric field instrument, a wide-band radio receiver and a relaxation sounder. Depending on the plasma conditions, each has their pros and cons (Section 18.2) but used in concert, they offer a rare opportunity to derive one of the most accurate measures of the electron density in the magnetotail. Section 18.3 focuses on the theoretical interpretation of the cutoffs observed on the spectrograms of active and passive wave measurements performed in the distant tail in order to derive the electron density. A rare event in the southern lobe region is then presented where density estimates from natural waves and calibrated spacecraft-to-probe potential difference measurements are compared. Typical examples found in the main regions of the magnetotail are finally presented in Section 18.4, comparing simultaneous density estimates from the electron instrument and active wave data.

18.2 Cluster Instruments for Electron Density Estimation On each Cluster satellite, the electron density can be derived from the following four instruments: the Plasma Electron And Current Experiment (PEACE) [18], the double-probe Electric Field and Waves (EFW) instrument [15] and two plasma wave instruments: the Wide-Band Data (WBD) experiment [14] and the Waves of HIgh frequency and Sounder for Probing of Electron density by Relaxation (WHISPER) instrument [5]. As detailed below, each of them has its advantages and disadvantages depending on the plasma conditions encountered.

18.2.1 PEACE The electron density is the zero-th order moment of the electron velocity distribution function measured by an electron experiment. A tutorial on the measurement of such distribution functions may be found in Fazakerley et al. [11] for particles of a few eV to a few tens of keV energy. A companion paper on plasma moments derived

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from a measured electron velocity distribution function [28] details their definition, computation, accuracy and use. An overview of the PEACE data contained in the Cluster Active Archive (CAA) with many aspects of their calibration can be found in [Fazakerley et al. Chapter 8, 19]. For completeness, we include some specifics here of the PEACE instrument with respect to the measure of the electron density. Accurate estimates of the electron density can be obtained in most regions of the magnetotail from the ground analysis of three dimensional (3D) data collected by PEACE on each Cluster satellite. These data have a good data coverage along the Cluster orbit compared to WBD (see Section 18.2.3) but don’t always have spin by spin cadence, except on Cluster 2 (C2). There are a couple of drawbacks inherent to this type of experiment including: the aging of the micro-channel plates (MCP) and the non-linear response of the MCP depending on the gain level used and the energy of the electrons detected. To counter balance this latter issue and fine-tune the calibration of the PEACE experiment, the absolute sensitivity is determined using comparisons of density measurements between PEACE and the plasma wave instruments WHISPER and WBD. Moreover, due to the inherent measurement technique used by the instrument (only a finite energy range is sampled), PEACE only provides a partial moment of the full electron distribution. As a result, in certain plasma regimes, where a proportion of the distribution is outside the range of the instrument, the density will be under estimated. These measurement challenges reinforce the importance of inter-calibrating all Cluster instruments able to estimate the electron density.

18.2.2 EFW The EFW instrument onboard Cluster [15], Chapter 6 estimates the potential difference between the main body of the satellite and the electric field probes every 0.2 s in the normal mode. In order to sample the pristine unperturbed plasma, the probes are attached to long booms to escape the sheath of plasma perturbations induced by the spacecraft. This goal is achieved on Cluster by having four spherical probes at the end of four 42 meter long antennas attached to each conductive spacecraft platform. Moreover, the probes are kept close to the local plasma potential by balancing their photoelectron current with a bias current from the spacecraft. In the magnetosphere, the spacecraft potential is determined by the balance between the current related to the escaping photoelectrons, the current related to the collected ambient electrons and the bias current. Thus, the knowledge of the photoelectrons escaping the spacecraft as a function of its potential, also called spacecraft photoelectron characteristic, enables the derivation of the ambient plasma density from the spacecraft potential measurements. Several papers have detailed this procedure for data collected by different magnetospheric satellites (e.g., [7, 19, 20, 24, 30–32, 36, 40]). Cully et al. [4] have carried out numerical calculations of the potential around Cluster, including the booms and the probe systems. They found that the potential

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in the vicinity of the probes (or probe potential) is driven by the positive boom tips and is approximately 19% of the spacecraft potential when the Debye length is larger than the probe-boom tip separation of 3 m. Taking into account this effect, yearly relationships (2001–2007) between the EFW spacecraft-to-probe potential difference measurements and the ambient electron density have been recently reported for plasma conditions found in the tail lobes and the polar caps [33, 38]. These recent developments are discussed further in Section 18.4.1.

18.2.3 WBD The NASA Wideband (WBD) plasma wave instrument consists of a digital wideband receiver onboard each Cluster spacecraft. Each of them provides very high-rate electric field waveforms either between 100 Hz and 9.5 kHz, 100 Hz to 19 kHz or 700 Hz to 77 kHz. These waveforms can also be sampled in three frequency conversion modes that provide frequency offsets of approximately 125, 250, and 500 kHz. For a complete description of the WBD instrument, see Gurnett et al. [14] and for the Wideband data products delivered to the CAA, see [Pickett et al. Chapter 11]. In the magnetosphere, WBD data can be used as a means to obtain accurate estimates (to a few percent at most) of the electron density via the cutoffs of plasma waves (see Section 18.3). However, the WBD primary mode of operation is the transmission of the measured waveform data in real-time to the NASA Deep Space Network or to the ground station in Panska Ves, Czech Republic. The consequence of this mode of operation is a non-continuous coverage of data along the Cluster orbit, unlike most of the other instruments like PEACE, EFW or WHISPER (see Section 18.2.4). After 8 years of operations, the average amount of data recorded by WBD is around 9 h per 57-h orbit for each spacecraft. In order to fulfill its many scientific objectives, the Wideband data recorded in the distant magnetotail are scarce. A recent survey of the WBD database found less than a dozen cases where the electron density could be accurately deduced in the distant tail. For all these events, WBD was operating in the mode up to 9.5 kHz which provides continuous waveforms with a 27.4 kHz sampling rate. This frequency range enables estimates of the electron density to be made between 0.001 and 1 cm3 . Despite their paucity, these case studies have played a key role in deducing the mode of propagation of the waves whose frequency cutoff can be used to derive the electron density. In combination with WHISPER active soundings, these cutoffs can be related to the local plasma density signatures.

18.2.4 WHISPER In most of the regions crossed by the Cluster mission, the electron density can be derived accurately from the active soundings and passive measurements of the

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WHISPER experiment. The hardware of WHISPER mainly consists of a pulse transmitter in the 4–80 kHz range, a wave receiver (2–80 kHz) and a wave spectrum analyzer. The principle of a relaxation sounder may be described as follows. A radio transmitter sends a wave train of frequency f during a short time period (1 or 0.5 ms for WHISPER). Soon after, a radio receiver connected to an electric sensor records the electric field signal around f for a short while. In the case of WHISPER, the electric sensor is one double-sphere dipole probes of the EFW experiment. The frequency is then shifted for a new sounding. The process is repeated until the full frequency bandwidth is covered. When a transmitted wave train is close to a characteristic frequency of the local plasma, very intense echoes can be received. Some of these stimulated signals are called resonances. They are almost monochromatic and mainly electrostatic. These plasma resonance signals enable the accurate derivation of the electron density via the identification or the deduction of the electron plasma frequency. A complete description of the WHISPER hardware can be found in Décréau et al. [5] and WHISPER data products delivered to the CAA are described in [Trotignon et al. Chapter 12]. The sounding approach has been considered the standard in the ionosphere (e.g. [6]) to which other techniques are compared and is also capable of making reliable magnetospheric electron density measurements using either relaxation sounding [9] or high-power sounding designed to produce long-range echoes [34]. Three main advantages favour the use of a relaxation sounder to derive the plasma density. First, it can trigger plasma resonances locally when the medium does not always show them naturally, as in the distant magnetotail (see Section 18.4.2). Second, it guarantees in situ measurements, while cutoffs of the plasma waves captured by a radio receiver might reflect the density at some unknown distance from the spacecraft. Last but not least, the instrument is not subject to ageing phenomena and needs no real calibration, only integrity checks. The main limitations are inherent to the technique and the hardware characteristics. The density is derived indirectly and the resonance recognition process is not 100% efficient especially in complex plasmas [5]. On the hardware side, the frequency range chosen for WHISPER limits the analysis to plasma regimes with densities between 0.2 and 80 e-/cc in the sounding mode and 0.05 to 80 e-/cc in the passive mode. The electron temperature range where plasma densities can be derived from WHISPER data is related to the length of the EFW booms and will be discussed in Section 18.4.3. Finally, recall that each Cluster satellite only transmits to the ground the on-board calculated Fast Fourier Transform (FFT) of the digital electric waveforms. This prevents some data analysis techniques from being used, like those performed on the data collected by the ISEE-1 relaxation sounder [42]. Unlike WBD, WHISPER benefits from full data coverage along the Cluster orbit but the time and frequency resolutions of WHISPER are much smaller than WBD. In the normal mode, a passive spectrum is recorded every 2.2 s and an active spectrum every 52 s or 104 s, with a minimum frequency resolution of 162 Hz.

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18.3 Z-Mode in the Distant Tail Relaxation sounders have been rarely flown in the distant tail. The first spacecraft carrying a sounder above 10RE was ISEE-1 in the late 1970s [16, 17]. Using the measurements of this sounder, Etcheto and Saint-Marc [10] reported the first observation of a high-density cold plasma region (5 cm3 , 30 eV) just outside the plasma sheet boundary layer (PSBL). Parks et al. [27] later named this new region the LowEnergy Layer (LEL). More recently, a number of papers have presented examples of spectrograms recorded by WHISPER in the distant tail (e.g. [5, 43]). Each time, the low-frequency cutoff of the triggered emissions and sometimes the natural waves observed were considered to be close to the electron plasma frequency (fpe ), thus enabling the derivation of the density, Ne from p fpe ŒkHz D 8:98 Ne cm3

(18.1)

But overall, few studies made use of the electron density measurements derived from active soundings performed in the deep tail. Moreover, whereas the derivation of the electron density from sounder data collected in the solar wind, magnetosheath and plasmaspheric regions is common knowledge, the interpretation of active soundings and natural wave cutoff in the far tail is much less clearly linked to the cold plasma theory. For instance, Etcheto and Saint-Marc [10] consider that the strongest signal to be “in the vicinity of the plasma frequency”. The plasma frequency is the characteristic frequency at which plasma oscillates when its constituents are displaced relative to one another. In addition to this mode, a number of characteristic frequencies and speeds associated with the medium exist. These modes are derived from the dispersion relation of that medium. According to the cold plasma theory (e.g. [37]), where one ignores the thermal speeds of the ions and the temperature of the electrons, the so-called Z mode with L-X polarization exists below the electron plasma frequency (fpe ). Above fpe , three modes exist, the X polarized Z-mode and the two free space L-O and R-X modes when fpe is greater than fce with fce the electron cyclotron frequency (see left panel of Figure 1.2. of Benson et al. [2]). Local Z-mode signatures have been recorded by many ionospheric spacecraft and more recently in the magnetosphere by the NASA IMAGE satellite (polar orbit, apogee 7RE ). See Benson et al. [2] for a recent review. These data confirmed the idea that a more complicated relationship exists between the characteristic modes of the plasma and the observed cutoffs. In particular, the cutoff corresponding to fpe is accompanied by a lower cutoff (fZ ) corresponding to the cutoff at L D 0 of the Z mode with L-X polarization and given by fZ D

. 0:5 fce 2 C 4 fpe 2 fce 2

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The importance of a proper wave-mode identification was well illustrated by the classic work on the auroral plasma cavity by Calvert [3] where a whistler-mode interpretation by Gurnett and Green [12] was reinterpreted as a Z-mode emission,

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and by Gurnett et al. [13], who used DE-1 satellite data to reinterpret the Hawkeye satellite continuum data of Gurnett and Green [12] as Z-mode emission. An extensive review on auroral Z-mode emissions was done by LaBelle and Treumann [21]. The work of Lefeuvre et al. [22] stressed the benefit of multi-component wave measurements to distinguish between wave modes. Our paper stresses the benefit of multi-instruments in resolving difficult interpretation situations. In this section, we present two rare case studies, where a multi-instrument approach enables us to propose a new theoretical interpretation of these low frequency cutoffs observed on active and natural wave spectra far in the tail; data were collected by WBD, WHISPER, PEACE, EFW and the FluxGate Magnetometer (FGM) [1].

18.3.1 Event 1: 28 July 2006 Figure 18.1a displays a spectrogram of WBD electric field data recorded onboard Cluster 1 (or C1) in the outer plasma sheet (Te 660 eV) on 28 July 2006 between 09:25:30 and 09:26:00 UT. A clear steady cutoff of wave emissions is observed at 8:7 kHz called fZ (see white arrow). This cutoff can be extracted automatically

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from the WBD data by adapting the automatic cutoff recognition procedure developed for auroral hiss by Santol´ık et al. [35]. An active spectrum recorded by WHISPER on C1 at 09:25:31 is displayed in Fig. 18.1b where the same frequency value of the cutoff is observed (thick white arrow pointing up). Note that the chosen frequency cutoff (white arrow) was picked up in the middle of the decreasing slope and not at the foot of it. The active/passive comparison (not shown), however, does not indicate the presence of significant emissions stimulated by the sounder. Thus, we assume that both signatures are relevant to a local signature of the medium. Due to the high-time resolution of WBD, a dimmer but detectable secondary cutoff is present around 0.25 kHz above fZ . We suggest that this secondary cutoff corresponds to the electron plasma frequency (fpe ) while the sharp lower cutoff (fZ ) corresponds to the Z-mode frequency defined in equation (18.2). If true, the 0.25 kHz frequency difference between fpe and the lowest cutoff (fZ ) should correspond to half the value of the electron gyrofrequency as follows from Eq. (18.2) when fpe >> fce fz fpe fce =2 . Since fce ŒHz D 28 B ŒnT and the magnetic field strength estimated by FGM at this time is B 18 nT, hence fce =2 0:25 kHz. Thus, this interpretation leads to an estimate of the plasma frequency of fpe 8:95 kHz hence Ne 0:99 cm3 . If the lower cutoff had been interpreted as the electron plasma frequency (fpe 8:7 kHz), this would have led to an estimate of 0:94 cm3 . During the same time interval, PEACE measures a density varying between 0.92 and 0:84 cm3 using current calibrations. Knowing that the spacecraft potential is around 10 V, we suggest that the tiny difference between density estimates from the wave cutoff and the electron detectors is due to the electrons with energy below 35 eV not measured by PEACE during this time interval. In other words, PEACE data cannot be used to discriminate between the two cutoffs observed on WBD for this specific case study. It is fair to say that for such plasma conditions, fpe >> fce , the density difference between the new interpretation (fZ ) and previous interpretation (fpe ) is almost negligible (5%). In other words, previous published density estimates from active sounder data in the outer plasmasheet were good approximations. Moreover, since the nominal frequency resolution of WHISPER is 162 Hz but often 324 Hz is used, we cannot fully reject the possibility that the lower cutoff observed on active spectra in the far tail might be the plasma frequency instead. However, in other plasma conditions (e.g. the lobes), the interpretation of the lower cutoff of WBD passive data as either Z-mode or fpe can lead to a significant density difference, as we will now demonstrate.

18.3.2 Event 2: 07 September 2006 On 07 September 2006, the Cluster spacecraft were crossing the southern lobe region. Figure 18.2 displays the spectrogram of the electric field recorded by WBD on C1 between 07:38:30 and 07:39:00 UT where a clear cutoff is visible


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at fZ 1:5 kHz. Since such a frequency is below the lower limit of the WHISPER soundings (4 kHz), we need to assume that this natural wave cutoff corresponds to a local signature. At this time, the magnetic field strength measured by FGM was 32nT. Using the newly proposed interpretation of the frequency cutoff, fpe 2:01 kHz and Ne 0:05 cm3 . The spacecraft-to-probe potential difference recorded by EFW on C1 is perturbed by the Electron Drift Instrument [29] operating on both C1 and C3 during this time period. In such a tenuous and cold plasma environment (Te < 100 eV), EDI has sometimes the opposite effect of the Active Spacecraft POtential Control [41]: pushing the spacecraft potential up and perturbing PEACE electron measurements. However, EDI was not operating on C2 and C4 at the time of the WBD measurements on C1. The spacecraft-to-probe potential difference measured by C2 and C4 match very well for hours before and after the WBD time period. Since C2 and C4 were the more spread apart satellites within the Cluster space fleet while C1 was flying in between, we assume that the plasma was homogeneous within the Cluster constellation in the lobe region crossed that day. In other words, we make the assumption that the spacecraft-to-probe potential difference on C1 fluctuated between 35.55 V and 36.16 V from 07:38:30 to 07:39:00 UT, according to C2 and C4 measurements. Thanks to a recent calibration study of the spacecraft-to-probe potential difference measurements for such plasma conditions (see Sections 18.2.2 and 18.4.1), we are able to derive a density estimate of Ne 0:053 ˙ 0:01 cm3 from the average EFW potential value (35:7 V). This estimate is in good agreement with the WBD estimation. However, it would have been in disagreement if the WBD lower cutoff frequency would have been interpreted as the plasma frequency since fpe 1:5 kHz gives Ne 0:028 cm3 .

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PEACE estimates of the density on C2 and C4 exceed or are close to 0.028. These estimates take into account electrons with energy between 50 and 200 eV but discard lobe electrons in the same energy bin as the photoelectrons (below 50 eV) resulting in an underestimation of the electron density. Thus, PEACE data on C2 and C4 also support the Z-mode interpretation during this time interval.

18.4 A Multi-instrument Approach The Earth’s magnetotail is composed of three main regions, characterized by distinct electron density and temperature ranges: the lobe regions (Ne < 0:1 cm3 , Te 100 eV), the central plasma sheet (0:1 < Ne < 10 cm3 , Te 1 keV) and sandwiched between these two regions the Plasma Sheet Boundary Layer (PSBL). The PSBL is characterized by high-speed streaming and counter-streaming beams of particles of ionospheric and magnetic reconnection origin. Deriving the best density estimate in these regions requires a careful selected combination of Cluster instrument measurements. We illustrate this below with recent results and open questions showing how an accurate estimation of this parameter is relevant to assess critical geophysical issues.

18.4.1 Lobe Regions The magnetospheric lobes are the regions of space located tailward of the polar cap and delimited by the mantle and the plasmasheet regions of the magnetotail. They are usually characterized by tenuous cold plasma with density below 0:1 cm3 [38]. We note that the lowest density value that can be derived from WHISPER soundings is 0:2 cm3 . In such plasma conditions, the potential attained by the spacecraft is so high (20–70 V) that most of the ambient ions are not able to reach the ion sensors. Thus, ion density measurements in this region are of little relevance. Electron measurements can be affected by photoelectrons (see [? ? ]) and in certain low temperature plasma environments are limited by the finite energy bandwidth of the instrument. However, since the measure of the spacecraft-to-probe potential difference does not have these intrinsic limitations, a proper calibration of these measurements can provide accurate estimates of the ambient plasma density with a high time resolution (up to 0.2 s on Cluster) for all lobe crossings as long as the ASPOC instrument is turned off. The calibration procedure of the measured EFW spacecraft-to-probe potential difference (Vscp ) into density is detailed in Pedersen et al. [33] for plasma conditions found in the lobes and over the polar cap regions. Pedersen et al. [33] provides, for the first time, yearly relationships between Vscp and electron density from 2001 to 2004 assuming Te < 100 eV. An update to 2007 has been recently published by Svenes et al. [38]. Using these relationships, Ne can be derived from Vscp with an

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error bar of ˙ .10–20/ %. For spacecraft potential above 40 V .Ne < 0:05/, only an order of magnitude accuracy of Ne is claimed. Thanks to these relationships, Svenes et al. [38] was able to study the nearEarth magnetospheric lobes throughout 7 years of solar cycle 23 covered so far by Cluster. All derived densities are distributed between 0:007 cm3 and 0:5 cm3 but two-thirds of them are below 0:1 cm3 with a median value of 0:047 cm3 . The density in this region was found in general to be independent of the solar wind conditions or the geomagnetic activity. However, the high-density tail of the population (Ne > 0:2 cm3 ) seemed to decrease with the waning of the solar cycle, pointing to a source region influenced by the diminishing solar UV/EUV intensity. As the quiet time polar wind has such a characteristic, they conclude that polar wind is most likely the dominant source of plasma in the lobes.

18.4.2 PSBL/Outer Plasmasheet The plasma sheet boundary layer and the outer plasmasheet are characterized by electron densities of the order of a few electrons per cc and temperatures of a few hundreds eV. In these regions, the electron density is accurately sampled on each Cluster satellite by the PEACE experiment. However, as discussed in Section 18.2.1, this instrument requires in-flight calibration due to the aging of the micro-channel plates (MCP) and the non-linear response of the MCP to the gain level and the energy of the electrons detected. As detailed in Fazakerley et al. [? ], the post-launch calibration has been enhanced by the comparison with other experiments estimating the electron density in an independent way. Contrary to the lobe regions, no yearly relationships between EFW spacecraft potential and density have been derived yet while WBD datasets are too scarce to provide reference densities through the PEACE energy range. Very often triggered emissions are observed on WHISPER active spectra in these regions, which enable the provision of accurate reference densities over a wide range of electron temperatures. Figure 18.3 presents data collected by C1 during a typical outer plasmasheet crossing (17 August 2003, 15:00–16:20). The top panel displays a passive WHISPER spectrogram of the electric field between 2 and 40 kHz, where almost no wave activity is detected above 10 kHz. The second panel from top presents an active WHISPER spectrogram between 5 and 40 kHz during the same time period with a 52 s time resolution. In this panel, the most intense emissions are observed between 15 and 30 kHz. These emissions are sounder stimulated since almost no wave activity is observed on the passive receiver data above 10 kHz during the same time period (see top panel). A clear resonance, nearly continuous, is observed around 15 kHz in the second panel. This resonance is pointed out with three white arrows.The third panel also displays the active WHISPER spectrogram but this time, the PEACE density dataset, re-sampled at WHISPER sounding times is over-plotted in pink using Eqs. 18.1 and 18.2. Meanwhile, the magnetic field modulus estimated by FGM fluctuates between

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10 and 35 nT, corresponding to an electron gyrofrequency, fce , between roughly 0.3 and 1 kHz. An almost perfect match is found between PEACE densities converted to Z-mode frequencies and WHISPER resonances. The bottom panel displays the parallel electron temperature (black curve) and the electron density (pink curve) determined by PEACE. The temperature slowly evolves between 100 and 200 eV while the density fluctuates between 1 and 5 cm3 . For each Cluster spacecraft, analysis of tens of cases such as this one have been performed in the outer plasmasheet and the PSBL by members of the intercalibration working group of the Cluster Active Archive. Each time, an agreement better than 90% was found between PEACE densities converted to Z-mode frequencies and WHISPER resonances.

18.4.3 Central Plasmasheet Most of the time, the plasma number density in the central plasmasheet is of the order of a few tenths of electrons per cubic centimetre (e =cc) with a temperature around a few keV [23]. However, during periods of extended northward Interplanetary Magnetic Field (IMF) with low geomagnetic activity, a Cold Dense Plasmasheet (CDPS) can be observed. The density of the CDPS can be as high as several e =cc with a plasma temperature dropping well below 1 keV. The CDPS is observed more often near the flanks, but at times extends throughout the entire plasmasheet. Several mechanisms have been proposed to explain the CDPS, in particular plasma diffusion across the magnetopause [39], plasma mixing due to KelvinHelmholtz vortices [25], and dual lobe magnetic reconnection [26]. Understanding the CDPS formation is important because the plasmasheet provides the seed populations for the ring current and the radiation belts, which can become substantially enhanced when the IMF turns southward after a CDPS episode, and when the ensuing magnetic storm pushes the plasma into the inner magnetosphere. The central plasmasheet is also the place of major macro-scale magnetospheric phenomena such as bursty bulk flows and magnetic reconnection related to substorms. For all these reasons, an accurate estimate of the electron density is crucial. The PEACE instrument on each Cluster satellite provides an accurate estimate of the electron density in most cases. However, regular comparisons with an independent estimate of the density help to fine-tune the calibration of PEACE. In the central plasmasheet, the analysis of WHISPER active soundings on tens of case studies has revealed that accurate densities can be derived from active spectra. One of these case studies is presented in Fig. 18.4. It corresponds to the crossing of the central plasmasheet by Cluster 1 on 30 July 2002 between 18:00 and 19:20 UT. In the top panel, the parallel electron temperature derived from PEACE measurements every 4 s is displayed as a black line. The blue asterisks indicate when an estimate of the electron density was derived from WHISPER active soundings. In the second panel, the black line corresponds to the estimation of the electron density by PEACE while the blue asterisks are the densities derived from WHISPER active

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Fig. 18.4 Cluster 1, 30-July-2002, 18:00–19:20 UT, top panel: PEACE parallel electron temperature (black line), the blue asterisks indicate when an estimate of the electron density was also derived from WHISPER active soundings. Second panel from top: PEACE electron density (black line), the blue asterisks are the electron density values derived from WHISPER active soundings. The third panel from top displays WHISPER active spectrogram of the electric field between 4 and 28 kHz recorded every 52 s. A superimposed thick black line correspond to the PEACE densities converted to Z-mode frequencies using Eqs. 18.1 and 18.2, down sampled to WHISPER time resolution; the electron gyrofrequency is estimated using FGM magnetic field data. All sharp lower cutoff frequencies extracted from individual WHISPER active spectra are overplotted in this third panel as short horizontal white line segments. They correspond to the blue asterisks in the top two panels. The bottom panel displays a single active spectrum recorded at 19:05:31 UT from 4 to 80 kHz. A sharp cutoff is observed at 6.29 kHz and shown with a dotted black line. A blue dashed line is located at 28 kHz to stress the upper frequency limit of the spectrogram displayed in the third panel. The 4–28 kHz part of this spectrum corresponds to the narrow black rectangle pointed out with a black arrow in the third panel

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soundings. Not every WHISPER active sounding enables the successful derivation of a density value since a sharp lower cutoff, such as the one presented in the bottom panel, is not always observed (see discussion below). A shallow cutoff logically leads to imprecise or impossible density estimation. Active spectra recorded every 52 s by WHISPER between 4 and 28 kHz are presented in the third panel from top. Although the measurements have been performed up to 80 kHz, we focus on this lower range to better compare PEACE and WHISPER density estimates. In the same panel, a superimposed thick black line displays the PEACE densities converted to Z-mode frequencies using Eqs. 18.1 and 18.2, down-sampled to WHISPER time resolution. The electron gyrofrequency is estimated using FGM magnetic field data (not displayed, the modulus of the magnetic field fluctuates around 8 nT). This black line fits the lower cutoff of intense emissions triggered by WHISPER soundings especially after 19:00 UT (Te 500 eV). Lower cutoff frequencies have been extracted from individual WHISPER active spectra when a sharp cutoff was observed. These frequency values are overplotted in this third panel as short horizontal white line segments. They correspond to the blue asterisks in the top two panels. The bottom panel displays a single active spectrum recorded at 19:05:31 UT from 4 to 80 kHz. A sharp cutoff is observed at 6.29 kHz and shown with a dotted black line on the left of the bottom panel. A blue dashed line is located at 28 kHz to stress the upper frequency limit of the spectrogram displayed in the third panel. The 4–28 kHz part of this spectrum corresponds to the narrow black rectangle pointed out with a black arrow in the third panel. As one can notice, the WHISPER response to this hot plasma environment is different from the outer plasmasheet/PSBL. Whereas almost continuous density datasets can be extracted from this latter region (see Section 18.4.2), only a set of clear cutoffs, irregularly spread in time, can be extracted from WHISPER soundings in the central plasmasheet, especially before 18:40 UT when Te > 1 keV. This result is not surprising since, according to antenna theory, the physical length (L) of the antenna has to be higher than the Debye length, which is proportional to the square root of the Te =Ne ratio. Thus, a hot and relatively tenuous population has an associated Debye length much larger than L and is sometimes not seen by the sounder. Unfortunately, a quantitative estimation of the Debye length limit has not yet been estimated for the WHISPER instrument [? ]. In other words, a precise range of electron density and temperature where the WHISPER soundings can be used to estimate the electron density remains to be established. However, a number of numerical simulations, together with statistical analyses of WHISPER/PEACE cross-calibrations in this region, are in progress to estimate it. Nevertheless, the example presented in Fig. 18.4 represents one of the first determinations of densities derived from active soundings in the central plasmasheet. The interpretation of the active resonance proposed in Section 18.3 is used since close to the cutoff the phase speed is very large (>c, diverging to infinity at the cutoff frequency) so the wave-particle interactions should be independent of particle velocities, which are obviously below the speed of light. Of course the cutoff position would be shifted in a relativistic plasma since the electron gyrofrequency would

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Table 18.1 Instruments available on every Cluster satellite to provide an estimate of the electron density are listed in the left column. The next column details the data coverage in the magnetotail of these instruments. The last three columns indicate by a “X” sign which instruments should be preferably used in the magnetotail to derive the density according to this study PSBL/outer Cluster experiments Magnetotail data coverage Lobes plasmasheet Central plasmasheet EFW 100% X PEACE 100% X X WHISPER 100% X X WBD Few data sets X X

decrease with increasing relativistic mass of the particles. But the energies are still too low for that in the plasmasheet and the cold plasma approximation holds. Analyses of tens of events reveal that PEACE and WHISPER densities agree within a few percent. According to the different findings reported in Sections 18.3 and 18.4, Table 18.1 summarizes which Cluster instruments should be preferably used to derive the electron density in the three main regions of the magnetotail.

18.5 Conclusion Together, particle detectors, DC and AC electric fields instruments onboard magnetospheric satellites enable to accurately estimate the electron density in the Earth’s magnetotail. A multi-instrument approach enhances the calibration of both particle experiment and spacecraft-to-probe potential difference values, thus enabling the scientific community to access a more accurate estimate of the electron density. This paper details the outcome of this approach for such experiments onboard each satellite of the Cluster mission. A new theoretical interpretation in terms of the Z-mode is proposed for the lower cutoff of natural and active soundings observed on spectrograms collected by a wide-band receiver and a relaxation sounder in the far tail (20 RE ). However, since the nominal frequency resolution of the WHISPER relaxation sounder is 162 Hz (but often 324 Hz is used), we cannot fully reject the possibility that the lower cutoff observed on active spectra in the far tail might be the plasma frequency instead. An agreement between the density derivation based on this interpretation and calibrated spacecraft-to-probe potential difference measurements is found to be within a few percent in the lobes. The same level of agreement is found in the PSBL and the outer plasmasheet between densities derived from the electron detectors and from active soundings. One of the first examples of density derivation from active soundings is presented for data collected in the central plasmasheet around 20 RE on the nightside. This observational fact raises the issue of an accurate estimation of the Debye length limit for the WHISPER instrument. In other words, in which plasma conditions is WHISPER able to sense the plasma and accurately derive the density?

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Overall, a very good agreement was found between estimates of the electron density from these totally independent types of experiments. The multi-instrument approach has helped to fine-tune the calibration of the PEACE and EFW instruments, hence providing a higher accuracy of density estimates in the Earth’s magnetosphere. Acknowledgements This study has been triggered and discussed within the cross-calibration group of the Cluster Active Archive (CAA) sponsored by the European Space Agency. Ondrej Santol´ık acknowledges the grant support from GAAV IAA301120601 and NSF 0307319/ME 842.

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15. Gustafsson, G., M. André, T. Carozzi, A. I. Eriksson, C.-G. Fälthammar, R. Grard, G. Holmgren, J. A. Holtet, N. Ivchenko, T. Karlsson, Y. Khotyaintsev, S. Klimov, H. Laakso, P.-A. Lindqvist, B. Lybekk, G. Marklund, F. Mozer, K. Mursula, A. Pedersen, B. Popielawska, S. Saving, K. Stasiewicz, P. Tanskanen, A. Vaivads, and J.-E. Wahlund (2001), First results of electric field and density observations by Cluster EFW based on initial months of operation, Ann. Geophys., 19, 1219–1240. 16. Harvey, C. C., J. Etcheto, Y. de Javel, R. Manning, and M. Petit, The ISEE electron density experiment, IEEE Trans. Geosci. Electron., GE-16, 231–238, 1978. 17. Harvey, C. C., J. Etcheto and A. Mangeney (1979), Early results from the ISEE electron density experiment, Space Sci. Rev., 23, 39–58. 18. Johnstone, A. D., et al. (1997), PEACE, a plasma electron and current experiment, Space Sci. Rev., 79, 351–398, doi:10.1023/A:1004938001388. 19. Laakso, H., and A. Pedersen (1998), Ambient electron density derived from differential potential measurements, in Measurement Techniques in Space Plasmas: Fields, Geophys. Monogr. Ser., 102, edited by J. Borovsky, R. Pfaff, and D. Young, pp. 73–78, AGU, Washington, DC. 20. Laakso, H., R. Pfaff, and P. Janhunen (2002), Polar observations of electron density distribution in the Earth’s magnetosphere. Density Profiles, Ann. Geophys., 20, 1725–1735. 21. Labelle, J. and R. A. Treumann, Auroral radio emissions, hisses roars, and bursts, Space Sci. Rev., 101, 364–440, 2002. 22. Lefeuvre, F., M. Parrot, J. L. Rauch, B. Poirier, A. Masson, and M. Mogilevsky (1998), Preliminary results from the MEMO multicomponent measurements of waves on-board INTERBALL 2, Ann. Geophys., 16, 1117–1136. 23. Nagata, D., S. Machida, S. Ohtani, Y. Saito, and T. Mukai, Solar wind control of plasma number density in the near-Earth plasmasheet: three dimensional structure, Ann. Geophys., 26, 4031– 4049, 2008. 24. Nakagawa, T., T. Ishii, K. Tsuruda, H. Hayakawa, and T. Mukai (2000), Net current density of photoelectrons emitted from the surface of the GEOTAIL spacecraft, Earth Planets Space, 52, 283– 292. 25. Nykyri, K. and Otto, A. (2001), Plasma Transport at the Magnetospheric Boundary due to Reconnection in Kelvin-Helmholtz Vortices, Geophys. Res. Lett., 28(18), 3565–3568. 26. Øieroset, M., J. Raeder, T. D. Phan, S. Wing, J. P. McFadden, W. Li, M. Fujimoto, H. Rème, and A. Balogh (2005), Global cooling and densification of the plasmasheet during an extended period of purely northward IMF on October 22–24, 2003, Geophys. Res. Lett., 32(12), L12S07, doi:10.1029/2004GL021523. 27. Parks, G. K., et al. (1992), Low-Energy particle Layer outside of the plasmasheet boundary, J. Geophys. Res., 97, 2943–2954. 28. Paschmann, G., A. Fazakerley and S. Schwartz (1998), Moments of Plasma Velocity Distributions in Analysis Methods for Multi-Spacecraft Data, edited by G. Paschmann and P. W. Daly, ISSI Scientific Report SR-001, ISSI/ESA. 29. Paschmann, G., Quinn, J. M., Torbert, R. B., Vaith, H., McIlwain, C. E., Haerendel, G., Bauer, O. H., Bauer, T., Baumjohann, W., Fillius, W., Förster, M., Frey, S., Georgescu, E., Kerr, S. S., Kletzing, C. A., Matsui, H., Puhl-Quinn, P., and Whipple, E. C.: The Electron Drift Instrument on Cluster: overview of first results, Ann. Geophys., 19, 1273–1288, 2001. 30. Pedersen, A. (1995), Solar wind and magnetosphere plasma diagnostics by spacecraft electrostatic potential measurements, Ann. Geophys., 13, 118–121, doi:10.1007/s00585-995-0118-8. 31. Pedersen, A., F. Mozer, and G. Gustafsson (1998), Electric field measurements in a tenuous plasma with spherical double probes, in Measurement Techniques in Space Plasmas: Fields, Geophys. Monogr. Ser., vol. 103, edited by R. F. Pfaff, J. E. Borovsky, and D. T. Young, pp. 1–12, AGU, Washington, DC. 32. Pedersen, A., P. Décréau, C. P. Escoubet, G. Gustafsson, H. Laakso, P.-A. Lindqvist, B. Lybekk, A. Masson, F. S. Mozer, and A. Vaivads (2001), Four-point high time resolution information on electron densities by the electric field experiment (EFW) on Cluster, Ann. Geophys., 19, 1491–1504.

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33. Pedersen, A., B. Lybekk, M. André, A. Eriksson, A. Masson, F. Mozer, P.-A. Lindqvist, P. M. E. Décréau, I. Dandouras, J.-A. Sauvaud, A. Fazakerley, M. Taylor, G. Paschmann (2008), Electron density estimations derived from spacecraft potential measurements on Cluster in tenuous plasma regions, J. Geophys. Res., 113, A07S33, doi:10.1029/2007JA012636. 34. Reinisch, B. W., et al. (2001), First results from the radio plasma imager in IMAGE, Geophys. Res. Lett., 28, 1167. 35. Santol´ık, O., A. M. Persoon, D. A. Gurnett, P. M. E. Décréau, J. S. Pickett, O. Marsalek, M. Maksimovic, and N. Cornilleau-Wehrlin (2005), Drifting field-aligned density structures in the night-side polar cap, Geophys. Res. Lett., 32, L06106, doi:10.1029/2004GL021696. 36. Scudder, J. D., X. Cao, and F. Mozer (2000), Photoemission current spacecraft voltage relation: Key to routine quantitative low energy plasma measurements, J. Geophys. Res., 105, 21,281, doi:10.1029/1999JA900423. 37. Stix, T. H. 1992, Waves in Plasmas, New York, American Institute of Physics. 38. Svenes, K.R., B. Lybekk, A. Pedersen, and S. Haaland (2008), Cluster observations of near-Earth magnetospheric lobe plasma densities – a statistical study, Ann. Geophys., 26, 2845–2852. 39. Terasawa, T., Fujimoto, M., Mukai, T., Shinohara, I., Saito, Y., Yamamoto, T., Machida, S., Kokubun, S., Lazarus, A. J., Steinberg, J. T., and Lepping, R. P. (1997), Solar Wind control of density and temperature in the near-Earth plasmasheet: WIND/GEOTAIL collaboration, Geophys. Res. Lett., 24, 935–938. 40. Thiébault, B., A. Hilgers, A. Masson, C. P. Escoubet, and H. Laakso (2006), Simulation of the Cluster-Spacecraft Floating Probe Potential, IEEE Nucl. Plasma Sci. Soc., 34(5), 2078–2083, doi:10.1109/TPS.2006.883407. 41. Torkar, K., Riedler, W., Escoubet, C. P., Fehringer, M., Schmidt, R., Grard, R. J. L., Arends, H., Rüdenauer, F., Steiger, W., Narheim, B. T., Svenes, K., Torbert, R., André, M., Fazakerley, A., Goldstein, R., Olsen, R. C., Pedersen, A., Whipple, E., and Zhao, H.: Active spacecraft potential control for Cluster – implementation and first results, Ann. Geophys., 19, 1289–1302, 42. Trotignon, J. G., Etcheto, J., and J. P. Thouvenin (1986), Automatic determination of the electron density measured by the relaxation sounder on board ISEE-1, J. Geophys. Res., 91, 4302–4320. 43. Trotignon, J. G., Décréau, P. M. E., Rauch, J. L., Suraud, X., Grimald, S., El-Lemdani Mazouz, F., Vallières, X., Canu, P., Darrouzet, F., Masson, A. (2006), The electron density around the Earth, a high level product of the Cluster/WHISPER relaxation sounder, Cluster and Double Star Symposium, 5th Anniversary of Cluster in Space, held 19–23 September, 2005 in Noordwijk, The Netherlands, edited by K. Fletcher, ESA SP-598, European Space Agency, published on CDROM., p. 70.1.

Chapter 19

Cluster-PEACE In-flight Calibration Status A.N. Fazakerley, A.D. Lahiff, I. Rozum, D. Kataria, H. Bacai, C. Anekallu, ˚ M. West, and A. Asnes

Abstract We briefly summarise key aspects of our on-going in-flight calibration work for the Cluster Plasma Electron And Current Experiment (PEACE) instruments, and demonstrate the quality of moments which may be achieved, by comparisons with measurements from other Cluster instruments. As improved calibrations are generated, data in scientific units which have been produced for the Cluster Active Archive will be systematically updated. This article is not intended as a detailed description of our calibration studies, but rather as a snapshot of the calibration status at the time of writing, which will give the researcher using the CAA an indication of the levels of accuracy that can be achieved at this time.

19.1 Introduction The CAA data for the Plasma Electron And Current Experiment (PEACE) and the experiment itself, have been introduced elsewhere in Chapter 8 of this book. The purpose of this paper is to briefly describe the PEACE calibration parameters, discuss which ones vary over time as the mission progresses and how the variation is accounted for. Examples of the accuracy of moments calculated from PEACE 3D data using the current calibration are provided to illustrate the effectiveness of our in-flight calibration work. The calibrations now available (version 5.1 at time of writing) allow determination of four-point plasma quantities, enabling studies of, for example, the divergence of the electron pressure tensor [2].

A.N. Fazakerley (), A.D. Lahiff, I. Rozum, D. Kataria, H. Bacai, C. Anekallu, and M. West Mullard Space Science Laboratory, University College London, UK e-mail: [email protected] M. West Now at Royal Observatory, Belgium ˚ A. Asnes ESA/ESTEC, Noordwijk, The Netherlands


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19.2 The Calibration Parameters 19.2.1 Introduction to the Calibration Parameters Every spin, each PEACE sensor makes a series of measurements in different look directions and energies to sample all or part of the full velocity distribution of the plasma electrons (as explained by Fazakerley et al., Chapter 8, this book). An individual measurement is intended to reveal the velocity space density of the electrons in a small region of velocity space, described in terms of a restricted energy (or equivalently speed) interval k and a direction defined by polar angle i and azimuth angle j , which is called fijk . The relationship between measured quantities, calibration factors and fijk is given as follows: fijk D Pijk = tacc vk 4 Gi "ik where: tacc is the data accumulation time, a fixed fraction of the spin period vk is the mean value of the measured electron speed during time tacc Gi is the geometric factor for the i th polar angle sector, which in a sufficiently concentric analyser, reduces to a single value G for all sectors Pijk is the number of counted electrons after dead time correction (related to instrument electronics not the MCP) and "ik D "0 " vk 2 i is the detector efficiency, which is expected to vary with position on the detector and with electron energy Ground calibration work provides values for the energies (speeds) measured during energy sweeps, vk , the geometric factor Gi and the relative sensitivity of the detector " vk 2 i , under conditions of optimum detector performance. These are used as the baseline from which any in-flight calibration corrections are made. It is challenging to establish good values for absolute detector efficiency "0 , during ground calibration, due to the difficulty of measuring the current in an electron beam in a calibration facility with sufficient accuracy (i.e., in generating a beam with very well determined fijk ). Furthermore, although the MCPs are kept purged with dry nitrogen as much as possible before flight, they are exposed to the atmosphere at least once between ground calibration and orbit (at the launch site) which may affect their performance.

19.2.2 Calibration Parameters: HEEA and LEEA The HEEA and LEEA sensors are intended to be identical, except for having different geometric factors (G) due to a different mechanical design for the electrostatic analyser entrance (see [3]). All eight sensors use the same equipment to control electron energy selection and to count detected electrons. Care was taken to make the electrostatic analysers of all the HEEAs as mutually identical as possible, and similarly for the LEEAs. The least controllable aspect of the design is the efficiency

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."ik / of the individual micro-channel plate (MCP) detectors in each sensor. The calibration parameters mentioned above were measured in a test chamber to ensure that the individual sensors were well characterized and that their performance was identical to within specified tolerances before the instruments were accepted for flight.

19.2.3 Calibration Correction Factors Three aspects of the instrument calibration were expected to vary during flight operations. The detector efficiency was expected to decline over time, and to require occasional correction by using increased voltage levels across the MCP. The bulk velocity (determined by integration of fijk collected during each spin) was expected to possibly exhibit errors in the spin axis component due to errors in the determination of the relative sensitivity of the anodes; even small errors in inter-anode calibration could cause large errors in the bulk velocity measurement. The detector sensitivity was also expected to respond by under-counting in sufficiently high flux environments, and ground tests of flight detectors suggested this could sometimes affect HEEA (though not usually LEEA) in the magnetosheath. This scenario can be discussed in terms of additional factors in the expression for detector sensitivity, as follows "ik D ˛"0 ˇik " vk 2 i ijk where ˛.t/ is a time dependent correction factor for "0 , used to describe the effect of sub-optimal detector efficiency (equally for all anodes), ˇik represents corrections to " vk 2 i , the relative sensitivity of different parts of the detector, which may in principle vary with energy and ijk represents possible under-counting due to detector saturation in high flux environments (not to be confused with electronic dead time, which sets in at higher count rates). These parameters (˛, ˇ, ) were each equal to 1 in ground test conditions, when the MCP gain was well above 2 106 electrons and beam fluxes were not strong enough to cause detector saturation. In practice, as we will discuss below, we have found that the ˇik term shows dependence on the detector sensitivity, and thus a more elegant formulation of the problem might involve merging the ˛ and ˇ terms.

19.2.4 Relationship Between Calibration Parameters and Moments It can be shown that the plasma velocity (second order moment of f .v/) is independent of geometric factor and instrument sensitivity terms G˛"0 , but is dependent

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on the relative sensitivity of different parts of the detector, i.e, the terms ˇik " vk2 i . Therefore, achieving plasma bulk flow vectors in agreement with independent measurements from other instruments is a good test of successful determination of the ˇik " vk2 i terms. It can also be shown that the plasma density is inversely proportional to the G˛"0 terms, as well as having a more complex dependence on ˇik " vk2 i . Thus accurate densities from PEACE show that all calibration factors are well characterized, including time dependent detector efficiencies. Conversely, to isolate the correct value for "0 (discussed further in Section 19.3.4) requires that ˛ and ˇ and all other calibration factors have been properly determined, that a reliable reference for the electron density is available and that proper moments calculations have been performed (see Section 19.3.1).

19.3 PEACE In-flight Calibration Method In-flight calibration is required to refine knowledge of "0 , and to keep track of (and provide corrections for) changing MCP detector efficiency. Calibration corrections are validated by determining bulk properties of the plasma and comparing them with measurements of the same parameters by instruments which use different techniques. If successful, the process also establishes that the majority of the calibration parameters were satisfactorily determined during ground tests (and that they are still applicable after the instrument has been strongly vibrated during launch).

19.3.1 Note on Determination of Electron Moments In this paper we will discuss electron density and velocity moments data. In all cases, these have been produced by performing moments calculations using transmitted 3-D data (most commonly 3DR), and they are not onboard-calculated moments. These moments are similar to the CAA Moments dataset (i.e. the first release of Moments data, which is the one available at the time of writing), although in some cases they are calculated for a single sensor only, while CAA Moments use data from both sensors. They have been calculated using PEACE Calibration version 5.1. They have been calculated using a correction to the measured energy to account for plasma electron acceleration by the spacecraft potential .Vsc /, which assumes that the true potential is 1 V greater than VEFW , the measured difference between the probe potential and the spacecraft potential, provided by the electric field instrument (EFW). In addition, electrons with measured energies in the energy bin that contains VEFW , and in the energy bin above that, have been assumed to be spacecraft photo-electrons and have not been included in the moments integration. It is worth noting that the conversion from VEFW to Vsc by adding 1 V was recommended by members of the EFW team, and that their recommendation has been

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recently revised in the light of a recent study by Cully et al. [1] who showed that for tenuous plasmas such as the magnetotail lobes and plasmasheet, where the Debye length is long compared to the EFW boom length, VEFW underestimates Vsc by 19%. We may reformulate the Cully et al. results to express the spacecraft potential as Vsc D 0:86 1:24 VEFW recalling that VEFW is provided as a potential difference which is negative for a positively charged spacecraft (the expression also accounts for the 0.7 V voltage offset needed to balance the typical bias current used by Cluster EFW). It is interesting to note that the 25% larger value is in accordance with our estimates of spacecraft potential made using PEACE spectra alone (not shown here). Future calibrations will use PEACE moments which have been determined using this expression, where appropriate. It may be that when this formulation is in use, spacecraft photo-electrons will not be seen in the energy bin above the energy bin containing the inferred spacecraft potential. Care has been taken to isolate events for use in calibration analysis for which the relevant electron plasma population is fully sampled (e.g., it does not extend to higher or lower energies than those measured by PEACE). The plasma regions used are usually the magnetosheath and the magnetotail plasmasheet. Background counts have been ignored since their fluxes are considered to be negligible compared to the magnetosheath or plasmasheet electron fluxes in the sensor energy range (and events with high background count rates from, e.g., solar energetic particles, have not been included).

19.3.2 Determination of ˛ Correction Factors As a first step, it was essential to correctly assess the contribution of the ’ term, based on the detector sensitivity time history which we constructed using data from weekly tests of PEACE sensor performance. These tests are performed by setting both sensors to observe the same energy range, and then varying the MCP voltage on one sensor while keeping the other sensor at normal operating voltage. The process is then repeated with the roles of the sensors exchanged. The response of the measured count rate to increasing voltage in the test sensor can separated from count rate changes due to variations in the plasma environment using data from the second sensor. Note that data from other instruments such as WHISPER is not used in this procedure. Figure 19.1 provides an example of the time history of ’ for the Cluster 2 PEACE sensors. The variations in detector efficiency reflected here are due to a competition between the degrading effects of exposures to high electron fluxes (e.g., magnetosheath intervals), and the compensating effects of raised MCP voltage levels, complicated by a change of the PEACE operations plan from 2003, which exposed the sensors to higher fluxes less frequently.

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Fig. 19.1 The plot shows the time history of the ’-factor for the Cluster 2 HEEA (below) and LEEA (above) sensors, together with the time history of the MCP levels used in normal operations (proxy for the voltage across the MCP). The main point to note is that the alpha factor which is ideally 1 has been held near 1 in the later years, but in the early years of the mission it tended to decline in the early part of each year, especially for HEEA, until the MCP level was raised. The sensitivity decline was associated with prolonged exposure to high fluxes in the magnetosheath and solar wind. The exposure to high fluxes has been limited in the later phase of the mission either by deactivating the sensor in such regions (according to a duty cycle) or by operating the sensors with lowered MCP voltages in those regions. The lowered MCP levels are not shown on the MCP level plots (upper panels), but their consequences (two sets of crosses per day) are apparent in the ’-factor plots, especially in early 2005. The curves for other sensors (not shown) exhibit similar features, though in some cases (particularly Cluster 3 and 4) the ’-factor values are not always so close to 1 later in the mission

19.3.3 Determination of ˇ Correction Factors Our approach to estimating inter-anode relative sensitivity corrections is based on the requirement that when measuring gyrotropic pitch angle distributions which are varying only on long timescales, the same pitch angle may be observed by more than one anode for a sensor on a spinning spacecraft, and all such anodes should provide the same measured values of fluxes (in scientific units) at that given pitch angle. The principle may be applied across the full pitch angle range. This general type of approach is also used for the CIS-CODIF sensors (see, for example, [4]). Our study applied this principle in a large scale automated approach, testing each measured energy at which the count rate was considered acceptable, for all spins of

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data from data intervals where the plasma was selected to be relatively steady and with suitable temperature anisotropy. Temperature anisotropies in the range 0:95 < Tjj =T? < 5 (but commonly near 1) were used, provided they remained steady to within ˙0:05 during chosen intervals; such intervals ranged in duration from 20 to 360 s. The study focused on 3DR and 3DXP data, from which ground moments are usually calculated (see the companion paper on PEACE data products, Fazakerley et al., Chapter 8 of this book). The resulting correction factors ˇik were organized by energy and anode. In our initial studies, moments data produced using these calibrations were not very satisfactory. It was then recognized that the correction factors ˇ lso showed a dependence on ’. Therefore, by applying the appropriate correction factors for a given anode, energy and ’ (itself a function of time), the corrected calibrations could be used to produce moments which showed much improved accuracy (see Section 19.4.1). Note that while we will validate this method by examining the statistics of v?z values determined using our improved calibrations, the method does not make use of moments and in particular does not seek to minimize the average value of v?z .

19.3.4 Determination of "0 Calibration Parameter The absolute detector efficiency "0 was determined using comparisons of density measurements between PEACE and the plasma wave instrument WHISPER. Only when the ˛ istory is available, together with ˇ.˛/ is it possible to obtain a time independent value for "0 , through cross calibration with WHISPER (see Section 19.2.4). Our density reference was a large set of WHISPER electron density data during all magnetosheath and solar wind data intervals in 2001 and 2002, provided via the CAA. PEACE electron density moments were calculated using data from the LEEA sensors (to minimise the risk of count rate saturation which is greater for HEEA sensors) and applying ’ and “ factor efficiency corrections and a preliminary value of "0 . Figure 19.2 shows a quite narrow and tall histogram of ratios of PEACE/WHISPER densities, peaking near 0.8 for the particular case of Cluster 1 LEEA. The preliminary value of "0 was subsequently reduced so as to shift the peak to a value of 1. The new value of "0 is used in the updated calibration dataset. For events where the HEEA sensor also fully covered the energy range occupied by these solar wind and magnetosheath plasmas, the HEEA ©0 value was similarly adjusted to ensure agreement of HEEA, LEEA and WHISPER densities. There was no systematic attempt to filter out cases where ijk is less than 1, but some cases where a problem was clearly apparent were removed. The process was repeated for all four spacecraft. To illustrate how well the overall calibration (including all parameters mentioned in Sections 19.2.1 and 19.2.3) works, and how similar the results from the HEEA and LEEA sensors are, we present in Fig. 19.3 the ratio nL =nH of densities measured in the same band of energies in the same plasma by LEEA and HEEA. The plot covers 6 years (compared to the 2 year interval used for determining "0 ) and

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Fig. 19.2 Illustration of the approach used to correct the ©0 absolute detector efficiency parameter. PEACE LEEA densities are calculated using efficiency corrections related to detector gain variations (’ and “), with a value for ©0 produced during ground calibration. A comparison is then made with densities determined by WHISPER. The examples here are Cluster 1 data from magnetosheath and solar wind intervals in 2001 and 2002 (using CAA WHISPER data). The most frequently occurring ratio of PEACE LEEA to WHISPER densities, indicated by the histogram peak, shows the discrepancy associated with imperfect knowledge of ©0 and can be used to determine the correct value of ©0

shows that the inter-calibration is usually very good, with the ratio being 1 ˙ 0:02 for much of the time. The main exceptions are intervals in the spring of years 2001, 2002 and 2003 where the ratio is sometimes >1, consistent with undercounting by HEEA in the high fluxes of the magnetosheath, i.e., cases when ijk < 1. After 2003, the HEEA sensors were used less frequently in the solar wind and magnetosheath. At present, we simply flag time intervals in the PEACE CAA files where may depart from 1 and do not attempt a correction.

19.4 Assessment of PEACE Calibrations 19.4.1 Effect of Inter-anode Sensitivity Corrections In order to discuss bulk velocity measurements, we will focus on v? , the velocity vector perpendicular to the local magnetic field, as it can be measured well by other instruments, facilitating comparisons (see below). Comparisons of the full velocity

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Fig. 19.3 The effectiveness of the HEEA/LEEA relative calibration is illustrated for Cluster-1 in this plot comparing densities nL =nH . For each case, the density is calculated using 3DR data transmitted to the ground, applying the v5.1 calibrations in use at CAA at the time of writing, and applying corrections for spacecraft potential and removal of spacecraft electrons. The density nL is calculated using LEEA data in the energy overlap region while the density nH uses HEEA data in the overlap region. Thus any difference between the two densities is expected to be due to differences in calibration of the energy overlap region. Generally the ratio is very satisfactory, and lies within 1% or 2% of a perfect result, though there are some exception. The most obvious exceptions are in the early months of 2001, 2002 and 2003, when the HEEA sensor was used in the magnetosheath. Some of the magnetosheath events had sufficiently high fluxes that the HEEA sensor saturated and returned too few counts, hence leading to a density underestimate and a ratio >1. These may be considered as examples of situations where ” < 1 (see Section 19.2.3). For this reason, the CAA Moments data product uses the LEEA data in the energy overlap region

vector between, e.g. ion and electron instruments, may be less successful, for example if there are electron beams but not ion beams travelling along the magnetic field at the spacecraft location. We stated earlier that poor inter-anode calibrations give rise to significant errors in the spin axis component of the velocity vector, v?z . Figure 19.4 shows histograms of values of v?z for the four PEACE-HEEA sensors, using the uncorrected calibration values for " vk 2 i . The datasets are 208 selected quiet magnetotail plasmasheet intervals from 2001–2003. Corresponding data is also provided from CIS-CODIF on spacecraft C1 and C4 (see Section 19.4.3 for further details). The CIS histograms peak around 0 km/s and have a full width at half maximum of roughly 100 km/s. It is clear that the distribution of v?z is not consistent amongst the four PEACE-HEEA sensors, and nor do the distributions resemble those from CIS (with the possible exception of C1).

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Fig. 19.4 Illustration of the quality of spin-axis components of v? from PEACE-HEEA (red) and CIS-CODIF (blue) for a set of 208 magnetotail plasmasheet intervals during 2001–2003 BEFORE improvement of PEACE inter-anode relative calibrations, “. The plots use moments calculated from 3D data collected by the HEEA sensors

Figure 19.5 shows histograms of all three components of PEACE-HEEA v? data for a large collection of data intervals from the quiet magnetotail plasmasheet, for which moments have been calculated using the current calibration (version 5.1). The dataset ranges from 2001–2007 on C1, C2 and C4, and 2001–2005 for C3. There are a greater number of data points for spacecraft C2 due to the greater availability of 3DR data from that spacecraft, as discussed in a companion paper in this volume [? ]. For all spacecraft, and for all three velocity components, the most commonly occurring value is around zero, as expected for plasmasheet data. The results are grouped about the mean value in quite a tight distribution, typically having a range of 80–100 km/s at half maximum, and 200 km=s at 0.1 maximum. These results are similar to the CIS results of Fig. 19.4, and are much better than the PEACE results in the same figure, for which the calibration did not include ˇi k correction factors. The ˇ corrections needed when detector efficiency was similar to that used in the ground calibration are minor (not shown), confirming that the ground calibration was quite effective, but the corrections become increasingly important at smaller detector gains. Nonetheless, even relatively minor corrections were found to significantly improve spin axis velocity moment components.

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Fig. 19.5 Illustration of the quality of spin-axis components of PEACE-HEEA v? for a set of plasmasheet intervals from 2001–2007 on spacecraft C1, C2 and C4, and 2001–2005 on C3, AFTER improvement of inter-anode relative calibrations. The histograms indicate that the parameter is as well measured by PEACE as by CIS-CODIF

19.4.2 EFW-FGM-PEACE Comparisons In addition to comparisons with CIS, the v?z parameter determined by PEACE is also expected be consistent with the electric field drift velocity determined using electric and magnetic field data from EFW and FGM. The electric field is only available in the spin plane, so it is only the spin axis component of vE D ExB=B 2 , derived from spin plane components of E and B, that is well determined by this method. These data are less reliable in cases of weak magnetic field, or magnetic field vector near the spin plane. Comparisons of –vxB with individual components of E are also possible, but are not shown here. Figure 19.6 shows a set of electric field derived v?z values from 2001 provided by the CAA (only via the command line interface at the time of writing), which are available for all four spacecraft, together with the corresponding values from PEACE (using dual sensor moments). The dataset includes plasmasheet and magnetosheath intervals. The electric field derived values are also centered on 0 km/s, but show a much narrower spread, and

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Fig. 19.6 Illustration of the difference between spin-axis component of v? as determined by from ExB=B 2 and by PEACE, for magnetosheath and plasmasheet events in 2001. Note that in all cases the most commonly occurring value is 0 km/s, and that the electric field derived values show a very much narrower spread of values. A much larger number of electric field derived results are seen at small speeds, so the histograms were normalized to 1 to allow a clear comparison

when presented as an occurrence frequency histogram, a correspondingly taller peak; hence we show the two histograms together after normalization. Although the electric field derived values are often very good, it is worth recalling that the requirements on the magnetic field mean that the technique is not applicable in such a wide range of situations as those for which CIS and PEACE can measure bulk flow velocities. Also, occasionally, issues such as incorrect EFW bias currents, or cold ion wakes (or, usually less significantly, the electric field offset in the sun direction) may introduce errors which the user should be cautious about. Figure 19.7 compares the two types of v?z measurements in a specific randomly selected interval. During this rather long interval, in which the spacecraft crosses from the magnetosheath to the polar cap via the cusp, the two measurements generally agree to within 30 km/s or better, i.e., to within 20% when significant (100 km=s) flows are present.

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Fig. 19.7 Illustration of the accuracy of PEACE v?z moments for a 14 h inbound pass beginning in the magnetosheath, passing through the southern high altitude cusp and entering the polar cap. The spectrogram confirms that the LEEA sensor measured the complete energy range occupied by the magnetosheath/cusp plasma. The black trace in the spectrogram indicates the EFW probespacecraft potential energy, as a proxy for the slightly larger energy that is gained by an electron accelerated through the spacecraft potential, which must be allowed for in the moments calculation. The next panel shows the v?z values from PEACE and from the ExB method (from CAA files) in red and black. The next panel shows the difference (PEACE – ExB) between them and the lowest panels show the ratio of these two time series (PEACE/ExB). The ratio is naturally rather large where the values are very small (intervals highlighted by red horizontal bars) but where there are significant flows we see ratios in the range 1 ˙ 0:2. In all regions we see differences of order only 20–30 km/s

19.4.3 CIS-PEACE Comparisons As has been shown in Fig. 19.4, a similar test can be carried out using ion velocity measurements from the CIS experiments, although not for all spacecraft. CIS is inoperative on C2 and does not provide reliable v?z on C3 except during the early part of the mission. The v?z parameter is used as a measure of the local convection speed of magnetic flux, which should be the same for ions and electrons that are all “frozen-in” to the local magnetic flux.

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Fig. 19.8 Illustration of the difference Œv?z CODIF Œv?z PEACEHEEA , showing results for current version 5.1 calibrations (green) and earlier version 4 calibrations (red). Note that the difference histogram shows a similar spread to the histograms of CODIF and HEEA data in Figs. 19.4 and 19.5, suggesting that the spread is due to fluctuations which are un-correlated between PEACE and CIS

The CIS measurements have been calibrated by the CIS team, in a similar way to PEACE, prior to this comparison (see [4]). The ion moments used were calculated using the CIS team “cl” software for CODIF on C1 and C4. This dataset was not checked to eliminate cases where perfect agreement is not expected, such as when the CIS or PEACE moments are calculated using incomplete coverage of the range of energies occupied by the plasma energy distribution. Figure 19.8 shows residuals Œv?z CODIF Œv?z PEACE calculated for each of the 208 plasmasheet intervals, using the present (v5.1) and previous (v4) PEACE calibration datasets, for the same intervals as in Fig. 19.4. The improvement in the PEACE results due to the v5.1 calibration is clear. The residuals histogram shows a similar spread to that of the CODIF histogram (Fig. 19.4) and the PEACE histograms (Fig. 19.5). This suggests that the v?z values are not correlated between the sensors, and that both represent a degree of random scatter about the “true” value of v?z . If the measurements had all been “perfect” so that the histogram represented a range of conditions represented in the plasmasheet, the residuals would have been zero, unless differential flows associated with electric current were present. On the other hand, this scenario is inconsistent with the narrow spread of values we see in the electric field based v?z (Fig. 19.6).

19.4.4 PEACE-WHISPER Comparison Figure 19.9 shows a comparison of electron density values determined by PEACE and by WHISPER, from a randomly selected magnetosheath interval. The data files were sourced from the CAA. The difference between the two datasets is typically less than 1 cm3 , and the ratio between them shows agreement to within 5%.

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Fig. 19.9 Illustration of the accuracy of PEACE density moments for a 1 h magnetosheath interval. The spectrogram confirms that the LEEA sensor measured the complete energy range occupied by the magnetosheath plasma. The black trace indicates the EFW probe-spacecraft potential energy, as a proxy for the slightly larger energy that is gained by an electron accelerated through the spacecraft potential, which must be allowed for in the density calculation. The next panel shows the PEACE and WHISPER densities (from CAA files) in red and black. The lower panels show that the ratio of these two time series is generally around 95%, sometimes closer to 100%. The intervals where the ratio departs significantly from 1 are periods of elevated spacecraft potential, and the WHISPER CAA file quality factor is rather low here, indicating less reliable density determination from the WHISPER wave data

There is an ongoing activity to seek useful test intervals in higher energy plasmas for which reliable density is available from WHISPER or WIDEBAND, but far fewer satisfactory intervals are available than for the magnetosheath, as the density tends to be too low for these instruments to give accurate results (e.g. see Masson et al., Chapter 18 of this book). Although we have no reason to think that there is a problem at higher energies, density comparisons for cases with electron energies in the plasmasheet range would complete the in-flight validation of the calibration across the full PEACE instrument energy range.

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19.4.5 PEACE-RAPID Comparisons In order to investigate the inter-calibration of PEACE and RAPID-IES, some preliminary studies have been carried out, using comparison plots such as the example shown in Fig. 19.10. The measurements made by IES were made at the same time as the PEACE measurements. We make the reasonable assumption that the same plasma population is being measured both the top of the PEACE energy range and in the IES range, so that the spectral gradient is expected to be the same according to both instruments. The two parallel green guidelines in the figure show that a common gradient can be seen. The only PEACE points which do not follow the trend well are interpreted as being at energies where the signal falls below instrument background. The general conclusions are that the results based on the existing

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instrument calibrations, without any inter-calibration adjustments, are already quite good (although how good has not yet been quantified). It is clear from the figure that when making such comparisons one needs to be aware of the background count level in PEACE data since the plasma fluxes are often relatively low at the high energy end of the PEACE energy range. The studies have also shown that some care is needed in treating the low energy end of the IES energy range. This work is expected to be discussed in more detail elsewhere.

19.4.6 PEACE Inter-instrument Comparisons Figures 19.11 and 19.12 illustrate good relative accuracy between the 4 Cluster PEACE instruments for randomly selected magnetosheath and plasmasheet burst mode intervals, using the CAA PEACE (version 1) dual sensor Moments data product. As in earlier figures, v? is used to avoid differences that might arise if there are magnetic field-aligned beams at some spacecraft and not others. Exact agreement

Fig. 19.11 Illustration of the relative accuracy of CAA PEACE Ver1 moments for randomly selected 1 h burst mode (BM) telemetry intervals in the magnetosheath. Spacecraft separation is 200 km. Data traces use the usual colour code: C1 black, C2 red, C3 green, C4 blue. Moments data from C1 and C3 is less frequent than spin rate, even though this is BM, as complete 3D distributions from both PEACE sensors are not available for each and every spin. Agreement is quite good in all parameters

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Fig. 19.12 Illustration of the relative accuracy of CAA PEACE Ver1 moments for randomly selected 1 h burst mode (BM) telemetry intervals in the magnetotail plasmasheet. Spacecraft separation is 4;000 km: Data traces use the usual colour code: C1 black, C2 red, C3 green, C4 blue. Moments data from C1 and C3 is less frequent than spin rate, even though this is BM, as complete 3D distributions from both PEACE sensors are not available for each and every spin. Agreement is quite good in all parameters

is not expected as the spacecraft are not perfectly co-located (200 km apart in the magnetosheath case and 4;000 km: apart in the plasmasheet case). Nonetheless, values are generally very similar and the time series show the same trends between spacecraft. The CIS data (not shown) exhibit very similar behaviour, including the unusual variations in the y and z components of the magnetosheath flow in Fig. 19.11 (probably related to solar wind current sheets transiting the magnetosheath) and the enhanced plasmasheet flows near 09:18 UT in Fig. 19.12.

19.5 Summary Our paper has briefly described the PEACE calibration parameters and our approach to improving them through in-flight calibration work. It is outside the scope of this paper to provide a detailed account of the inter-calibration methods. Validation of the calibrations using comparisons with datasets from other Cluster instruments is also demonstrated.

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We include examples showing CAA PEACE moments data which show good agreement (to within a few 10’s km/s) between the (difficult to determine) spin axis component of v? and the values derived from electric and magnetic field data, and magnetosheath electron densities that agree within 5% of densities derived from plasma wave instruments. We also provide evidence of effective inter-sensor inter-calibration and effective inter-calibration between PEACE instruments on the 4 Cluster spacecraft. Acknowledgments The authors thank ESA and STFC for funding. We are also grateful to other Cluster instrument teams and the CAA team for their support.

References 1. Cully, C.M., R.E. Ergun and A.I. Eriksson, Electrostatic structure around spacecraft in tenuous plasmas, J. Geophys. Res., 112, A09211, doi:10.1029/2007JA012269, 2007. 2. Henderson, P.D., C.J. Owen, A.D. Lahiff, I.V. Alexeev, A.N. Fazakerley, L. Yin, A.P. Walsh, E.A. Lucek, and H. Reme, The relationship between jxB and div(Pe) in the magnetotail plasma sheet: Cluster observations., J. Geophys. Res., 113, A07S31, doi:10.1029/2007JA012697, 2008. 3. Johnstone A.D., C. Alsop, S. Burge, P.J. Carter, A.J. Coates, A.J. Coker, A.N. Fazakerley, M. Grande, R.A. Gowen, C. Gurgiolo, B.K. Hancock, B. Narheim, A. Preece, P.H. Sheather, J.D. Winningham, and R.D. Woodliffe, Peace: A Plasma Electron and Current Experiment, Space Sci. Rev. 79, pp. 351–398, 1997. 4. McFadden et al., In-flight Instrument Calibration and Performance Verification, in Calibration of Particle Instruments in Space Physics, M. Wuest, D.S. Evans and R. von Steiger (Editors), ISSI Scientific Report SR-007, International Space Science Institute, Bern, 2007.

Chapter 20

Generation and Validation of Ion Energy Spectra Based on Cluster RAPID and CIS Measurements Elena A. Kronberg, Patrick W. Daly, Iannis Dandouras, Stein Haaland, and Edita Georgescu

Abstract We present a method to combine spectral information from the Cluster RAPID (Research with Adaptive Particle Imaging) and CIS (Cluster Ion Spectroscopy) instruments. Preliminary results from the magnetotail show that the kappa distribution can fit the ion distributions in the magnetotail, for example in thin plasma sheets during quiet and disturbed times with kappa factors '4.4 and '10, respectively. With the most recent RAPID and CIS/CODIF calibration files the average ratio of CIS fluxes (approximated using the kappa-fit to the effective energy of the first RAPID energy channel) to the RAPID fluxes at the first energy channel is about 0.74 ˙ 0.24. This result is perfectly acceptable for these two experiments, based on two very different measurement principles, therefore no further spectral shift or recalibrations are needed.

20.1 Introduction Knowledge about the spectral distribution of a particle populations provides important information about e.g. acceleration and diffusion processes. For instance, earlier studies indicate that the kappa distribution (a Maxwellian core with a power law tail) rather than the Maxwellian will lead to enhanced wave growth [10, 12]. Sarris et al. [9], using IMP-7 and eight spacecraft data, have reported on plasma sheet ion distributions over the energy range 0.1 keV to a few MeV in the distant terrestrial magnetotail. They found that during periods of low bulk velocity the ion

E.A. Kronberg (), P.W. Daly, S. Haaland, and E. Georgescu Max-Planck Institute for Solar System Research e-mail: [email protected]; [email protected]; [email protected]; [email protected] I. Dandouras CESR, Université de Toulouse / CNRS, Toulouse, France e-mail: [email protected] S. Haaland University of Bergen, Norway


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distribution is often best characterized by a Maxwellian but with a high energy (50 keV) tail described well by a power law (/E ). A case study of the thermal and suprathermal protons in the Earth’s quasistable plasma sheet over the energy range 13 keV to 1 MeV has been made by Ipavich and Scholer [5] using ISEE-1 data. They reveal that the temporal behaviour of suprathermal ions in the plasma sheet is a complex one, with numerous energy-dependent structures. The typical spectral shape is: a thermal component below 16–19 keV that has the Maxwellian distribution, but the high energy spectrum departs from the Maxwellian extrapolation. The suprathermal distributions fall off steeply beyond 100–200 keV with a high-energy component extending up to 1 MeV. Christon et al. [1, 2] using ISEE 1 data have reported on plasma sheet ion distributions over the energy range 0.1 keV to a few MeV. They find that during periods of low bulk velocity the ion distribution is often best described by a kappa distribution. Further studies by Christon et al. [3] reveal that the spectrum observed during disturbed geomagnetic conditions typically is complex and cannot be represented in general by a single functional form, as during quiet periods when it can be represented by the kappa distribution function. A power law form most able to approximate the shape at higher energies and a Maxwellian form most able to approximate the shape near the knee,1 can be used to characterize the observed distribution. The purpose of this paper is to present a method to fit Cluster ion data to a kappa distribution and to show how it works for different applications. We show the specific of the spectral fitting for the Cluster data, over the combined energy range of the RAPID/IIMS and the CIS/CODIF experiments. The results can be used further for the spectral studies.

20.2 Data and Methodology The measurements of the proton fluxes are obtained by two particle experiments: RAPID/IIMS (Imaging Ion Mass Spectrometer) for the higher energies and CIS/CODIF (Composition and Distribution Function) for the medium and lower energies. The centerpiece of the IIMS is a spectrometric camera for neutral and ion composition. This is a miniature telescope composed of a time-of-flight and an energy detection system which allows us to distinguish different species [11]. The instrument measures 3D distribution of ions and covers the energy range from 27.7 to 1,500 keV for the protons. The CODIF instrument is a high-sensitivity mass-resolving spectrometer which measures full 3D distribution functions of different ion species [8]. The spectrometer combines ion energy per charge selection, by deflection in a rotationally symmetric toroidal electrostatic analyser, with a subsequent time-of-flight analysis. The energy range of CODIF is 0–40 keV/q. 1 The knee is that portion of the spectrum where flux begins to roll over and decrease rapidly with increasing energy [3].

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These two instruments have an energy overlap which allows us to intercalibrate and verify the data quality. The overlapping channels are the 29–37 keV (CODIF) and 28–64 keV (IIMS). The first six CIS channels are not used as their fluxes are often very scattered (presence of different plasma populations). The RAPID/IIMS instrument has three detector heads which cover the full range of 0–180ı in the polar direction. Unfortunately the central head (60–120ı) has been degraded by sunlight and doughnut shaped data gap appears in the 3D ion distribution. We tried to compensate for this effect by removing measurements from the corresponding part of the CODIF sensor. However, unless the distributions were extremely anisotropic this correction had little effect on the energy spectra above approximately 2 keV. We therefore decided to use the full directional range of CODIF for the fitting. The kappa distribution can be written as follows (taken from Krimigis et al. [6])

. C 1/ n jv Vj2 1C f .v/ D 3=2 3 3=2

. 1=2/ !0 !02

!.C1/ (20.1)

where n is the particle density, v the particle velocity, V is the bulk velocity, is the kappa-distribution power law spectral index, is the Gamma-function and the most probable speed, is given by p

. 1=2/ 1=2 !0 D 2kTH =M . 3=2/

(20.2)

where TH is the temperature of the plasma at E 1 keV, M is the particle mass and k is the Boltzmann constant. When v V the spectrum approaches a power law in energy and the Maxwellian distribution is a special case of expression (20.1) as ! 1:

20.2.1 Fitting Method The fit is obtained by minimization of the difference between the observed fluxes and the values of the kappa fit at the same energies using the following function gD

X .fobs .v/ fexp .v//2 N.N 1/fobs .v/

(20.3)

where fobs .v/ is the observed flux, fexp .v/ is the kappa-fit, and N is the number of fitted points. Therefore we get basically chi-square criteria. The minimization was done using Powell’s direction set method [7]. As free parameters of the kappa-fit we used and kTH : The plasma density and the bulk velocity are defined using CIS/CODIF data and the integration method explained in the CIS-CAA Interface Control Document (ICD) – see Dandouras and Barthe [4].

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For lower energies, i.e., most of the CODIF energy range, the bulk motion, V, constitutes a significant part of the total velocity. Prior to fitting, we therefore transform the CIS data into the bulk flow frame. For RAPID, on the other hand, the bulk velocity is negligible compared to the gyro motion, and no such correction has been made.

20.3 Examples Figure 20.1 shows two examples of the kappa fit in the thin plasma sheet during a quiet and a disturbed time. The data are plotted in the flow frame and fitted using energy channels with energies from 1 keV to 4 MeV. One can see significant temperature and spectral index increases during the substorm time. The value of the 4:4 for the quiet time is comparable with the typical values 4–8 derived for the quiet times by Christon et al. [2]. During the disturbed time 10 is in the range of the observed values during disturbed geomagnetic conditions from 3 to 11. We also compared the derived kTH with the temperature obtained from moment calculations. During disturbed time conditions (right panel) the peak of the spectra is shifted, and we obtain a temperature kTH 10:5 keV. For comparison, the CIS moments give 13 keV. During quiet conditions (left panel), we obtain a temperature at 3 keV (CIS moments: 4.7 keV). 10:52:30

23:24:29 106

106

Hydrogen flux, [1/cm2 sr s keV]

Quiet

Disturbed

105

105

104

104

103

103

102 101 100 0.01

102

κ = 4.36 kT = 2.98

0.1

101

1

10

100 1000

100 0.01

κ = 9.71 kT = 10.53

0.1

1

10

100 1000

Energy, [keV]

Fig. 20.1 Example of energy spectra and kappa-fit for the periods: on 20 September 2002, 23:24– 23:25 UT, SC1, during the quiet time in the thin plasma sheet (left) and on 17 September 2003, 10:52–10:53, SC1, during substorm in the thin current sheet. For both examples we fitted the CIS data from 1 keV. The diamonds are the joint CIS/CODIF and RAPID/IIMS data and the thick solid lines are the kappa-fit. kT is in keV

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20.4 CIS/CODIF and RAPID/IIMS Cross-Calibration The original purpose of this study was to accent the cross-calibration between CIS/CODIF and RAPID/IIMS instruments. The RAPID/IIMS particle fluxes of the lowest energy channel can not be directly compared with CIS/CODIF particle fluxes of the highest energy channel due to their nonsymmetric energy overlapping. The method described above was applied to the CIS/CODIF data in order to be able to compare particle fluxes at the same energies. Events in the plasma sheet region for 2002–2005 are investigated. The results show that the RAPID ion fluxes and CIS ion fluxes are consistent with each other, and do not have a difference in order of magnitude as it was before using direct comparison of the overlapping channels and old calibrations. With new RAPID calibration files and the most recent CIS/CODIF calibration files the average ratio of CIS fluxes (approximated using the kappa-fit to the effective energy of the first RAPID energy channel) to the RAPID fluxes at the first energy channel (27.7–64.4 keV) is about 0.74 ˙ 0.24. Here we applied the kappa-fit only to the higher CIS channels (5.5–38.3 keV) in order to improve the reliability of the approximated overlapping channel. More detailed information on the ratios can be seen in Table 20.1. This result is perfectly acceptable for these two experiments, which are based on two very different measurement principles; (solid state detectors in RAPID versus electrostatic analysers in CODIF). It should be also taken into account that CODIF detects only positive ions whereas RAPID is sensitive to both ions and energetic neutral atoms. We therefore conclude that no further spectral shift or recalibrations are needed.

20.5 Summary and Outlook In this paper we applied the kappa-distribution fit to the joint CIS/CODIF and RAPID/IIMS spectra. Kappa-fit works quite well for the energy range between 1 and 600 keV in the terrestrial magnetotail and gives consistent results for the combined measurements of the two experiments. At the same time there are a number of cases when this fit does not work, for example in thick plasma sheets or during ion beams.

Table 20.1 Ratios of the CIS fluxes (approximated using the kappa-fit to the effective energy of the first RAPID energy channel) to the RAPID fluxes at the first energy channel (27.7–64.4 keV). Data from SC3 were not used for analysis after 2003 because half of anodes on the CODIF instrument were not working satisfactory Year C1 C3 C4 2002 0.69 ˙ 0.09 (15 events) 0.62 ˙ 0.44 (31 events) 0.8 ˙ 0.09 (16 events) 2003 0.8 ˙ 0.17 (20 events) 1.1 ˙ 0.09 (34 events) 2004 0.76 ˙ 0.15 (31 events) 0.95 ˙ 0.19 (27 events) 2005 0.61 ˙ 0.13 (35 events) Average 0.75 ˙ 0.13 (66 events) 0.62 ˙ 0.44 (31 events) 0.86 ˙ 0.15 (112 events)

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The problem with the central head at the RAPID does not significantly affect the results of the kappa-fit. Therefore the CIS data are approximated without removing the corresponding data gap. However, cases with strong anisotropy should not be fitted with the kappa-fit and it is recommended to study them separately. The methods described in this paper will be used for the survey of the spectral characteristics and its dependence on solar wind parameters in the terrestrial magnetosphere. Acknowledgements We thank A. Barthe for preparation of the CIS data.

References 1. Christon S.P., Mitchell D.G., Williams D.J., Frank L.A., Huang C.Y., Eastman T.E.: Energy spectra of plasma sheet ions and electrons from about 50 eV/e to about 1 MeV during plamsa temperature transitions. J. Geophys. Res. 93, 2562–2572 (1988) 2. Christon S.P., Williams D.J., Mitchell D.G., Frank L.A., Huang C.Y.: Spectral characteristics of plasma sheet ion and electron populations during undisturbed geomagnetic conditions. J. Geophys. Res. 94, 13,409–13,424 (1989) 3. Christon S.P., Williams D.J., Mitchell D.G., Huang C.Y., Frank L.A.: Spectral characteristics of plasma sheet ion and electron populations during disturbed geomagnetic conditions. J. Geophys. Res. 96, 1–22 (1991) 4. Dandouras I., Barthe A.: Cluster Active Archive: Interface Control Document for CIS. ESA document CAA–CIS–ICD–0001 (2007). Latest version available at http://caa.estec.esa. int/documents/ICD/CIS CAA ICD V2.1.pdf 5. Ipavich F.M., Scholer M.: Thermal and suprathermal protons and alpha particles in the earth’s plasma sheet. J. Geophys. Res. 88, 150–160 (1983) 6. Krimigis S.M., Carbary J.F., Keath E.P., Armstrong T.P., Lanzerotti L.J., Gloeckler G.: General characteristics of hot plasma and energetic particles in the Saturnian magnetosphere - Results from the Voyager spacecraft. J. Geophys. Res. 88, 8871–8892 (1983) 7. Press W.H., Teukolsky S.A., Vetterling W.T., Flannery B.P.: Numerical Recipes in C: The Art of Scientific Computing (Second Edition), chap. 10.5. Cambridge University Press (1992) 8. Rème H., Aoustin C., Bosqued J.M., et al.: First multispacecraft ion measurements in and near the Earth’s magnetosphere with the identical Cluster ion spectrometry (CIS) experiment. Annales Geophysicae 19, 1303–1354 (2001) 9. Sarris E.T., Krimigis S.M., Lui A.T.Y., Ackerson K.L., Frank L.A., Williams D.J.: Relationship between energetic particles and plasmas in the distant plasma sheet. Geophys. Res. Lett. 8, 349–352 (1981) 10. Thorne R.M., Summers D.: Enhancement of wave growth for warm plasmas with a high-energy tail distribution. J. Geophys. Res. 96, 217–223 (1991) 11. Wilken B., Daly P.W., Mall U., et al.: First results from the RAPID imaging energetic particle spectrometer on board Cluster. Annales Geophysicae 19, 1355–1366 (2001) 12. Xiao F., Zhou Q., He H., Zheng H., Wang S.: Electromagnetic ion cyclotron waves instability threshold condition of suprathermal protons by kappa distribution. Journal of Geophysical Research (Space Physics) 112, 7219–+ (2007). doi10.1029/2006JA012050

Part IV

Magnetospheric Missions

Chapter 21

The Cluster Mission: Space Plasma in Three Dimensions M.G.G.T. Taylor, C.P. Escoubet, H. Laakso, A. Masson, and M.L. Goldstein

Abstract At the time of writing, Cluster is approaching 8 years of successful operation and continues to fulfill, if not exceed its scientific objectives. After a nominal mission lifetime of 2 years Cluster currently in its extended mission phase, up to June 2009, with a further extension request submitted for a further 3.5 years. The primary goals of the Cluster mission include three-dimensional studies of smallscale plasma structures and turbulence in the key plasma regions in the Earth’s environment: solar wind and bow shock, magnetopause, polar cusps, magnetotail, and auroral zone. During the course of the mission, the relative distance between the four spacecraft is being varied to form a nearly perfect tetrahedral configuration at 100, 250, 600, 2,000, 5,000 and 10,000 km inter-spacecraft separation targeted to study scientifically interesting regions at different scales. In the last few years, the constellation strategy has moved towards a multi-scale concept, enabling two scale sizes to be investigated at the same time. In these cases, three spacecraft are separated by 10,000 km with the last spacecraft separated from this plane by varying distances from 16 km up to several 1,000 km. This configuration is targeted at boundaries, with the plane of the large-scale triangle parallel to the plane of the boundary and the final spacecraft separated a small distance from the main triangle in the normal direction. In this paper, we provide a brief overview of the mission concept and implementation and highlight a number of Cluster’s latest science results, which include: the first observation of three dimensional (3-D) surface waves on the bow shock, the first 3-D analysis of turbulence in the magnetosheath, the discovery of magnetosonic waves accelerating electrons to MeV energies in the radiation belts, along with a number of discoveries involving magnetic reconnection.

M.G.G.T. Taylor (), C.P. Escoubet, H. Laakso, and A. Masson ESA/ESTEC, D-SRE, Keplerlaan 1, 2200 AG Noordwijk, The Netherlands e-mail: [email protected] M.L. Goldstein Code 673, NASA/GSFC, Greenbelt, USA 20771


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21.1 Introduction Together with the Solar and Heliospheric Observatory (SOHO), the Cluster mission constitutes the first cornerstone of ESA’s Horizons 2000 Programme, which was presented to and subsequently selected by the ESA Science Programme Committee (SPC) in late 1985 early 1986. Cluster was first proposed in November 1982 in response to an ESA call for proposals for new scientific missions [7] as a mother and three daughter spacecraft. Economic constraints led to the four identical spacecraft being adopted and scientific arguments led to choosing a polar orbital plane to allow for observations of the polar cusp and magnetotail. In March 1988, following a (1987) joint ESA/NASA Announcement of Opportunity, 11 instruments were selected to make up the spacecraft science payload. During the following 7 years instruments and spacecraft were built, integrated and made ready for the infamous failure of the first Ariane 5 launch on 4 June 1996 when the rocket exploded 47 s after liftoff, destroying all four spacecraft. Quickly recovering from the shock of the loss, the instrument and project teams resolved to recover the mission objectives and following a number of science working team and ESA committee meetings, the Cluster team convinced the ESA SPC to rebuild the four spacecraft. In April 1997, Cluster II was born. Taking about half the time and half the cost of the original build, Cluster II was ready for launch in 2000. Even after the successful Soyuz launch of the first two Cluster spacecraft in July 2000 from the Baikonur Cosmodrome, the Cluster teams were not able to relax until after the successful launch and orbit injection of the subsequent pair in August 2000 and the instruments were finally turned on. The aim of this paper is not to review previous magnetospheric missions, but to provide an overview of the Cluster mission itself, in the scope of providing information for these proceedings focusing on orbit, spacecraft separation and instrumentation. We also discuss some recent results leading up to the Cluster/CAA workshop held in Tenerife. Finally we will briefly discuss the proposed future mission extension.

21.2 Mission The four identical spacecraft of the ESA Cluster mission provide a unique capability to study the temporal evolution of space plasma interactions in three dimensions. The near-Earth environment provides an ideal laboratory for investigating plasma interactions, transport and turbulence in a number of environments. These key regions of the magnetosphere are: the solar wind, the bow shock, the magnetopause, the polar cusp and the magnetotail. To sample these regions, the Cluster spacecraft were originally placed in a 4 19:6 RE polar orbit (orbital period 56 h), with the single spacecraft orbits designed to enable a perfect tetrahedron to be formed at particular parts of the orbit, aiming at science targets such as the polar cusps and plasma sheet (Fig. 21.1). Over the years the line of apsides has rotated further below

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Fig. 21.1 Evolution of the Cluster orbit in the x–z GSE plane during the period 2001–2009

the ecliptic, such that now Cluster crosses the ecliptic plane much closer to the Earth (Fig. 21.1). This has allowed the mission to enter regions that were not in the original mission plan (e.g. the low-latitude magnetopause, near-Earth plasma sheet, auroral acceleration regions and radiation belts), thus enhancing the originally anticipated scientific output. The separation strategy during the entire mission to date is detailed in Table 21.1 and Fig. 21.2, where during the first 5 years a perfect tetrahedron was formed twice during each orbit (purple line in Fig. 21.2). During the first 2 years of the mission, the spacecraft separation was altered approximately every 6 months. During the first extension (January 2003–December 2005) manoeuvres were limited to once per year to reduce operational costs and instrument down time and to help ensure uniform spatial coverage of scientifically interesting regions at the same magnetic local time over the calendar year. This reduction was made possible thanks to the expertise of the Flight Dynamics team from the European Space Operations Centre (ESOC), who implemented a strategy that imposed a tetrahedron during the cusp passes and then 6 months later during the magnetotail plasma sheet crossing without large-scale reconfigurations. More details of the preparation and execution of the manoeuvres can be found in Volpp et al. [30]. In 2003/2004 the Cluster mission was augmented with the launch of the Double Star mission. This mission consists of two spacecraft, the equatorial-orbiting TC-1 (550 66;970 km, 28:5ı inclination) launched on 29 December 2003 and the polarorbiting TC-2 (700 39; 000, 90ı inclination) launched in July 2004. The orbits of

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M.G.G.T. Taylor et al. Table 21.1 Cluster separation strategy split into cusp and tail seasons Year Phase Separation (km) 2001 Cusp 600 2001 Tail 2,000 2002 Cusp 100 2002 Tail 4,000 2003 Cusp 5,000 2003 Tail 200 2004 Cusp 300 2004 Tail 1,000 2005 Cusp 1,300 2005 Tail 10,000 (1,000) 2006 Cusp 10,000 2006 Tail 10,000 2007 Cusp 10,000 (450) 2007 Tail 10,000 (40) 2008 Cusp 10,000 (40) C Tilt Campaign 2008 Tail 10,000 (3,000) 2009 Cusp 10,000 tetrahedron in solar wind C 10,000 (1,000) in auroral region The figures in brackets from 2005 onwards represent the spacecraft 3 and 4 separation during the multi-scale configuration

Fig. 21.2 Detail of the Cluster inter-spacecraft separation strategy

Double Star were specifically designed to maximize the conjunction with Cluster in the plasma sheet and in the polar cusp and magnetopause. Furthermore half of the Double Star payload is made of spare or duplicate of the Cluster instruments, which has allowed full comparisons between all spacecraft to be made. TC-1 deorbited in October 2007 but TC-2 is still operating, although due to loss of attitude control it has periods of loss of contact as well as thermal issues and is expected

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to last only to the end of 2009. More information can be found in Liu et al. [12] and also Dunlop et al. [Chapter 22 of this book] where a number of the science examples are discussed, outlining the benefits of multi-mission conjunction studies and demonstrating the great success of this first ESA-China collaboration. The Cluster spacecraft separation has gradually increased over the years, allowing the same regions of the magnetosphere to be sampled at different scales. This is a one-way strategy, as the spacecraft cannot return to a small tetrahedron configuration due to diminishing fuel reserves that no longer allow substantial separation distance changes, particularly perpendicular to the direction of the orbit. However, capability does exist to move spacecraft ‘along track’ in the direction of the orbit, which has facilitated the implementation of the multi-scale operations in the second extension (since January 2006). In this configuration, three of the spacecraft (Cluster 1, 2 and 3) form a 10,000 km sided triangle, while Cluster 3 and 4, whose orbits are very similar, can be drifted with respect to one another and their separation can be varied from a few 10s of km to 10,000 km. In other words, with such minor manoeuvres only, Cluster will have fuel to continue operations for a number of years. In addition to the multi-scale concept, in May 2008 a special operation was implemented to measure the third component of the electric field along the spin axis. This was achieved by tilting Cluster 3 and Cluster 4 with respect to one another by 45ı , while they were separated by only 40 km. Preliminary data show that the third component of the electric field and in particular the electric field parallel to the magnetic field can, indeed, be measured (Y. Khotyaintsev, private communication). In addition, the possibility of localizing the source of electromagnetic waves is greatly enhanced. During the current second extension period, a mid-term review was carried out in November 2007 and concluded that all four Cluster satellites were fit to enter the second half of the extension. ESA has recently undergone a review of future mission extension assessment, and to bring all mission extension timelines into line, has set the current end of the Cluster mission at 30 June 2009. A proposal has been submitted to extend the Cluster mission from 1 July 2009 to December 2012, with a mid-term review in 2010. The science case is strong, and the spacecraft are technically able to support the extension. Analysis of the spacecraft performance carried out for the autumn 2007 review demonstrated that the platforms are in good health and are able to continue operation until the end 2012. Due to the age of the spacecraft and the finite resources, certain aspects have to be considered (Battery health and fuel limitations for example), but the experience gained by the flight control team in recent years have meant that any aspects of ageing have had limited impact on the science return. In particular, the ESOC team has implemented a number of measures to enable varying levels of spacecraft operations during orbits containing eclipses to optimize science data return. We hope for a positive outcome to the request for further mission extension, as the new science opportunities available to the mission are unique, both in Cluster observations themselves, but in particular in conjunction with other highly complementary missions such as the NASA THEMIS (Time History of Events and Macroscale Interaction during Substorms) mission [1] and the ESA Earth observation multi-spacecraft mission Swarm [6].

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21.3 Instrumentation Cluster payload commanding is carried out using the JSOC (Joint Science Operations Centre; URL http://www.jsoc.rl.ac.uk/) system, which creates the overall science plan or Master Science Plan (MSP) that covers a period of several months. This MSP forms the basis of a consolidated payload command schedule, which is iterated via a specialized interface with the principle investigator teams and the final version, which covers a single planning period, equivalent to 3 orbits or 1 week, is finally delivered ESOC for uplink to the spacecraft. The Cluster payload is a complete set of complementary instruments to measure magnetic fields, electric fields, particles (along with a spacecraft potential control device to enable low energy particle measurements in tenuous plasma) and electromagnetic waves (see [5] for more information on these instruments and the instrument archiving papers in this book). Table 21.2 provides an overview of the instruments and their principle investigators. At the time of writing, a vast majority of the instruments are still functioning nominally and provide a wealth of science data to the community. However, the CIS instrument on Cluster 2 is not operational and CIS-HIA is switched off on Cluster 4. We note that CIS-CODIF is still functional on Cluster 4, so thermal ion measurements are still possible on 3 of the 4 spacecraft. The electric field instrument EFW has a malfunctioning probe 1 on spacecraft 1, 2 and 3. This has a minor effect on science data return but instrument can still return 2 orthogonal E components in the spin plane. On all four spacecraft, the energetic ion instruments have no operating head in the look direction of the spin plane (hence only partial pitch angle distributions are possible) and recently all heads on spacecraft 1 have ceased to function. The Electron drift instrument (EDI) does not function on Cluster 4. Most recently, ASPOC, the spacecraft potential control was turned off due to the depletion of all its indium reserves, thus making it more difficult to measure the low energy component of particle distributions.

Table 21.2 Cluster instruments and Principal investigators (December 2008) Instrument Principal investigator ASPOC (spacecraft potential control) CIS (ion composition, 0 < E < 40 keV) EDI (plasma drift velocity) FGM (magnetometer) PEACE (electrons, 0 < E < 30 keV) RAPID (high energy electrons and ions, 20 < Ee < 400 keV, 10 < Ei < 1,500 keV) DWP (wave processor) EFW (electric field and waves) STAFF (magnetic and electric fluctuations) WBD (electric field and wave forms) WHISPER (electric density and waves)

K. Torkar (IWF, A) I. Dandouras (CESR, F) R. Torbert (UNH, USA) E. Lucek (IC, UK) A. Fazakerley (MSSL, UK) P. Daly (MPAe, D) H. Alleyne (Sheffield, UK) M. André (IRFU, S) N. Cornilleau-Wehrlin (CETP, F) J. Pickett (University of Iowa, USA) J.-G. Trotignon (LPCE, F)

Instruments marked with a are part of the wave experiment consortium (WEC)

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Access to the Cluster data was originally only available via the Cluster Science Data System, which distributed quicklook, summary and prime parameters data to all Cluster Principal and Co-Investigators. The Cluster Co-Is number around 300 plus the 11 Principal Investigators, located in more than 90 laboratories in 24 countries. Now high-resolution Cluster data are open to the worldwide science community via the Cluster Active Archive, which currently has more than 900 registered users (see Laakso et al. [Chapter 1 of this book]).

21.4 Publications Overall, the mission has been very productive and as of the end of December 2008 has generated 927 refereed publications (see Fig. 21.3), which includes publications from the Double Star mission. With 186 papers in 2008 alone, the number of scientific publications is still increasing. This recent increase is partly due to a new and wider user community gaining access to high quality Cluster data through the Cluster Active Archive (CAA) and partly to a special issue of the Journal of Geophysical Research. Of these papers, 30 have been published in high-impact journals not specific to the science of plasma physics: Nature, Nature Physics and Physical Review Letters. This shows that Cluster has not only revolutionized plasma physics, but also physics in general. About 60% of the total number of papers were published in the last 3 years, which shows that the community is still very active. Two Cluster scientists (Prof Balogh and Prof Rème) are listed by Thomson Scientific as fifth and eighth most cited authors in geosciences over the last decade.

Fig. 21.3 Cluster and Double Star publications as of December 2008

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Cluster has proven to be an excellent educational tool for training young scientists in the field of plasma physics and has resulted (as of December 2008) in 49 theses, of which 40 are Ph.D. Highlights of the latest Cluster results are published once a month on the ESA public and technical web sites. In the last 3 years, 37 web stories have been published on the ESA web site.

21.5 Recent Results Since the beginning of the current extension in February 2005, many new science results have been reported using Cluster data. These results were obtained as a result of Cluster’s unique four-point measurement capability, the strategy of varying inter-spacecraft distances and the high quality instrumentation, all of which have facilitated the sampling and derivation of the numerous plasma parameters necessary to characterize and understand fundamental plasma physics phenomena (Fig. 21.4).

Fig. 21.4 Cluster four-point measurements of magnetic field magnitude and density from C1 (black), C2 (red), C3 (green), C4 (blue). Dashed lines show low pass filtered data, solid lines the sum of low pass and band pass filtered data. The band pass covers 0.025–0.083 Hz. Detailed study shows that oscillations are not exactly in phase. In particular, the oscillations phases and amplitudes do not show a nested signature. This is most evident at t D 80 s. An immediate implication is that they cannot be explained by a static one dimensional shock profile oscillating back and forth, but instead must be propagating. This and the profile of the oscillation amplitude indicates that they could be described as a surface wave within the shock structure [17] (Reproduced by permission of American Geophysical Union)

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21.5.1 First Observation of Surface Waves on the Bow Shock The Earth bow shock is the place where the solar wind is decelerated in front of the Earth magnetic field. The shock is usually observed as a sharp discontinuity in magnetic field, plasma density and velocity. New Cluster observations [17] showed coherent oscillations of the plasma density and the magnetic field amplitude around the shock crossing. Phase differences in the oscillations, as seen on the four Cluster spacecraft, indicated that the oscillations were propagating, and could not be explained by a one-dimensional shock profile fluctuating in position. Four-point timing shows that the oscillations correspond to ripples traveling across the surface of the shock, with wavelength 1,000–2,000 km and propagating roughly parallel to the magnetic field. The presence of these oscillations could have major implications for the analysis of crossings observed in the past if it turned out to be a common phenomenon.

21.5.2 Solitons Observed and Successfully Modeled at the Magnetopause Solitary waves or solitons, have application across various fields of physics, including optical fibres (e.g. to enable ultra-fast internet). Fundamental questions on this phenomenon, however, remain open. In an article published by Trines et al. [29] the spontaneous formation of zonal mode solitary waves at the magnetopause is reported and explained. Although different types of solitons have been observed in the magnetosphere, this paper reports, for the first time, a direct comparison of multispacecraft observations and matched numerical modeling of zonal flow solitons, unambiguously showing that these structures penetrate through the magnetospheric border.

21.5.3 First 3-D Analysis of the Turbulence in the Magnetosheath Fundamental 3-D properties of the magnetic turbulence in the magnetosheath have been revealed [25], using the four-point measurements of Cluster and a data processing technique called k-filtering. Characterizing the properties of the magnetic turbulence occurring in this region is of prime importance to understand its role in fundamental processes such as mass transport, energy dissipation and magnetic reconnection (a physical process which enables the incoming solar wind to flow through the magnetopause). The nature of the turbulence could be firmly demonstrated in terms of mirror-like wave structures for the first time. The respective role of the propagation velocity and Doppler effects could be separated because of the 4-point measurement capability of Cluster. A power-law k-spectrum was constructed that had a surprisingly steep index compared to those expected from theory. The other significant result concerned the strong anisotropy of the turbulence in which the spectra were nonlinearly widened in only one direction: parallel to the

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magnetopause boundary and perpendicular to the magnetic field. New results, recently published in Physics Review E [26], go beyond the k-spectra and provide findings that had never been obtained before, neither in space nor in laboratory: the coherent nature of the structures composing the turbulence has been quantized and the existence of an inertial range, transferring energy from large to small scales, established.

21.5.4 Discoveries on Magnetic Reconnection Magnetic reconnection is a process by which magnetic energy is converted into particle energy and is accompanied by a topological change in the geometry of the magnetic field. The process allows for the transfer of mass and momentum between adjacent plasma regimes. This process is believed to be important in astrophysics (intergalactic medium, neutron stars), solar and space physics (solar flares, coronal mass ejections, geomagnetic substorms), and laboratory devices (e.g., tokamaks). Other than in the laboratory, planetary magnetospheres and the solar wind are the only places where we can study this process in-situ by measuring electric and magnetic fields and particle distribution functions. The advantage of space plasmas is that the measurement devices, the spacecraft, are much smaller than the plasma scales and therefore do not perturb the medium and the underlying physical process. In addition, a wide range of plasma parameters can be measured and there are no external walls that perturb the plasma as opposed to laboratory plasmas. We describe below a few highlights on reconnection studies.

21.5.5 Discovery of the Largest Reconnection Line (2.5 Millions of Kilometers Length) Using the Cluster spacecraft and the NASA Wind and ACE satellites, the largest jets of particles created between the Earth and the Sun by magnetic reconnection were discovered [20]. This result was published in Nature and the key illustration made it to the cover of the journal. The reported observations in the solar wind provide direct evidence that magnetic reconnection is fundamentally large scale and quasi-steady in nature. The 2.5 million km reconnection region is a world record, two orders of magnitude longer than the previous record.

21.5.6 First Observation of Magnetic Reconnection and Electric Current Disruption Close to Earth Using Cluster and Double Star Colourful aurorae, huge currents induced in power grids, rails and pipelines and perturbations of GPS signals are just some of the effects of a magneto-

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spheric phenomenon known as a magnetic substorm. Up to now, the onset of this phenomenon has been explained by two competing models: current disruption and near-Earth reconnection. A study published in Geophysical Research Letters [28] challenges this binary vision of substorm onset. Thanks to simultaneous measurements performed by the four Cluster satellites and the Double star TC2 spacecraft, a third type of substorm onset is now suggested. Data collected on 26 September 2005 between 08 and 10 UT captured the occurrence of three consecutive substorm onsets. But for the first time, these data indicate that the current disruption process and magnetic reconnection can coincide in space and time showing possibly the two sides of the same process.

21.5.7 Discovery of Magnetic Reconnection in Turbulent Plasma Irregular behavior of particle flows and magnetic fields, known as plasma turbulence, occurs throughout the universe. In turbulent plasma many small-scale boundaries can form, where models predict reconnection to occur. However, magnetic reconnection in turbulent plasma has never been directly observed before. Using measurements of the four Cluster satellites, a study published in Nature Physics [23] shows, for the first time, experimental evidence of magnetic reconnection in turbulent plasma. Reconnection was found to occur within a very thin current sheet embedded in the turbulent plasma with a typical size of about 100 km, a real challenge for the resolution of the instrumentation on Cluster. The observations showed that the turbulent plasma was accelerated and heated at thin, reconnecting current sheets, as had been predicted by Matthaeus and Montgomery [15]. Moreover, this new type of small-scale reconnection seems to be associated with the acceleration of particles to energies much higher than their average energy, something that could explain, in part, the creation of high energy particles by the Sun. This discovery opens new perspectives to better understand the behaviour of turbulent plasmas in the universe.

21.5.8 First Observation of Magnetic Reconnection in Giant Vortices Cluster observations revealed the presence of magnetic reconnection within giant swirls of plasma of 40;000 km size located on the flank of the magnetosphere [19]. These giant swirls were identified to be the result of the Kelvin-Helmholtz instability (also known as ‘wind over water’ instability) and were shown to facilitate the transport of solar wind material into the magnetosphere. Believed to be two distinct physical processes, Kelvin-Helmholtz instabilities and magnetic reconnection have been shown to co-exist under certain conditions. This result improves our knowledge on how, where and under which conditions the solar wind is able to penetrate the Earth’s magnetic shield (Fig. 21.5).

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21.5.9 Discovery of Very Elongated Electron Diffusion Region At the heart of the reconnection process is a small core zone called the electron diffusion region, where extreme topologies of the magnetic field lead to a situation where electron are de-magnetised, which means that their motion is not controlled by the magnetic field anymore. In a paper published in Physics Review Letters [21], Cluster observations in the Earth’s magnetosheath show evidence for the overall size of this diffusion region and find that it is 300 times larger than previously thought. This was supported by particle simulations with large simulation boxes. This means that future missions will have a much better chance of detecting and resolving this region than previously estimated, profoundly impacting mission design and scientific operations.

21.5.10 First Observation of 3D Magnetic Reconnection and Magnetic Nulls By reconnecting with each other, two adjacent regimes of magnetic fields create a magnetic null at the centre of the reconnection region. This is the classical twodimensional picture of reconnection. In three dimensions however, theory predicts not one but two nulls that would be linked to each other. A paper published in Nature Physics reports the first observation of two linked magnetic nulls using data collected by the four Cluster spacecraft [31]. In addition, the rare occurrence of one of the Cluster satellites passing by one null of the pair has uncovered a new phenomenon where the electrons are temporarily trapped around that null [8]. The electron trapping may ultimately lead to the formation of energetic electron beams, a well-known but poorly understood consequence of reconnection. This pioneering discovery will help constrain theoretical models of magnetic reconnection.

21.5.11 Confirmation of Relation Between Magnetic Substorms and Plasma Bursty Bulk Flows High-speed flows of plasma, known as bursty bulk flows (BBF), are propagating in the Earth’s magnetotail at velocities higher than 300 km/s. They carry decisive amounts of mass, energy and magnetic flux towards the Earth but their link to magnetic substorms was never absolutely established. Based on data recorded by three Cluster spacecraft (those with fully functioning ion detectors), a statistical study reveals, for the first time, that more than 95% of magnetic substorms observed in this time period were accompanied by BBF [2]. It also shows that BBF lasts longer than previously estimated and may account for up to 20% of the energy transport of a substorm. Published in the Journal of Geophysical Research, these results enhance previous studies based on single spacecraft measurements (Fig. 21.6).

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Fig. 21.6 Magnetic field configuration of a magnetic null pair reconstructed from Cluster measurements when C2 crosses the neutral sheet. (a) Separator reconnection configuration reconstructed from observations by Cluster at 09:48:25.637. A-null and B-null are shown as orange and red balls, respectively, with the separator as a bold pink curve connecting them. Magnetic field lines, colored according to local field strengths, converge along the fan surface (in white) to approach the A-null and then travel out along the spine (marked in black arrows) of the A-null. Magnetic field lines converge along the spine of the B-null and then diverge out along its fan surface (in grey). Cluster C1, C2, C3, C4 are drawn as four cubes in black, red, green, and blue, respectively. The origin of the illustrating coordinates is at the C2 position. (b) Magnetic field strength distributed on the X-line. The total field strength is drawn in bold black. Three components, Bx, By, and Bz, are in red, green and blue, respectively. The x-coordinate is the distance along X-line starting at the beginning with the smallest y in Fig. 21.6a. The orange (red) circle marks the location of the A-null (B-null) [8] (reproduced by permission of American Geophysical Union)

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21.5.12 Strongest Current Measured So Far in the Magnetotail To sustain its elongated shape, the magnetotail has in its centre part a current sheet, also called neutral sheet. Under normal conditions, the neutral sheet is usually wide (a few earth radii) and the current density is around 4 nA m2 . Before the Cluster era the actual values of local current densities in most regions of space have been uncertain due to the difficulty of measuring electric current densities in situ. During magnetic substorms, the neutral sheet becomes very thin. In such cases, the density of electric current increases steeply and subsequently magnetic reconnection can be triggered in the resulting extreme magnetic configurations. Cluster data at smallest separation distances in the magnetotail, around 200 km, were used to quantify for the first time the thickness of the current sheet; it was found to be comparable to or less than one ion inertia length or a few 100s km [18]. In addition using the curlometer technique or applying Ampere’s law to the multipoint magnetic data, the current measured was extremely strong, above 180 nA m2 , a factor 40 more than during quiet conditions. This finding will help to improve theoretical models of neutral sheet dynamics and understand how, when, where and why reconnection is initiated in the magnetotail.

21.5.13 First Measurement of the Size of Ion Diffusion Region Using Cluster Multi-scale Configuration Another thin magnetotail current sheet was observed in August 2005 during a magnetic substorm [24]. During that event, the spacecraft were in a multiscale configuration with C1, C2 and C3 forming a large triangle of 9,000 km parallel to the neutral sheet and C4 above C3 at about 900 km. distance. The analysis of the magnetic, electric and plasma data in the thin current sheet showed plasma flow reversal demonstrating that reconnection was taking place locally and that the spacecraft crossed the ion diffusion region. Using data from the closely spaced C3 and C4 pair of spacecraft, the vertical scale of the ion diffusion region was estimated to be less than 900 km. This is less than previous estimations. This preliminary analysis would however need more analysis and support for simulations since not all observations in this case supported the classical picture of reconnection (Fig. 21.7).

21.5.14 First Measurement of Second Order Terms in the Generalized Ohm’s Law In a plasma the electric field is fundamentally linked to the magnetic field, such that the two fields are perpendicular to each other for most of the time. However, at the heart of the reconnection process, the electric field has a component parallel

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to the magnetic field, which controls in particular the acceleration of particles. The perpendicular E-field component on the other hand is important, as it causes plasma and magnetic field inflow towards the X-line, necessary for reconnection to occur. This electric field component is known as the “reconnection electric field”. The total electric field is described by the generalised Ohm’s law, were E is the sum of four terms: MHD term, Hall term, pressure tensor term and electron inertia term. The first two terms have already been measured in space, while the last two never before. For the first time the third term, which can be understood as the divergence of the electron pressure tensor, was estimated using the electron detectors on board Cluster [9]. In agreement with numerical simulations, it was shown that the electric field from the pressure tensor was opposite to the Hall electric field and could support the reconnection electric field. Such studies to measure micro-physics quantities were only possible with the four Cluster at small separation distances from each other, around 200 km.

21.5.15 First Observation of “Chorus” Emission Propagation to Low Altitude Natural emissions of whistler-mode chorus consist of electromagnetic waves in the frequency range from a few hundreds of Hz to several kHz. Chorus emissions have been known for several decades but their source mechanism and effects are not yet well understood. Understanding the mechanisms and effects of chorus is important since it is believed that these intense plasma waves may strongly energize other radiation belt electrons to MeV energies. For the first time, Cluster has enabled scientists to determine the location and size of chorus source regions to be determined, together with propagation characteristics from these sources. Ray-tracing studies based on this new knowledge have then revealed that chorus waves can propagate to lower altitudes without being damped and provide a possible embryonic source of plasmaspheric hiss [3]. These results have been further improved in recent studies combining Cluster with the ionospheric DEMETER spacecraft [27].

21.5.16 Discovery of Magnetosonic Waves Accelerating Electrons to MeV Energies in Radiation Belts The relativistic electron flux in Earth’s outer radiation belt varies by over five orders of magnitude and is responsible for certain types of satellite malfunctions. Flux variations are due to a combination of electron acceleration, transport, and loss processes acting within the inner magnetosphere, indicating that the magnetosphere is a gigantic particle accelerator. For many years inward radial diffusion from a source beyond geosynchronous orbit (L D 6:6) has been considered the dominant

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Fig. 21.8 Fast magnetosonic waves detected by the STAFF instrument on Cluster 3, as it crossed the magnetic equator on 25 Nov 2002. The event occurred during an unusually long storm recovery phase. The waves can be identified by the intense emissions between 20 and 60 Hz, below the lower hybrid resonance frequency fLHR (solid line) but above the local proton gyrofrequency fcH , (5:1 Hz at the equator). The waves are confined to C= 3ı of the magnetic equator and are far more intense than chorus for this event (the band of emissions above fLHR rising in frequency towards the equator). These waves are generated by ion ring distributions and accelerate electrons, and it is suggested that they contributed t the elevated electron flux observed during this event, and could be an important energy transfer process from the ring current to the Van Allen radiation belts [10] (Reproduced by permission of American Geophysical Union)

mechanism for transport and acceleration but recent observations show that the electron phase space density can peak near L D 4.5. Acceleration by whistler mode chorus waves is an important mechanism for particles in the outer radiation belt during magnetic storms. However, Cluster observations have shown that fast magnetosonic waves can also accelerate electrons between 10 keV and a few MeV and must be considered as an additional local acceleration mechanism [10] (Fig. 21.8).

21.5.17 First Observation of Narrow Angle Emission of the Auroral Kilometric Radiation A recent study reveals how the most powerful emission of terrestrial origin, the Auroral Kilometric Radiation (AKR), is beamed from the auroral zone into space. Seen from deep space, the Earth is a powerful planetary radio source, comparable to

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Jupiter, with maximum output power in the 50–500 kHz range. AKRs are intimately linked with auroras, or more precisely with the acceleration of the energetic electron beams that cause the auroras. The new result clarifies how the radiation is beamed [16], which is in a narrow plane tangent to the magnetic field at the source, rather than a hollow cone as previously suggested. Cluster multi-point measurements could demonstrate that individual AKR bursts do not radiate in the manner described by two models that were proposed some 30 years ago. However, these new data do back up the numerical simulations of Louarn and Le Quéau [13] and Pritchett et al. [22] which predicted longitudinal propagation.

21.5.18 First Observation of the Evolution of Electric Circuit Powering the Auroras Aurora are powered by giant electrical circuits that accelerate electrons which then hit the upper layers of the atmosphere and form arcs in high-latitude regions like Scandinavia. It is known that two different types of electrical circuit, each associated with its own type of electric potential structure (“U” or “S” shape), close at low altitude along these arcs, but little was known about the source of this difference. For the first time, two consecutive crossings by two Cluster spacecraft captured the reconfiguration from one type of current system to the other [14]. It was shown that the particular evolution of such current systems may have its origin in the electron population in the magnetotail.

21.6 Conclusions Eight years of Cluster operations have provided a wealth of unique and ground breaking science results, in particular illuminating the three dimensional aspect of space plasma phenomena, some of which were highlighted above. A further extension of Cluster will provide even more exciting new science opportunities. Specifically, the extension proposal core science objectives are: 1. To discover the triggering and time evolution of the auroral acceleration by making the first four spacecraft measurements in the auroral acceleration region 2. To discover the role of current disruption in magnetic substorms, still a controversial problem, by making the first four spacecraft measurements in the near-earth neutral sheet (at 8–10 Earth radii radial distance) and to discover the role of electric fields in tail dynamics by repeating the tilting manoeuvre in the magnetotail 3. To study the relationships between the characteristics of cold plasma and wave activity in the plasmasphere and high-energy particles in the radiation belts using low-perigee data

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4. To study the magnetosphere simultaneously at global and ionscales by enhancing common operations with the THEMIS mission 5. To understand the structuring of currents and energy transport in space plasmas between ionosphere and magnetosphere by collaborating with the Earth observation Swarm multi-spacecraft mission in the ionosphere 6. To turn Cluster into an observatory, in order to exploit any yet unidentified new and exciting ideas from a wider user community to utilize this unique set of spacecraft While the first three topics basically are facilitated by the favourable development of the orbit (apogee in the South hemisphere and decreasing altitude at perigee), topics 4 and 5 represent new opportunities arising from multi-spacecraft collaborations in the wider magnetosphere, both inside and outside the Cluster orbit (THEMIS), and down to the ionosphere (Swarm). Topic 6 will open the Cluster science to a wider community. Cluster, by utilizing multi-spacecraft measurements, has provided a quantum leap in space plasma physics investigation. Recently, the five spacecraft THEMIS mission has further demonstrated the utility of such measurements at large separations. Future missions have multiple spacecraft measurements at the heart of their concept. The NASA Magnetospheric Multi-Scale mission, due to launch in 2014, will utilize 4 spacecraft to investigate the phenomena of reconnection at smaller scales than Cluster (down to electron scales), using highly specialized fast plasma detectors to unravel the mysteries of the reconnection diffusion region. Recently ESA made a call to the community for proposals to Cosmic Vision 2015–2025. The Cross-Scale proposal was selected for further study. The mission concept is to quantify the coupling in plasmas between the three different physical scales (electron ion and MHD) in order to address fundamental questions such as: how shocks accelerate and heat particles; how reconnection converts magnetic energy and how turbulence transports energy from source to dissipation. This mission will be made up of up to 12 spacecraft comprising three nested tetrahedra. In collaboration with this activity, JAXA are investigating the multispacecraft mission SCOPE, which consists of a large mother spacecraft and four smaller daughter spacecraft. The future of space plasma physics lies truely in multi-point multi-scale observations, and this development is in no small part due to the Cluster mission. We hope Cluster can continue to remain an important part of space plasma science for a few decades even beyond the anticipated mission extension thanks to the datasets available to the worldwide science community through the Cluster Active Archive. The latest news relating to the Cluster mission can be found at: http://sci.esa.int/ cluster/. Information on the Double Star mission can be found at http://sci.esa.int/ doublestar/. Acknowledgements The authors would like to thank all PIs and their teams for their hard work on the Cluster instruments and data, and the JSOC and ESOC teams for their very efficient operation of the Cluster spacecraft.

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M.G.G.T. Taylor et al. of an ion-scale current sheet in the magnetotail under the presence of a guide field, J. Geophys. Res., 113, A07S16, http://dx.doi.org/10.1029/2007JA012760, (2008) Nykyri, K., Otto, A., Lavraud, B., Mouikis, C., Kistler, L.M., Balogh, A., Rème, H.: Cluster Observations of reconnection due to the Kelvin-Helmholtz instability at the dawnside magnetospheric flank, Annales Geophysicae, 2619–2643, Vol. 24, No. 10, (2006) Phan, T.D., Gosling, J.T., Davies, M.S., Skoug, R.M., Øieroset, M., Lepping, R.P., McComas, D.J., Smith, C.W., Rème, H., Balogh, A.: A Magnetic reconnection X-line extending more than 390 Earth Radii in the solar wind, Nature, Vol. 439, (2006) Phan, T.D., Drake, J.F., Shay, M.A., Mozer, F.S., Eastwood, J.P.: Evidence for an Elongated (>60 Ion Skin Depths) Electron Diffusion Region during Fast Magnetic Reconnection, Phys. Rev. Lett., 99, 255002, (2007) Pritchett, P.L., Strangeway, R.J., Ergun, R.E., Carlson, C.W.: Generation and propagation of cyclotron maser emissions in the finite auroral kilometric radiation source cavity, J. Geophys. Res., 107(A12), 1437, doi:10.1029/2002JA009403, (2002) Retinò, A., Sundkvist, D., Vaivads, A., Mozer, F., Andre, M., Owen, C.J.: In-situ evidence of magnetic reconnection in turbulent plasma, Nature Physics, March 25, doi:10.1038/nphys574, (2007) Runov, A., Baumjohann, W., Nakamura, R., Sergeev, V.A., Amm, O., Frey, H., Alexeev, I., Fazakerley, A.N., Owen, C.J., Lucek, E.A., André, M., Vaivads, A., Dandouras, I., Klecker, B.: Observations of an active thin current sheet, J. Geophys. Res., 113, A07S27, doi:10.1029/2007JA012685, (2008) Sahraoui, F.; Belmont, G., Rezeau, L., Cornilleau-Wehrlin, N., Pinçon, J.-L., Balogh, A.: Anisotropic turbulent spectra in the terrestrial magnetosheath: Cluster observations, Physical Review Letters, 96, 075002, (2006) Sahraoui, F.: Diagnosis of magnetic structures and intermittency in space-plasma turbulence using the technique of surrogate data Phys. Rev. E, 78, 026402, (2008) Santolik, O., Chum, J., Parrot, M., Gurnett, D.A., Pickett, J.S., Cornilleau–Wehrlin, N.: Propagation of whistler mode chorus to low altitudes: Spacecraft observations of structured ELF hiss, J. Geophys. Res., 111, A10208, doi:10.1029/2005JA011462, (2006) Sergeev, V., Semenov, V., Kubyshkina, M., Ivanova, V., Baumjohann, W., Nakamura, R., Penz, T., Runov, A., Zhang, T.L., Glassmeier, K.-H., Angelopoulos, V., Frey, H., Sauvaud, J.-A., Daly, P., Cao, J.B., Singer, H., Lucek, E.: Observation of repeated intense near-Earth reconnection on closed field lines with Cluster, Double Star, and other spacecraft, Geophys. Res. Lett., Vol. 34, No. 2, (2007) Trines, R., Bingham, R., Dunlop, M.W., Vaivads, A., Davies, J.A., Mendonça, J.T., Silva, L.O., Shukla, P.K.: Spontaneous Generation of Self-Organized Solitary Wave Structures at Earth’s Magnetopause, Phys. Rev. Lett., 99, 205006, (2007) Volpp, J., Escoubet, C.P., Foley, S., Godfrey, J., Hapgood, M., Pallaschke, S.: Cluster constellation change manoeuvres – Management and Operations, SpaceOps 2004, Montreal, Canada, (2004) Xiao, C.J., Wang, X.G., Pu, Z.Y., Ma, Z.W., Zhao, H., Zhou, G.P., Wang, J.X., Kivelson, M.G., Fu, S.Y., Liu, Z.X., Zong, Q.G., Dunlop, M.W., Glassmeier, K.-H., Lucek, E., Rème, H., Dandouras, I., Escoubet, C.P.: Satellite observations of separator line geometry of threedimensional magnetic reconnection, Nature Physics, 3, 609–613, doi:10.1038/nphys650, (2007)

Chapter 22

Double Star: Mission, Instruments and Joint Observations M.W. Dunlop, C.P. Escoubet, Z.-X. Liu, C. Shen, H. Laakso, M.G.G.T. Taylor, A.N. Fazakerley, and the Double star PIs

Abstract The Chinese National Space Agency (CNSA) Double Star (DSP) spacecraft, TC-1 and TC-2 were launched in December 2003 and July 2004 into near equatorial and polar orbits respectively. During more than 3 years of operations they have maintained a close phasing with the ESA four-spacecraft mission to produce the first, well coordinated multi-scale measurements, sampling phenomena with five and six spacecraft. In this short paper we give a brief review of the DSP mission and show its joint capability with Cluster by showing examples of use of some early and more recent analysis techniques and their application to (more than) four spacecraft. We highlight a selection of some co-ordinated events, focussing on dayside phenomena, but also with a brief discussion of a tail event. Other reviews in this special issue will deal more completely with coverage of the other regions of the magnetosphere.

22.1 Introduction The two Double Star spacecraft were launched in order to provide the opportunity to monitor events at distinct locations in the Earth’s magnetosphere, when coordinated with the quartet of Cluster spacecraft. The ESA Cluster mission [4]

M.W. Dunlop () SSTD, Rutherford Appleton Laboratory, Chilton, Didcot, Oxfordshire, OX11 0QX, UK and The Blackett Laboratory, Imperial College London, London, SW7 2AZ, UK e-mail: [email protected] C.P. Escoubet, H. Laakso, and M.G.G.T. Taylor ESA/ESTEC, Keplerlaan 1, 2200 AG Noordwijk, The Netherlands Z.-X. Liu and C. Shen Centre for Space Science and Applied Research, Chinese Academy of Sciences, Beijing 100080, China A.N. Fazakerley Mullard Space Science Laboratory, University College London, Dorking, Surrey, RH5 6NT, UK


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provided extremely detailed multi-point measurements sampling local in situ phenomena, while coordination with the Chinese Double Star mission [6] provided distant, simultaneous monitoring at other locations, often providing multi-scale information. At the magnetopause, for example, such coverage over a wide range of different magnetopause sites, combining up to six spacecraft from the two missions, has provided simultaneous coverage of the high and low latitudes, cusp and low latitude boundary layer. Recent studies have investigated X-line formation (directly and indirectly) and the development of the boundary layer at both high and low latitudes. For example, Pu et al. (2007, [8]) surveyed a number of direct reconnection events under both dominant BY and for low clock angles, finding evidence of predominantly component driven low latitude merging in conjunction with predominantly anti-parallel high latitude sites. The identification of oppositely moving FTEs at the Double Star TC-1 and Cluster spacecraft and detailed tracking of flux tube motion between TC-1 and Cluster along the MP was made by Wild et al. [12], Dunlop et al. [3], Fear et al. [5], and Wang et al. [11], and has been recently compared to MHD simulation results by Berchem et al. [2008]. Comparison of the cusp electron boundary layer and the low latitude boundary layer (LLBL) under northward directed interplanetary field has been investigated recently by Bogdanova et al. [1]. 1. The Double Star Project (DSP) consists of two magnetospheric spacecraft, built and operated by the Chinese National Space Agency (CNSA), following a mission programme which was first accepted by Chinese government on 28 September 2000. An agreement between ESA and CNSA was later signed in July 2001. The DSP spacecraft were launched from Long March-2C/SD vehicles, having an upgrade of the third stage to a more powerful version (responsible for the larger TC-1 orbit). The launches occurred at the Xichang (Equatorial, TC-1) and Taiyuan (polar, TC-2) sites. One equatorial (28ı ) satellite, TC-1, was launched on 29 Dec 2003 into a 1:09 13:4 RE inclined orbit, while the other, polar satellite, TC-2, was launched on 25 July 2004 into a 1:17:1 RE polar orbit. In fact, the apogee achieved by TC-1 was slightly higher than initially planned. Moreover, the spacecraft precesses semi-inertially so that it is initially in phase with the Cluster orbit. TC-2 has an increasing argument of perigee so that its line of apsides fell during the mission lifetime. The TC-1 spacecraft underwent a natural re-entry to Earth on 11 October 2007 (a year and a half beyond its nominal lifetime), while TC-2 is still in operation at the time of writing after an initial loss of contact in August 2007 and recovery in November 2007. The planned scientific objectives for the nominal mission, having a 2 year lifetime, were: to study magnetic reconnection at the magnetopause and in the magnetotail; to understand and locate the trigger mechanism for magnetospheric storms and substorms; to study physical processes like particle acceleration, diffusion, injection and up-flowing ions during storms, and to study temporal variations of field aligned currents and the coupling between tail current and auroral current. Figure 22.1 shows the scientific regions visited by Cluster and Double Star for both the extended spring and summer phases: dayside to nightside. The inclination of TC-1 placed its apogee initially low on the dayside and high on the nightside as shown, and was initially in phase with the Cluster orbital plane. The local time separation between

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Fig. 22.1 Dayside (left panel ) and nightside (right panel ) views of the combined Cluster and DSP orbit configuration

Cluster and TC-1 increased progressively, while TC-2 had an initially high apogee elevation, which progressively fell from that indicated. The views in Fig. 22.1 represent the orbital orientations in February and August of each year, where it is clear that on the nightside all spacecraft sample a range of distances down tail and sample field lines directly or indirectly connecting to both expected current disruption and near Earth reconnection sites. On the dayside, Cluster samples the mid to high latitude magnetopause while TC-1 samples the low to mid latitude magnetopause. Cluster may also be located in the solar wind, bow shock or magnetosheath at low to mid latitudes while TC-1 lies nearer the Earth at the magnetopause or magnetosheath. Cluster and TC-2 may also sample the Cusp simultaneously at different altitudes.

22.2 Operations, Payload and Data Acquisition The European Space Agency gave support to DSP via the bi-lateral agreement with CNSA in 2001 and involved: refurbishment/rebuilding of the Cluster spare instruments; integration of the European instruments in Europe; carrying out the tests for conductivity and magnetic cleanliness; performing the required radiation analysis; provision of the VILSPA-2 ground station (4 h/day) in addition to the 2 Chinese Ground stations, Beijing: ¿ 11 m dish, Shanghai: ¿ 25 m dish, which conducted shared operation and support of science operations for European instruments. The full payload and PI teams are listed in Table 22.1, which summarises the key technical information. Full descriptions of all instruments can be found in the special issue of Annales Geophysicae (2005), on The Double Star Mission, [Ann. Geophys., 23]). Table 22.1 shows the name of each experiment and its mass, power and data telemetry rate and instrument operating ranges. Identical Chinese lead high energy and heavy ion instruments (CSSAR) were accommodated on both TC-1 and TC-2. In addition, similar magnetic field (FGM) and thermal electron (PEACE), UK led instruments were accommodated on both TC-1 and TC-2, together with the French thermal ion (HIA) and wave (STAFF/DWP) experiments on TC-1, developed from flight spare Cluster instruments. The PEACE DSP instrument used a low energy

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Table 22.1 Payload distribution for TC-1 and TC-2, with European instruments in red [6] Equatorial double star (TC-1) Polar double star (TC-2) Instruments Active spacecraft Potential control (ASPOC) indium ions. 50 A max current. (2.54 kg, 2.9 W, 108 bps)

PI K. Torkar, IWF, Graz, Austria

Instruments Neutral Atom Imager (NUADU) 45 KeV < Eena < 300 KeV (5.7 kg, 4.6 W, 4,224 bps)

Fluxgate Magnetometer (FGM), 22 vector/s (3.1 kg, 3.6 W, 1,211 bps)

C. Carr IC, UK

Plasma electron and Current exp. (PEACE)# 1eV < Ee < 25 KeV (6.5 kg, 3.8–4.8 W, 4,624 bps) Hot Ion Analyzer(HIA), CIS sensor 2) 5eV < Ee < 32 KeV (3.5 kg, 2.8 W, 4,440 bps)

A. Fazakerley, MSSL, Dorking, UK

Part of Spatio-Temporal Analysis of Field Fluct.(STAFF) 0 < f < 4 kHzC Digital wave processor (4.9 kg, 4.0 W, 3509 bps) High Energy Electron Detector .HEED/ 0:2 < Ee < 10 MeV (2.2 kg, 2.0Watts, 224bps) High Energy Proton Detector .HEPD/ 3 < Ep < 400 MeV (2.2 kg, 2.0 W, 202 bps)

N. Cornilleau/H. Alleyne, CETP, Velizy, France and Sheffield U. UK

Fluxgate Magnetometer (FGM) 22 vector/s (3.1 kg, 3.6 W, 1,211 bps) Plasma Electron and Current Exp. (PEACE) 1 eV < Ee < 25 KeV (6.5 kg, 3.8–4.8 W, 4,624 bps) Low Energy Ion Detector .LEID/ 50 eV < Ee < 25 KeV (4.0 kg, 4.0 W, 2,000 bps) Low Frequency Electromagnetic Wave detector (LFEW) 8 Hz < f < 10 kHz (4.0 kg, 5.0 W, 3,000 bps) High Energy Electron Detector .HEED/ 0:2 < Ee < 10 MeV (2.2 kg, 2.0 W, 224 bps) High Energy Proton Detector .HEPD/ 3 < Ep < 400 MeV (2.2 kg, 2.0 W, 202 bps) Heavy ion detector .HID/10 MeV < Ei < 8 GeV (2.2 kg, 2.0 W, 45 bps)

Heavy ion detector .HID/ 10 MeV < Ei < 8 GeV (2.2 kg, 2.0 W, 45 bps)

H. Rème, CESR, Toulouse, France

W. Zhang and J.B. Cao, CSSAR, China

J. Liang and J.B. Cao, CSSAR, China

Y. Zhai and J.B. Cao, CSSAR, China

Instrument built by China # PEACE includes only one sensor on each spacecraft

PI S. McKennaLawlor, Ireland U., Ireland L. Lu, CSSAR, China S. Barabash, IRF, Sweden T. Zhang, IWF, Austria

A. Fazakerley, MSSL, Dorking, UK

Q. Ren and J.B. Cao, CSSAR, China

Z. Wang and J.B. Cao, CSSAR, China

W. Zhang and J.B. Cao, CSSAR, China

J. Liang and J.B. Cao, CSSAR, China

Y. Zhai and J.B. Cao, CSSAR, China

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Fig. 22.2 The stowed and flight configuration of the DSP spacecraft

sensor for TC-1 (LEEA) and a high energy sensor for TC-2 (HEEA) and the HIA represented part of the full CIS experiment on Cluster. Thus, many properties of the plasma (distributions of the ions and electrons, and the magnetic field) were measured by almost identical instruments on all six spacecraft. The instrument data set has been re-calibrated on ground, and is available through the PIs and the DSP data centre. The in-flight spacecraft configuration, shown together with the launch configuration in Fig. 22.2, resulted in all instruments operating nominally. The spacecraft had a mass of 280 kg, cylindrical in shape with ¿ 2:1 m diameter and a height of 1.2 m. Each spacecraft was established in orbit with a nominal spin rate of 15 rpm (identical to Cluster) and a spin axis perpendicular to ecliptic. Spacecraft power was achieved via a solar panel array, with 6:33 m2 , 280 W (BOL) and Nickel-Cadmium batteries. The nominal, planned operational lifetime was 18 months (TC-1) and 12 months (TC-2). A number of non critical operational issues ensued after each launch. The solar panels on TC-1 generated an anomalous spacecraft current, introducing a complex, rotating (sun fixed), dipole spacecraft field, which affected the FGM measurements of the ambient magnetic field. Boom deployment, carrying the STAFF instrument, failed resulting in a number of spacecraft interferences in the wave power measurements. The attitude computer on each spacecraft also failed at different times on each spacecraft so that the spin axis orientation could not be controlled, resulting in a drift from nominal perpendicular orientation (after November 2004, for TC-1, and after July 2004, for TC-2). This drift of the spin axis became pronounced during the mission extension: TC-1: 9ı drift up to end of 2006; TC-2: 30ı drift up to July 2006. The spacecraft attitude was also derived from magnetometer data for operations and data analysis, providing an additional tracking of the spin axis orientation. In addition to these particular issues, the spacecraft environment induced a number of anomalous instrument resets, particularly affecting the PEACE instrument, and there were some calibration issues for some of the Chinese instruments. Nevertheless, overall, both DSP spacecraft operated with nominal parameters and all instruments operated continuously. The ground segment provided 99% data recovery via 3.3 h of data dump per day, which was initially disseminated via an adaptation of the Cluster data distribution system, comprising an internet based quick-look, summary data

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facility (DSDSweb), holding data up to five days after acquisition, and a data management system (CDMS) holding validated summary (1 min time resolution) and prime (spin averaged) parameters. Both systems contain data viewing capabilities, with the DSDSweb providing a range of standard summary plots, as shown in Fig. 22.3. Data can be downloaded in CDF or ASCII files formats (http://www.rssd.esa.int/index.php?project D DOUBLESTAR&page D about dsds). Science quality or high resolution data, also distributed, on request from the PI teams.

Fig. 22.3 Example summary data plot from the DSDS data system. A number of options for display are possible. This plot shows a set of instrument data for TC1, with magnetic field and plasma moments in the top panels, energy spectrogams for ions and electrons and magnetic wave spectra at the bottom

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22.3 Orbit Strategy and Mission Extension Following the nominal 18 months of operations both the CNSA and ESA accepted a case for a mission extension based on the data quality achieved and the additional science aims: to increase the number of conjunctions between Cluster and Double Star; to measure small, medium and large scales simultaneously; to measure size of large scale structures at the magnetopause/cusp; to observe more rare events like reconnection and storms, and to acquire “stereo” ring current images with IMAGE. Table 22.2 shows the orbits phases for the mission which were executed. The nominal mission is shown in grey shading and summarises the coordination with Cluster, as is plotted in Fig. 22.1. In the plots, the TC-1 and TC-2 orientations shown are nominal. For the initial dayside phases in spring 2004 and 2005, Cluster was set in small and meso-scale configurations, crossing the magnetopause above and below TC-1, at 5–10 RE distance. For the tail phase, summer 2004, the Cluster sampled the whole plasma sheet (15–19 RE ) as TC-1 sampled the near-current sheet at a range of down-tail distances ( 1 in the local plasma.

26.1 Introduction Mirror mode waves are compressive, non-propagating low frequency magnetic field fluctuations in which the field magnitude is anti-correlated with the plasma pressure. They are linearly polarized with a maximum variance direction which typically lies at about 10ı –20ı to the mean magnetic field direction [3]. Mirror mode waves are generated by the mirror instability [6] developing in high “ plasmas when the ion temperature is anisotropic and the proton-electron plasma contains a small percentage of HeCC ions [4,5] corresponding to the composition of the solar wind. Beyond the terrestrial magnetosheath (cf. Tsurutani et al. [20], Lucek et al. [12]), mirror M. Tátrallyay () and G. Erd˝os KFKI Research Institute for Particle and Nuclear Physics, 1525 Budapest, P.O. Box 49, Hungary e-mail: [email protected] I. Dandouras CESR, BP 4346, 31028 Toulouse, Cédex 4, France E. Georgescu MPS, Max-Planck-Str. 2. 37191 Katlenburg-Lindau, Germany H. Laakso et al. (eds.), The Cluster Active Archive, Astrophysics and Space Science Proceedings, DOI 10.1007/978-90-481-3499-1 26, c Springer Science+Business Media B.V. 2010

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mode fluctuations were most frequently observed in the magnetosheath of the outer planets ([3, 15, 20, 22] and a number of later studies), but recently they were also identified in the induced magnetosheath of Venus [23]. Mirror mode waves were encountered in the coma of comets [14, 21], in the interplanetary field [24], and also in the heliosheath [2]. These observations confirm that the actual parameters of different space plasmas often favour the development of the mirror instability. Tátrallyay and Erd˝os [18] investigated the evolution of mirror type fluctuations in the terrestrial magnetosheath based on magnetic field data measured aboard the ISEE-1 spacecraft. Fluctuations were observed in different regions of the sheath with increasing amplitudes from the bow shock towards the magnetopause. The growth rate of the instability was determined assuming that the fluctuations were originating at the bow shock and the field strength perturbations were growing exponentially while traveling frozen in the plasma flow. The compared amplitudes were observed at different locations and at different times during the magnetosheath pass of one satellite. Tátrallyay et al. [19] revisited the evolution of mirror mode waves in the magnetosheath comparing the amplitudes of linearly polarized magnetic field fluctuations observed simultaneously aboard Cluster-2 and Cluster-4 at distant locations (10;000 km) during two inbound passes. The growth rate values obtained by both studies were about an order of magnitude smaller than those calculated from a numerical evaluation of the full kinetic dispersion relation by Gary et al. [5]. Plausible explanations were given for the significant difference between the observed and calculated growth rate values: (1) the growth of mirror type fluctuations cannot be described by linear approximations in the magnetosheath; (2) the waves are not always originating at the bow shock, there may be other sources inside the magnetosheath. In this paper, the evolution of mirror type magnetic fluctuations is further investigated in the magnetosheath involving also plasma data. During the four selected inbound passes, the magnetic field variations were mainly quasi-sinusoidal oscillations or peaks, except for the regions close to the magnetopause. Tátrallyay et al. [19] used only magnetic field data simultaneously measured by the Cluster spacecraft. In the present study, local plasma parameters measured by the Cluster Ion Spectrometer are also analyzed and the influence of changes in the interplanetary magnetic field and solar wind is also taken into account.

26.2 Data Analysis During the winter/spring season in 2006, the separation of the Cluster spacecraft was about 10,000 km when they passed through the magnetosheath, so that fluctuations measured simultaneously at significantly different distances from the magnetopause could be compared. Supposing that the field variations were originating from the same source, their evolution between two distant observation points could be investigated. Mirror mode fluctuations were identified from 1 s resolution magnetic field time series measured by the Fluxgate Magnetometer [1]. Applying variance analysis,

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several orbits were selected when magnetic field fluctuations were linearly polarized (characteristic of mirror mode waves) for several hours in different regions of the magnetosheath. Two criteria were used for the selection: (1) the angle between the maximum variance direction and the average field vector is smaller than 20ı ; (2) the ratio of the maximum eigenvalue to the intermediate eigenvalue of the variance matrix is relatively large, i.e. œmax =œint > 5. The length of the sliding window applied for the variance analysis was 1 min, while the typical period of the mirror type fluctuations was 10–25 s. In order to have the possible largest separation between two spacecraft and also reliable local plasma data, mirror type fluctuations observed by Cluster-3 and Cluster-4 are compared in this study. Four seconds resolution plasma parameters measured by the Hot Ion Analyzer of the Cluster Ion Spectrometer [13] aboard Cluster-3 were used. CIS-HIA did not provide data for Cluster-2 and Cluster-4. The following parameters were determined from ion densities and temperatures parallel Tjj and perpendicular T? to the magnetic field: the correlation between plasma and magnetic field pressure; plasma “i , i.e. the ratio of ion pressure to magnetic field pressure; and the mirror instability criterion CM D “? T? =Tjj 1 as given by Hasegawa [6]. In mirror mode waves, plasma pressure is anti-correlated with magnetic pressure and the plasma beta is high .“i > 1/. Earlier Hasegawa [6] argued that mirror mode waves grow when the plasma is in unstable condition i.e. CM > 1. However, recent investigations suggested that the value of CM controls the shape of the mirror mode variations. Magnetic peaks develop when the plasma is unstable while dips survive in linearly stable plasma when CM < 1 (cf. Soucek et al. [17]). The influence of interplanetary effects on the occurrence of mirror mode fluctuations was investigated using the 1 min resolution OMNI data set providing magnetic field and plasma parameters upstream of the nose of the terrestrial bow shock (http://nssdc.gsfc.nasa.gov/omniweb/html/omsc min.html). Variations in solar wind dynamic pressure and in the magnitude and direction of the Interplanetary Magnetic Field were analyzed while the flow-time from the bow shock to the observation point of the mirror wave in the magnetosheath was taken into account. The angle between the IMF and the bow shock normal BN was determined in the bow shock region which was connected to the location of Cluster-3 by the plasma flow-line. Solar wind plasma flow-lines in the magnetosheath and flow-times along the flowlines were determined using the model of Kobel and Flückiger [9] as described by Tátrallyay et al. [19].

26.3 The Influence of Plasma Parameters on the Occurrence of Mirror Mode Waves Tátrallyay et al. [19] discussed the growth of mirror type magnetic field fluctuations during two magnetosheath passes based only on magnetic field measurements observed by Cluster-2 and Cluster-4. On 7–8 February 2006, solar wind dynamic pressure and the interplanetary magnetic field were undisturbed, the IMF stayed

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quasi-perpendicular to the bow shock normal .BN > 60ı / during the whole pass. Mirror mode magnetic fluctuations (mainly peaks) were observed by all satellites throughout the middle and inner magnetosheath where “i > 10 and CM Š 2 was measured. The amplitude of the waves was almost continuously growing while traveling inbound. During the inbound pass on 3 January 2006, however, there was a sudden change in the growth of the mirror type magnetic fluctuations at about 5:00 UT when the direction of the IMF changed significantly as shown in Fig. 26.1. Mirror waves did not occur downstream of the quasi-parallel bow shock .BN < 45ı / after 05:00 UT. Later (closer to the magnetopause where CM Š 1 and “i Š 1, i.e. both parameters decreased compared to the earlier measured values), Cluster-3 observed mirror mode fluctuations less frequently than Cluster-4 which was farther away from

Fig. 26.1 Inbound magnetosheath pass on 3 January 2006. Upper three panels: 1 min averaged plasma parameters calculated from data measured by CIS-HIA aboard Cluster-3: plasma “i ; correlation between plasma and magnetic pressure; mirror criterion CM D “? .T? =Tjj 1/, CM D 1 critical value is marked; panel 4 and bottom: 4 s resolution Cluster-3 and Cluster-4 magnetic field, vertical bars above the time axis mark the minutes when linearly polarized variations occur; panels 5–7: interplanetary parameters from the 1 min resolution OMNI data set: BN at the bow shock region connected by plasma flow-line, BN D 45ı is marked; IMF total value; solar wind dynamic pressure

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the magnetopause. Earlier, between 03:15 and 04:00 UT when there were changes in the magnitude of the IMF, mirror mode waves were observed rarely by both satellites. During the time interval presented by Fig. 26.1, there was no significant change in solar wind dynamic pressure. Two additional inbound passes were also investigated in details: 22 January and 10 February 2006. In both cases, there were sudden changes in solar wind dynamic pressure (usually together with changes in the IMF) moving the magnetopause inwards or outwards thus influencing plasma and magnetic field parameters in the magnetosheath. When the magnetopause moved closer to Cluster-3 in the inner sheath, this satellite did not observe mirror mode fluctuations any more since CM and “i parameters decreased below their critical values in the vicinity of the magnetopause. Cluster-4 which was farther out in the magnetosheath observed mirror mode fluctuations later when the variations in the interplanetary parameters became smoother. Also, the direction and/or magnitude of the IMF changed several times during both magnetosheath passes influencing the growth of the waves. No mirror mode waves were observed when the IMF was quasi-parallel to the bow shock normal in the region connected to the observation point.

26.4 Growth Rate of Fluctuations The growth rate of the fluctuations can be estimated by assuming that mirror waves are growing as •B exp. t/ while flowing frozen in the plasma along the streamlines where > 0 is the growth rate [18,19]. The value B presented in Fig. 26.2 was calculated from relation •B3 =•B4 D exp .B Œt3 –t4 / where •B3 and •B4 were the amplitudes of the fluctuations simultaneously measured by Cluster-3 and Cluster-4 at distant locations. The flow-times (from the source along the flow-line to the observation point) t3 and t4 were calculated from the model of Kobel and Flückiger [9] for the middle of the selected 20 min time intervals of the above discussed four inbound passes. Most of the time, the shape of the magnetic variations was quasi-sinusoidal

Fig. 26.2 The relation between growth rates B determined from simultaneously measured magnetic field variations aboard Cluster-3 and Cluster-4 and maximum growth rates C calculated from plasma parameters measured by CIS-HIA aboard Cluster-3 in 20 min intervals on 3 Jan, 22 Jan, 7/8 Feb, and 10 Feb 2006. Averaged amplitudes •B3 and •B4 were determined from individually selected mirror type variations (gray symbols) and from the maximum eigenvalues of the variance matrix (black symbols)

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or peak type since the value of the mirror instability criterion was well above 1, often CM > 2 was measured. Magnetic dips were observed only in the inner regions of the magnetosheath where CM was below the critical value or close to it corresponding to the results of Soucek et al. [17]. The averaged amplitudes •B3 and •B4 were determined in two ways: (1) from the difference between the magnetic field maximum and minimum values of individually selected mirror type variations when the change in the field direction was smaller than 20ı (similar conditions were used by Tatrallyay et al. [19]) – shown by gray symbols in Fig. 26.2; (2) from the maximum eigenvalues of the variance matrix for 1 min intervals applying the conditions discussed in Section 26.2 – shown by black symbols in Fig. 26.2. The B values determined from individual events are in good agreement with those calculated using the variance method. Based on the dispersion relation of Hasegawa [6], Liu et al. [11] analytically derived an expression for the maximum growth rate of mirror mode waves: C D 3=2 .3= /1=2 .6“? /1 T? =Tjj .CM 1/2 p for the conditions kjj k? in the long wavelength limit, where CM D “? T? =Tjj 1 > 1 is the mirror instability criterion, k is the wave number, and p is the proton gyro-frequency. This formula provides significant growth rates only in high “jj regions when the thermal anisotropy is moderate in agreement with observations (cf. Lacombe and Belmont [10], Samsonov et al. [16]) and with the results of hybrid simulation [7]: proton cyclotron waves dominate when “jj is lower and T? =T jj is well above 1, while mirror mode waves grow when the plasma beta is higher “jj > 1 and T? =Tjj is slightly over 1. For the calculation of C values presented in Fig. 26.2, ion densities and temperatures measured by CIS HIA aboard Cluster-3 were used. The parameters were averaged for 20 min intervals. Figure 26.2 illustrates that B growth rates estimated from the amplitudes of magnetic fluctuations are comparable with C maximum growth rates calculated from the local plasma parameters when the latter values are by “? when the anisotropy is moderate small. The value of C is mainly influenced as measured 1:2 < T? =Tjj < 1:6 during the selected events. The value of “? was 1–3 on 3 Jan providing smaller C values, while it was 10–20 on 7/8 Feb resulting in larger C . On 22 Jan and 10 Feb, the value of “? was changing in a wider range (mainly caused by significant changes in the IMF), therefore the dispersion in the C values was relatively large. According to Gary et al. [5], the numerical evaluation of the linear Vlasov dispersion equations provided the value of max 0:02 p for the maximum growth rate of the mirror instability when T? =Tjj D 1:5, “ D 4, and the plasma contained 4–10% HeCC ions. Hubert et al. [8] obtained very similar max values for plasmas of slightly different parameters using a linear model. Since p > 1:5 s1 during the selected magnetosheath passes, it is evident that both B and C growth rate values obtained in this study are smaller than the maximum growth rates predicted by these linear models. Samsonov et al. [16] compared the proton temperature anisotropy measured by Cluster in the magnetosheath with T? =Tjj values predicted by a 3D double adiabatic MHD model. According to their results, the maximum growth rate of the proton cyclotron and mirror instabilities could be equal in the high “

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regions varying in the range 104 < max =p < 2:5 102 . The values B and C determined in the present study fit well in the range of possible growth rates provided by Samsonov et al. [16]. It is obvious that linear models can provide a good approximation for the growth of mirror mode waves only around the onset of the instability. Later in the process, growing waves scatter ions, reduce the temperature anisotropy, and the growth rate becomes lower [5]. Therefore the amplitudes of the waves cannot grow beyond a certain degree, they get saturated as they are continuously responding to the slow changes in plasma conditions. Beside saturation, there may be other reasons for the significant difference between the growth rates determined here from the amplitudes of magnetic field variations and the growth rates provided by other models. The assumptions used here have some limitations, namely mirror mode waves simultaneously observed by the two distant satellites may not always originate from the same source as supposed in our study. Different local sources may be active at different times in the magnetosheath which may be located between the two observation points. However, when interplanetary conditions are quiet, local disturbances are less likely and changes in the magnetosheath plasma are expected to be smooth.

26.5 Summary In this study, four orbits were selected when the separation between the Cluster spacecraft was large and mirror mode fluctuations (mainly quasi-sinusoidal or peak type oscillations) were observed by all spacecraft in different regions of the terrestrial magnetosheath. The growth rates B D 0:001–0:008 s1 as estimated from the amplitudes of the magnetic field fluctuations observed simultaneously at distant locations were usually smaller than the maximum growth rates C D 0:001 0:03 s1 provided by the analytical formula of Liu et al. [11] using the locally measured plasma parameters. Other linear models [5, 8], which are valid when the amplitudes are small, obviously also predicted larger growth rates max Š 0:03 0:06 s1 for plasma and field parameters similar to those observed during the selected passes. The wide range for maximum growth rates 104 < max < 102 provided by Samsonov et al. [16] covers the B growth rate values determined in this study. According to the presented results, mirror mode waves do not grow beyond a certain degree, they seem to get saturated since they are continuously responding to any change in local plasma conditions. The effect of interplanetary parameters on the evolution of mirror mode waves was also investigated. Abrupt changes in solar wind dynamic pressure (usually occurring together with a sudden change in the IMF) move the magnetopause in or out influencing mainly theinnermost region of the magnetosheath. When the ion “ drops below a critical value “jj < 1 and the anisotropy increases above T? =Tjj > 1:7 after a sudden change in interplanetary conditions, mirror waves cannot be observed in the magnetosheath since the relation between “ and the temperature anisotropy does not favour the development of mirror mode waves [7, 10, 16]. Later, when the

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interplanetary activity gets quiet again, mirror mode waves can be observed mainly in the middle or outer regions of the magnetosheath, except for a few dips close to the magnetopause in the mirror stable plasma regions. An essential change in the direction of the IMF (with no significant variation in any other interplanetary parameter) may also influence the occurrence of mirror mode waves. When the interplanetary field gets quasi-parallel in the bow shock region connected by plasma flow-lines to the location of the satellite, no mirror mode waves are observed there. This result confirms the earlier suggestion of Tátrallyay et al. [19] that magnetosheath plasma connected to the compression region of quasiperpendicular bow shocks favour the growth of mirror mode waves.

References 1. Balogh, A., Carr, C.M., Acuna, M.H., et al.: The Cluster Magnetic Field Investigation: overview of in-flight performance and initial results. Ann Geophys. 19, 1207–1217 (2001) 2. Burlaga, L.F., Ness, N.F., Acuna, M.H.: Trains of magnetic holes and magnetic humps in the heliosheath. Geophys. Res. Lett. 33, L21106 (2006) doi:10.1029/2006GL027276 3. Erd˝os, G., Balogh, A.: Statistical properties of mirror mode structures observed by Ulysses in the magnetosheath of Jupiter. J. Geophys. Res. 101, 1–12 (1996) 4. Gary, S.P.: The mirror and ion cyclotron anisotropy instabilities. J. Geophys. Res. 97, 8519–8529 (1992) 5. Gary, S.P., Fuselier, S.A., Anderson, B.J.: Ion anisotropy instabilities in the magnetosheath. J. Geophys. Res. 98, 1481–1488 (1993) 6. Hasegawa, A.: Drift mirror instability in the magnetosphere. Phys. Fluids 12, 2642–2650 (1969) 7. Hellinger, P., Travnicek, P., Mangeney, A., Grappin, R.: Hybrid simulations of the magnetosheath compression: Marginal stability path. Geophys. Res. Lett. 30(18) (2003), doi:10.1029/2003GL017855 8. Hubert, D., Lacombe C., Harvey, C.C, et al.: Nature, properties, and origin of low-frequency waves from an oblique shock to the inner magnetosheath. J. Geophys. Res. 103, 26783–26798 (1998) 9. Kobel, E., Flückiger, E.O.: A model of the steady state field in the magnetosheath. J. Geophys. Res. 99, 23617–23622 (1993) 10. Lacombe, C. and Belmont, G.: Waves in the Earth’s magnetosheath: observations and interpretations. Adv. Space Res. 15(8/9), 329–340 (1995) 11. Liu, Y., Richardson, J.D., Belcher, J.W., Kasper, J.C., Skoug, R.M.: Plasma depletion and mirror waves ahead of interplanetary coronal mass ejections. J. Geophys. Res. 111, A09108 (2006), doi:10.1029/2006JA011723 12. Lucek, E.A., Dunlop, M.W., Balogh, A., et al.: Mirror mode structures observed in the dawnside magnetosheath by Equator-S. Geophys. Res. Lett. 26, 2159–2162 (1999) 13. Reme, H., Aoustin, C., Bosqued, J.M., et al.: First multispacecraft ion measurements in and near the Earth’s magnetosphere with the identical Cluster ion spectrometry (CIS) experiment. Annales Geophys. 19, 1303–1354 (2001) 14. Russell, C.T., Riedler, W., Schwingenschuh, K., Yeroshenko, Ye.: Mirror instability in the magnetosphere of comet Halley. Geophys. Res. Lett. 14, 644–647 (1987) 15. Russell, C.T., Song, P., Lepping, R.P.: The Uranian magnetopause: Lessons from Earth. Geophys. Res. Lett. 16, 1485–1488 (1989) 16. Samsonov, A.A., Alexandrova, O., Lacombe, C., et al.: Proton temperature anisotropy in the magnetosheath: comparison of 3-D MHD modelling with Cluster data. Ann Geophys. 25, 1157–1173 (2007)

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17. Soucek, J., Lucek, E., Dandouras, I.: Properties of magnetosheath mirror modes observed by Cluster and their response to changes in plasma parameters. J. Geophys. Res. 113, A04203 (2008), doi: 10.1029/2007JA012649 18. Tátrallyay, M. and Erd˝os, G.: The evolution of mirror mode fluctuations in the terrestrial magnetosheath. Planet. Space Sci. 50, 593–599 (2002) 19. Tátrallyay, M., Erd˝os, G., Balogh, A., Dandouras, I.: The evolution of mirror type magnetic fluctuations in the magnetosheath based on multipoint observations. Adv. Space Res. 41, 1537–1544 (2008) 20. Tsurutani, B.T., Smith, E.J., Anderson, R.R., et al.: Lion roars and nonoscillatory drift mirror waves in the magnetosheath. J. Geophys. Res. 87, 6060–6072 (1982) 21. Tsurutani, B.T., Lakhina, G.S., Smith, E.J., et al.: Mirror mode structures and ELF plasma waves in the Giacobini-Zinner magnetosheath. Nonlin. Proc. in Geophys. 6, 229–234 (1999) 22. Violante, L., Bavassano Cattaneo, M.B., Moreno, G., Richardson, J.D.: Observations of mirror waves and plasma depletion layer upstream of Saturn’s magnetopause. J. Geopys. Res. 100, 12047–12055 (1995) 23. Volwerk, M., Zhang, T.L., Delva, M., et al.: First identification of mirror mode waves in Venus’ magnetosheath? Geophys. Res. Lett. 35, L12204 (2008) doi: 10.1029/2008GL033621 24. Winterhalter, D., Neugebauer, M., Goldstein, B.E., et al.: Ulysses field and plasma observations of magnetic holes in the solar wind and their relation to mirror mode structures, J. Geophys. Res. 99, 23371–23382 (1994)

Part VI

Observations of Magnetopause and Cusp

Chapter 27

Mixed Azimuthal Scales of Flux Transfer Events R.C. Fear, S.E. Milan, E.A. Lucek, S.W.H. Cowley, and A.N. Fazakerley

Abstract Previous observations have allowed the scale size of flux transfer events (FTEs) to be determined both normal to the magnetopause and in the direction of motion of the FTE, but a key difference between some different models of FTE structure is their azimuthal scale size. Previous ground-based observations of the ionospheric signatures of FTEs indicated that magnetic reconnection can occur coherently over large extents of the magnetopause, but in situ determination of the azimuthal scale size of FTEs has not been possible until recent Cluster magnetopause crossing seasons when the separation of the spacecraft was 10;000 km. In this paper, we present Cluster observations of flux transfer events from the 27th March 2007, along with observations of the conjugate ionospheric signatures. We highlight two magnetospheric FTEs which were consistent with long X-line FTE models, but note also several FTEs with considerably smaller azimuthal scale.

27.1 Introduction Flux transfer events [15] are the time-varying embodiment of magnetopause reconnection [3]. Various attempts have been made in the past to quantify how much flux an FTE transfers into the magnetospheric system [11, 14–16], but these estimates are dependant on an assumption about the structure that an FTE takes. The original structure proposed was of an azimuthally narrow, elbow-shaped flux tube that crossed the magnetopause through an approximately circular hole [15], but subsequently other reconnection-based models were proposed which could extend significantly further azimuthally [10, 17, 20], and therefore could each reconnect more flux. R.C. Fear (), S.E. Milan, and S.W.H. Cowley University of Leicester, UK e-mail: [email protected] E.A. Lucek Imperial College London, UK A.N. Fazakerley Mullard Space Science Laboratory, University College London, UK


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Therefore, a key difference between some of these models is the azimuthal extent they can allow in comparison with their poleward extent. Since the scale of an FTE both normal to the magnetopause and in its direction of motion (poleward under strongly southward IMF) is typically of order 1–2 RE [4, 12, 14–16], observations from the Cluster spacecraft in their 10;000 km separation magnetopause crossing seasons (2006 onwards) can provide valuable information about whether the azimuthal scale of FTEs is comparable to or larger than their poleward extent. The first such FTE observations have recently been presented [5], but the magnetic shear across the magnetopause was comparatively low .110ı /. Whilst it was shown that the flux transfer events observed had a larger azimuthal extent than their poleward extent, the elbow-shaped flux rope model [15] could not be excluded completely. In this paper, we present a separate case study of flux transfer events observed by Cluster on the 27th March 2007 and their ionospheric signatures. At this time, the magnetic shear across the magnetopause was much closer to 180ı, which allows a clearer distinction between some of the models. Magnetic field data are provided at 5 Hz resolution from the Cluster FGM instrument [1], electron data from the Cluster PEACE instrument [7], and ionospheric observations from the SuperDARN radars [2].

27.2 Cluster Orientation and Solar Wind Conditions Figure 27.1 illustrates the location and orientation of the Cluster spacecraft (the tetrahedron has been expanded by a factor of two relative to the location of Cluster 1). In this and all subsequent figures, the Cluster spacecraft are denoted by a consistent colour scale which is shown in the legend. The model magnetopause (dashed line) and bow shock (dash-dot) are derived from the models by Shue et al. [18] and Peredo et al. [13], using upstream conditions as model inputs. The spacecraft were at

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Fig. 27.2 OMNI lagged solar wind conditions. From top: the IMF GSM components and magnitude, the magnitude of the IMF clock angle (expressed between 0ı and 180ı ) and the solar wind dynamic pressure

low latitudes in the northern hemisphere, near local noon. Typically for early 2007, the spacecraft were in a flat triangular formation, rather than a good quality tetrahedron, with the surface of the triangle being contained approximately in a plane tangential to the magnetopause surface. The solar wind conditions are shown in Fig. 27.2, which contains propagated observations from the OMNI database. These data were taken by the Wind spacecraft, which was situated 198 RE upstream of the Earth, and they have been propagated to the Earth’s bow shock using a variable lag time [9]. At 0440 UT, the interplanetary magnetic field (IMF) rotated southward, and the clock angle remained close to 180ı until 0550 UT, except for a brief downward rotation between 0510 and 0520 UT. We shall present the Cluster data in a boundary normal coordinate system [15], which was derived as follows. The unit vector normal to the magnetopause was derived by carrying out minimum variance analysis [19] on the Cluster magnetic field data between 0500 and 0512 UT (the Cluster spacecraft all crossed the magnetopause at around 0506 UT). The largest ratio between the intermediate and minimum eigenvalues was observed using Cluster 4 data .œint =œmin D 3:74/, so we adopted the minimum eigenvector from the magnetopause crossing made by Cluster 4 as the normal vector Œn D .0:938; 0:044; 0:342/GSE . The azimuthal vector was derived by normalising the cross product of n with the Earth’s dipole vector

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Fig. 27.3 The orientation of the Cluster tetrahedron, relative to Cluster 3, in boundary normal coordinates at 05:15 UT on the 27th March 2007

Œm D .0:174; 0:917; 0:359/GSE , and the poleward vector completes the righthanded set Œl D m n D .0:298; 0:397; 0:868/GSE . The coordinates n, m and l therefore correspond closely to the GSE x, y and z vectors, as is expected for a low-latitude, near-noon magnetopause crossing. The Cluster spacecraft separation is shown in these boundary normal coordinates in Fig. 27.3. The spacecraft formed a roughly equilateral triangle in the l-m plane, with each side of order 8,000 km. The maximum separation of the spacecraft normal to the nominal magnetopause was 1,200 km.

27.3 Extent of Dayside Reconnection: Ionospheric Signatures We first investigate the ground-based radar observations of the ionospheric signatures of FTEs to show the azimuthal extent over which magnetopause reconnection was taking place. Ionospheric observations from the Hankasalmi and TIGER coherent scatter radars (part of the SuperDARN network) are shown in Fig. 27.4. The Hankasalmi radar is situated in Finland, and has a field of view that is directed towards magnetic north. TIGER is situated in Tasmania, and its field of view is directed towards magnetic south. The top two panels show a snapshot of the ionospheric velocities from the entire fields of view of these two radars at 0508 UT; each panel is a polar grid of magnetic local time against magnetic latitude with 12 h MLT directed towards the top, and 06 h MLT directed towards the right. Both radars observed strong flows away from the radars (shaded red) in the beams that are directed poleward. TIGER also observed more azimuthal flows toward the radar (blue). Both are consistent with a twin-cell convection pattern. Time series of these observations are shown in the bottom half of Fig. 27.4. The top two panels show the ionospheric velocities against magnetic latitude (and time). Each panel shows data from one radar beam (beam 15 from Hankasalmi and beam 0 from TIGER). The bottom two panels show the corresponding backscatter power data. Three patches of enhanced backscatter power were observed by each radar, which propagated poleward, and which corresponded to enhanced ionospheric flows. These Poleward Moving Radar Auroral Forms (PMRAFs) are the ionospheric signature of time-varying magnetopause reconnection (Milan et al. [11]

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and references therein). The second and third PMRAFs observed by Hankasalmi correspond well with the first and second PMRAFs observed by TIGER. The fact that the Hankasalmi and TIGER radars observed PMRAFs in the post- and pre-noon sectors respectively indicates that pulsed reconnection was occurring over a large

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part of the magnetopause during this interval. As there is a gap in radar coverage around 12 h MLT, it cannot be shown that pulsed reconnection occurred along this entire sector of local time, but we note that the magnetic footprint of the Cluster spacecraft is in this region. As will be shown in the next section, signatures of pulsed reconnection were also observed by Cluster.

27.4 In Situ Observations: FTEs and Their Azimuthal Extent Cluster observations of the flux transfer events before and after the spacecraft crossed the magnetopause are shown in Figs. 27.5 and 27.6. In each figure, the top two panels show the components of the magnetic field tangential to the magnetopause, followed by the BN components observed by the four spacecraft, which are ordered by the positions of the spacecraft (equatorward to poleward: C3, C4, C1 and C2). The next panel shows a spectrogram of the electrons observed moving away from the magnetopause by Cluster 2 (0ı and 180ı pitch angles in Figs. 27.5 and 27.6 respectively). The angle between the magnetic field observed by Cluster 3 and the l vector .’LM /, and the IMF clock angle .™CA / are shown in the penultimate panel by green and purple traces respectively, and the magnetic field magnitude is shown in the bottom panel.

Fig. 27.5 Magnetospheric FTEs observed by Cluster. From top: The magnetic field components observed by the four Cluster spacecraft, a spectrogram of 0ı pitch angle electrons, the angle between the magnetic field observed by Cluster 3 and the vector l (green trace) and IMF clock angle (purple), and the magnetic field strength

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Fig. 27.6 Magnetosheath FTEs observed by Cluster. The spectrogram shows 180ı pitch angle electrons; the format is otherwise the same as Fig. 27.5

Before 0504 UT, all four spacecraft were in the magnetosphere, and observed a magnetic field which was almost entirely in the l component. At 0504 UT Clusters 2 and 3 crossed the magnetopause, followed by Clusters 1 and 4 at 0508 UT. The magnetosheath magnetic field was largely in the negative l direction .’LM D 180ı/, except between 0515 and 0524 UT when ’LM dropped to 150ı (observed in ™CA between 0509 and 0516 UT, and indicating that the IMF lag is too small). Between 0450 and 0524 UT, all four Cluster spacecraft observed bipolar variations of the BN component which are characteristic signatures of flux transfer events. We identify five FTEs which were clearly observed by all four spacecraft, which are indicated by vertical purple lines in Figs. 27.5 and 27.6. Two of these FTEs (at 04:56 and 05:22 UT) exhibited signatures at C3 and C4 that were not clearly bipolar, but they are similar enough to the other signatures observed for us to regard them as ‘irregular’ polarity FTEs [14]. In each case, the FTE was observed first by C3 and C4 (simultaneously), then by C1 and C2 (at approximately the same time as each other, but 30–60 s after C3). This order indicates a northward motion which is consistent with the ‘standard’ polarity of the BN signatures that was observed whenever the polarity was clear [14]. Since the Cluster tetrahedron had little extent in the n dimension, we cannot obtain a reliable three-dimensional velocity for these two FTEs by conventional multi-spacecraft timing analysis [6]. Therefore, we use the time delays between the FTEs being observed at Cluster 4 (which we take as a reference spacecraft) and Clusters 1 and 2 to obtain the FTE velocities in the l-m plane (which does contain large spacecraft separations as shown in Fig. 27.3).

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R.C. Fear et al. Table 27.1 2D FTE velocities determined from three-spacecraft Time (UT) dt41 .s/ dt42 .s/ jvj.km s 1 / vO LM 04:54:20 15.8 32.4 257 (0.932, 0.363) 04:56:20 37.8 32.6 197 (0.959, 0:285) 05:14:40 18.2 18.8 393 (0.990, 0:140) 05:17:52 27.4 61.4 168 (0.950, 0.312) 05:22:31 59.0 61.6 122 (0.991, 0:132)

timing Angle to l 21ı 16ı 8ı 18ı 8ı

The results are shown in Table 27.1. The two magnetospheric FTEs were observed to move at speeds of 257 and 197 km s1 , in a largely poleward direction. Such a direction of motion is expected from the fact that there are no significant azimuthal forces exerted on the reconnected flux tubes by either the magnetic tension in the reconnected field lines or the magnetosheath flow. Unfortunately, neither of these FTEs exhibited plasma signatures at any of the spacecraft (i.e. the draping region alone was observed). We therefore take the “characteristic time” (the time difference between the positive and negative peaks of BN , as defined by Kawano et al. [8]) as a proxy for the duration of the FTE. These two FTEs had characteristic times of 26 and 29 s respectively; these correspond to poleward extents of 6,700 and 5,700 km respectively, which is smaller than the 8,500 km azimuthal separation of Clusters 1 and 2. Consequently, it appears that these two FTEs have a larger azimuthal than poleward extent; in such conditions of high magnetic shear this is more consistent with extended X-line models of FTEs (e.g. [10, 17, 20]). However, there are some interesting differences between spacecraft in some other FTEs which were observed, and which are indicated by green arrows in Fig. 27.5. At 0455 UT an FTE was observed at Clusters 1, 3 and 4 (most clearly at Cluster 1). However, no BN signature is evident at Cluster 2. Considering that Cluster 2 was nearer the magnetopause than Cluster 1 and crossed the magnetopause before Cluster 1 (see Figs. 27.3 and 27.6), this implies that the azimuthal extent of this FTE is more limited. The dearth of FTEs at Cluster 1 between 0458 and 0502 UT could be explained by the fact that Cluster 1 is the furthest spacecraft from the magnetopause, but considering the size of the FTEs observed by Cluster 2 at 0459 and 0502 UT, and the fact that the separation between Clusters 1 and 2 normal to the magnetopause is only 1,200 km, it is perhaps more likely that these are also more azimuthally-limited features. Finally, between 0502 and 0504 UT, Cluster 2 observed three FTEs whilst Cluster 1 only observed a single event. The magnetosheath observations are shown in Fig. 27.6. The three FTEs identified at all four spacecraft are again indicated by purple lines. All three occurred during the interval where the magnetosheath magnetic field rotated dawnward (’LM , penultimate panel), caused by the rotation in the lagged IMF clock angle observed a few minutes before. The electron signature observed at 0514 UT was not clearly distinct from that of the previous FTE, but distinct electron signatures were observed for the other two FTEs, most clearly in the antiparallel pitch angle bin at Cluster 2. Three distinct electron energy enhancements were observed during the course of the

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0518 FTE; the time from the beginning of the first enhancement to the end of the last was 60 s. A single electron signature was observed at 0523 UT, which lasted 67 s. Multiplying these durations by the speeds reported in Table 27.1 gives poleward scale sizes of 8,200 and 10,000 km respectively (these two FTEs had a lower speed than those observed before the magnetopause crossing). Prior to 0515 UT, the rate at which FTEs were observed was higher, due at least in part to the proximity of the spacecraft to the magnetopause. It is therefore harder to link specific FTEs at different spacecraft with a high degree of certainty. However it is again clear that there are significant differences between Clusters 1 and 2, separated predominantly in the azimuthal direction. We highlight two FTEs in Fig. 27.6 which were observed by a subset of the spacecraft (both indicated by a green arrow). Clusters 3, 4 and 2 observed a clear FTE at 0513 UT, which was not observed by Cluster 1, despite the fact that this spacecraft was now the closest to the magnetopause. Cluster 1 alone observed a clear FTE at 0516 UT; recalling again that the maximum separation of the spacecraft normal to the magnetopause was only 1,200 km, this also suggests a spatially-limited structure.

27.5 Summary We have presented ground- and space-based observations of flux transfer events during an interval when the IMF clock angle was near 180ı and Cluster was near magnetic noon. The ionospheric observations indicate that pulsed magnetic reconnection occurred over a large part of the dayside magnetopause. Some FTEs were observed at all four spacecraft indicating that they extended azimuthally by at least 8,500 km. In some cases, this is larger than their observed poleward scale size, consistent with long X-line models of FTE formation. However, there are also significant differences in FTE observation on these azimuthal scales, implying that FTEs can also occur more patchily. These FTEs could be explained by any of the models. Acknowledgments OMNI data obtained from the GSFC/SPDF OMNIWeb interface at http://omniweb.gsfc.nasa.gov, and based upon Wind MFI and SWE observations courtesy of R. Lepping and K. Ogilvie. Work at Leicester was supported by Science and Technology Facilities Council (STFC) grant PP/E000983/1. Cluster data analysis was done with the QSAS science analysis system provided by the United Kingdom Cluster Science Centre, supported by STFC.

References 1. Balogh, A., Carr, C. M., Acuña, M. H., Dunlop, M. W., Beek, T. J., Brown, P., Fornaçon, K.-H., Georgescu, E., Glassmeier, K.-H., Harris, J., Musmann, G., Oddy, T., and Schwingenschuh, K.: The Cluster Magnetic Field Investigation: Overview of in-flight performance and initial results. Ann. Geophys., 19, 1207–1217 (2001). http://www.ann-geophys.net/19/1207/2001/

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2. Chisham, G., Lester, M., Milan, S. E., Freeman, M. P., Bristow, W. A., Grocott, A., McWilliams, K. A., Ruohoniemi, J. M., Yeoman, T. K., Dyson, P. L., Greenwald, R. A., Kikuchi, T., Pinnock, M., Rash, J. P. S., Sato, N., Sofko, G. J., Villain, J.-P., Walker, A. D. M.: A decade of the Super Dual Auroral Radar Network (SuperDARN): scientific achievements, new techniques and future directions. Surv. Geophys., 28, 33–109 (2007). doi:10.1007/s10712007-9017-8 3. Dungey, J. W.: Interplanetary magnetic field and the auroral zones. Phys. Rev. Lett., 6, 47–48 (1961). doi:10.1103/PhysRevLett.6.47 4. Fear, R. C., Milan, S. E., Fazakerley, A. N., Owen, C. J., Asikainen, T., Taylor, M. G. G. T., Lucek, E. A., Rème, H., Dandouras, I., and Daly, P. W.: Motion of flux transfer events: A test of the Cooling model. Ann. Geophys., 25, 1669–1690 (2007). http://www.anngeophys.net/25/1669/2007/ 5. Fear, R. C., Milan, S. E., Fazakerley, A. N., Lucek, E. A., Cowley, S. W. H., and Dandouras, I.: The azimuthal extent of three flux transfer events. Ann. Geophys., 26, 2353–2369 (2008). http://www.ann-geophys.net/26/2353/2008/ 6. Harvey, C. C.: Spatial gradients and the volumetric tensor. In: Paschmann, G., Daly, P.W. (eds.) Analysis Methods for Multi-Spacecraft Data, pp. 307–348, ISSI, Berne (1998) 7. Johnstone, A. D., Alsop, C., Burdge, S., Carter, P. J., Coates, A. J., Coker, A. J., Fazakerley, A. N., Grande, M., Gowen, R. A., Gurgiolo, C., Hancock, B. K., Narheim, B., Preece, A., Sheather, P. H., Winningham, J. D., and Woodliffe, R. D.: PEACE: A Plasma Electron and Current Experiment. Space Sci. Rev., 79, 351–398 (1997). doi:10.1023/A:1004938001388 8. Kawano, H., Kokubun, S., and Takahashi, K.: Survey of transient magnetic field events in the dayside magnetosphere. J. Geophys. Res., 97, 10 677–10 692 (1992) 9. King, J. H. and Papitashvili, N. E.: Solar wind spatial scales in and comparisons of hourly Wind and ACE plasma and magnetic field data. J. Geophys. Res., 110, A02104 (2005). doi:10.1029/2004JA010649 10. Lee, L. C. and Fu, Z. F.: A theory of magnetic flux transfer at the Earth’s magnetopause. Geophys. Res. Lett., 12, 105–108 (1985) 11. Milan, S. E., Lester, M., Cowley, S. W. H., and Brittnacher, M.: Convection and auroral response to a southward turning of the IMF: Polar UVI, CUTLASS, and IMAGE signatures of transient magnetic flux transfer at the magnetopause. J. Geophys. Res., 105, 15741–15756 (2000). doi:10.1029/2000JA900022 12. Owen, C. J., Fazakerley, A. N., Carter, P. J., Coates, A. J., Krauklis, I. C., Szita, S., Taylor, M. G. G. T., Travnicek, P., Watson, G., Wilson, R. J., Balogh, A., and Dunlop, M. W.: Cluster PEACE observations of electrons during magnetospheric flux transfer events. Ann. Geophys., 19, 1509–1522 (2001). http://www.ann-geophys.net/19/1509/2001/ 13. Peredo, M., Slavin, J. A., Mazur, E., and Curtis, S. A.: Three-dimensional position and shape of the bow shock and their variation with Alfvenic, sonic and magnetosheath Mach numbers and interplanetary magnetic field orientation. J. Geophys. Res., 100, 7907–7916 (1995) 14. Rijnbeek, R. P., Cowley, S. W. H., Southwood, D. J., and Russell, C. T.: A survey of dayside flux transfer events observed by ISEE-1 and ISEE-2 magnetometers. J. Geophys. Res., 89, 786–800 (1984) 15. Russell, C. T. and Elphic, R. C.: Initial ISEE magnetometer results: Magnetopause observations. Space Sci. Rev., 22, 681–715 (1978). doi:10.1007/BF00212619 16. Saunders, M. A., Russell, C. T., and Sckopke, N.: Flux transfer events: Scale size and interior structure. Geophys. Res. Lett., 11, 131–134 (1984) 17. Scholer, M.: Magnetic flux transfer at the magnetopause based on single X-line bursty reconnection. Geophys. Res. Lett., 15, 291–294 (1988) 18. Shue, J.-H., Chao, J. K., Fu, H. C., Russell, C. T., Song, P., Khurana, K. K., and Singer, H. J.: A new functional form to study the solar wind control of the magnetopause size and shape. J. Geophys. Res., 102, 9497–9511 (1997) ¨ and Cahill, Jr., L. J.: Magnetopause structure and attitude from Explorer 12 19. Sonnerup, B. U. O. observations. J. Geophys. Res., 72, 171–183 (1967) 20. Southwood, D. J., Farrugia, C. J., and Saunders, M. A.: What are flux transfer events? Planet. Space Sci., 36, 503–508 (1988). doi:10.1016/0032-0633(88)90109-2

Chapter 28

Perspectives Gained from a Combination of Polar, Cluster and ISEE Energetic Particle Measurements in the Dayside Cusp T.A. Fritz

Abstract Energetic particles are a consistent and common feature of the high-altitude dayside cusp. Observing these particles in a region where they cannot be stably trapped is one of the most striking findings of the Polar and Cluster satellites. The source of these cusp energetic particles (CEP) has centered on the possible role of the bow shock, leakage from the magnetosphere, and local acceleration within the cusp itself. The Polar satellite has documented that the shocked solar wind plasma enters the weak geomagnetic field of the polar region and produces cusp diamagnetic cavities (CDC) of apparent tremendous size .6 RE / well within the traditional magnetosphere. Within these cavities the local magnetic field is depressed and very turbulent. The intensities of the energetic ions are observed to increase by many orders of the magnitudes during the CDC encounters. The four Cluster spacecraft have typically not observed such a large cusp and extended diamagnetic cavity. The search for evidence to resolve this inconsistency led to a revisiting of ISEE 1 and 2 satellite measurements during two encounters with the high altitude cusp. In each of these cases the very good energy and angular resolution of the ISEE energetic particle experiment revealed that energetic ions within the cusp located at GSM Z ranging from 4 RE to 5 RE appeared from closer to the Earth and streamed outward in very close association with the diamagnetic cavities in the measured magnetic field. The electrons demonstrated a peaked at 90ı pitch angle distribution indicative of being confined within a cusp minimum field trap. In one of these cases the electron fluxes peak near the cusp boundary and in the other case they sharply define the CDC boundaries varying in a strictly anticorrelated manner during a large geomagnetic storm. The charge state distribution of these cusp cavity ions is indicative of their seed populations being a mixture of ionospheric and solar wind particles in many cases. Taken together these facts argue for a local acceleration of plasma within the cusp to many 10s and 100s of keV. By their geometry cusp magnetic field lines are connected to all of the magnetopause boundary layers and these cusp charged particles will form an energetic particle layer on the magnetopause. A source of energetic particles in the dayside T.A. Fritz () Center for Space Physics, Boston University, Boston, MA 02215, USA e-mail: [email protected]


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high-altitude CDC will be effective in transferring the solar wind energy, mass, and momentum into the Earth’s magnetosphere and could provide the source of the ring current ions.

28.1 Introduction The concept of the magnetosphere cusp prior to the Polar and Cluster missions was that of a narrow funnel-shaped volume in the sub-solar region that contains open geomagnetic field lines that topologically form the magnetopause. The region of the cusp has been studied and characterized at low altitudes where the narrow geometry seems to be consistent with observations [13, 14]. At higher altitude controversy exists as to what the topology might be and there are a plethora of names that have been created to cover this confusion. The most striking and significant finding of the Polar satellite is that energetic particles are observed to be consistently and continuously present in this high latitude, high altitude dayside cusp region where they cannot be stably trapped yet occupy the same region as the shocked solar wind. “Energetic” refers to ions with energies greater than 25 keV with upper limits being in the 100s of keV to MeV energies. The source of these energetic particles remains a topic of debate and scientific discussion. The initial observations of such energetic particles in this region were described by Shabansky [19] who interpreted them to be the result of the azimuthal drift of radiation belt particles caused by gradient and curvature effects in the geomagnetic field. These particles over a narrow range of radial distances will move to high latitudes as they follow the magnetic field minimum into this region. More recently Chen et al. [3, 4] and Fritz et al. [9] have reported observations of cusp energetic particles (CEP) and argued that they are accelerated locally within the cusp.

28.2 Polar Observations In April 1999 the Polar satellite observed regions of shocked solar wind plasma for many hours at a time at locations well inside the nominal location of the magnetopause. Polar was launched into a 1.8 by 9 RE orbit on February 24, 1996 with an inclination of 86ı . On board Polar, the Magnetospheric Ion Composition Spectrometer (MICS), a part of the Charge and Mass Magnetospheric Ion Composition Experiment (CAMMICE), is a one-dimensional time-of-flight electrostatic analyzer with post acceleration measuring ions with an energy/charge of 1–220 keV/e with very good angular resolution. The MICS, mounted perpendicular to the spin axis, is able to obtain a two-dimensional distribution at one energy per charge during each 6 s spin period. A complete energy spectrum is obtained in 32 spin periods. Polar was located on the morning side of local noon and was near to apogee of 9 RE when it became immersed in these extended regions of shocked solar wind plasma.

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Fig. 28.1 Polar pass through the dayside cusp on 20 April 1999. The five panels on the left side of this figure are energy spectrograms of the major ion species. The top panel labeled OC6 displays the intensity as function of energy for the high charge state oxygen ions characteristic of the solar wind. In the second panel the intensity of oxygen ions with charge states associated with an ionospheric source are displayed. The threshold energy of 50 keV for the detection of these OC , OCC ions is much higher than that of OC6 shown in the first panel and is due to an instrumental threshold for the unique identification of these ions. In the third and fourth panels the two charge states of Helium ions are displayed. In the fifth panel the energy spectrogram for hydrogen ions (protons) is displayed. The vertical scale on the far left indicates the energy of the ions in keV. The color bars indicate the intensity of the various ion species in particles/s cm2 sr keV. On the upper right side the figure is the orbit of Polar in SM coordinates (provided by NASA/GSFC SPOF). The red trace along the orbit marks the location of the region corresponding to the same red bar in the top left panel. The bottom right panel displays the measurement of the magnetic field [17]

In Fig. 28.1 a three part figure of data obtained by Polar on April 20, 1999 is displayed. Polar was northward bound through the radiation belts from 07 UT to about 12 UT. The CAMMICE/MICS sensor with it selection by energy/charge followed by a post acceleration of 20 kV/charge is able to measure the intensity of these ion species to energies of less than 1 keV. Note the abrupt appearance of intense fluxes of these shocked solar wind ions at 12 UT which lasted until 18W20 UT in Fig. 28.1. Although lacking the lower energies (50 keV) OC ions of presumed ionospheric origin were observed to be present at the same location as the oxygen ions of solar wind origin. A similar picture holds for the helium ions as well. HeCC (or alpha particles) are abundantly present in the solar wind but HeC is the dominant charge state in

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the ionosphere. At 12 UT there was an abrupt increase in the fluxes of the low energy HeCC that lasted until about 18:20 UT and showed the same variations in time as the high charge state oxygen ions in the top panel. HeC ions were present as well at higher energies indicating a mixture of ions from two separate origins. The hydrogen ions presented in the fifth panel also indicate that an abrupt increase in the intensity of protons most noteable for energies 25 keV ions present during the 12–18 UT interval reaching the upper energy cutoff of the MICS sensor (200 keV) in the case of the protons. In the other two sections of Fig. 28.1 note that as Polar approached apogee the magnetic field decreased gradually to nominal values of 60 to 70 nT but from 12 UT to 18 UT the field was further depressed with large fluctuations of high frequency some of which appear to approach extremely small values (e.g., 0 nT). This behavior and the occurrence of a near zero magnetic field in the cusp was noted by Russell et al. [18]. These observations by the Polar satellite indicate that shocked solar wind ions that are associated with the magnetospheric cusp were continuously present for a period of 6 h. These ions appear to create a diamagnetic cavity of large dimensions (but this could be a series of many smaller cavities) with the magnetic field demonstrating large fluctuations and turbulence, a region described as a Cusp Diamagentic Cavity or CDC. The presence of very energetic 10s and 100s of keV ions co-located with the intense solar wind ions is surprising as these ions should have a short lifetime against loss of seconds in an open field line topology associated with the magnetic cusp. The energetic particles have been first described by Chen et al. [3,4] as Cusp Energetic Particles or CEP. Upstream at the L1 liberation point the ACE satellite was measuring a steady solar wind (data not shown) with a measured pressure of 4 nPa. At 15W30 UT the pressure ramped up to a peak of 8nPa. The IMF was also fairly steady with positive By and negative Bx for most of the 6 h interval. Bz was initially negative, switched positive at 14W20 UT, negative again at 15:30 UT, then back positive at 16:15 UT where it remained for the rest of the interval. In Fig. 28.2 in the same format as Fig. 28.1 the Polar data are displayed for April 24, 1999. Polar encountered a region of solar wind plasma from 08:00 UT to 12:10 UT, a period of more than 5 h, on this day. In this case the features of a particle spectrum extending to very energetic particles (CEP) are coincident with a depressed and turbulent measured magnetic field (CDC) that averaged about 20 nT over the bulk of the diamagnetic cavity with many measured values close to 0 nT. This same behavior is basically observed by Polar pass after pass through the dayside cusp region. Upstream at the ACE spacecraft the solar wind was again fairly steady with a pressure of 3 nPa. The orientation of the IMF is such that all three GSM components are positive with Bz very small. Niehof et al. [15] have shown that not all cusp crossings by Polar consist of CDC and CEP events but rather that these are features within a possibly broader cusp. Finkemeyer et al. [6] and Fritz et al. [8] reported that the CDC/CEP features are found in 90% of the Polar crossing of the cusp during the first 2 years of Polar operations. Niehof et al. [15] further found that the variations of the magnetic field and particle fluxes were strongly anti-correlated inside the

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Fig. 28.2 Polar pass through the dayside cusp on 24 April 1999 in the format of Fig. 28.1

CDC cavities and that this anti-correlation existed at the maximum time resolution available for the particle fluxes which for the Polar Hydra experiment was 13.8 s. This particular cusp crossing by Polar has been discussed by Rae et al. [16] who argued that the variations of particle intensity and magnetic field in the cusp were caused by Alfven waves upstream of the magnetopause. These authors based their discussion on variations in the magnetic field and particle fluxes being out of phase, that is, anti-correlated. While it may be possible for such upstream waves to modulate the entry of the shocked solar wind into the cusp, such waves or any other feature in the upstream magnetosheath appear unlikely to produce the CEP particles as a Polar pass on April 21, 1999 demonstrated. During this pass presented in Fig. 28.3 CEP particles were present as Polar first entered the cusp (denoted as region A), were absent as Polar moved into the magnetosheath (region B), and were again present as Polar returned to the cusp (region C). As Polar encountered the cusp with a CDC/CEP at 0643 UT the particles present were of solar wind origin HeCC with an energetic (25 to >200 keV) component present of the same composition. A pressure pulse in the solar wind shown in the middle panel of Fig. 28.3 struck the magnetopause at 0730 UT pushing the magnetopause in over Polar. Polar remained in the magnetosheath from 0730 UT until returning to the cusp at 0920 UT. During this period the characteristics of the magnetic field variations changed and the solar wind velocity along GSE X jumped to approximately 200 km=s

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Fig. 28.3 Polar and Wind observations on 21 April 1999. The Wind measurements of the solar wind pressure have been propagated to the subsolar magnetopause by the measured solar wind velocity. The color-coded intensity scale for the Polar proton and alpha particle fluxes are the same as those shown in Figs. 28.1 and 28.2. The region between the two red lines labeled B is the magnetosheath while the regions A and C between the red and black lines have the properties described in the text for a CDC and CEP region

indicative of being in the magnetosheath. No energetic particles were observed in the magnetosheath. Upon reentering the cusp, CEP particles were again observed until Polar moved into the polar cap around 12:00 UT. In this event there were no energetic particles in the magnetosheath but they were present during the two CDC intervals that sandwiched this excursion into the magnetosheath. This argues that processes external to the cusp were not responsible for producing the CEP particles in the magnetosheath or bow shock that then find their way into the cusp.

28.3 Cluster Observations Cluster on the other hand has rarely observed a cusp similar to those that are very frequent in the Polar data. On some occasions the satellites did detect a CDC in combination with simultaneously enhanced energetic ion fluxes (e.g., [1, 20]). Usually Cluster sampled what has be-come known as the Stagnant Exterior Cusp or SEC [12]. Zhang et al. [24] found that energetic particles were present on 80% of the Cluster cusp crossings during the first 2 years of Cluster operations but the magnetic field was rarely depressed for an extended period and those energetic particles

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Fig. 28.4 An overview of Cluster Ion Spectrometer (CIS), Fluxgate Magnetometer (FGM), and Research with Adaptive Particle Imaging Detectors (RAPID) data from 10 to 13 UT on 23 March 2002. (a) Plasma density, (b) plasma velocity Vx component, and (c–e) magnetic field components in the GSM coordinate system (in nT). (f–i) Energetic electron, proton, helium, and heavy ion flux. Note that the energetic particles are confined to the cusp boundary. The energy ranges shown are: Electrons (>30 keV), Protons and He (>30 keV), Heavy Ions (>210 keV) (From [24])

present were usually associated with a cusp boundary. An example occurring on March 23, 2002 that she has published showing the association of these particles with the cusp boundary is presented in Fig. 28.4. Examples of Cluster magnetic field observations in the outer cusp are shown in Fig. 28.5 [5] indicating a cusp diamagnetic cavity of only some 10 min duration.

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28.4 ISEE 1 and 2 Observations This dichotomy in the impression of the energetic particles within the cusp gained from the Polar and Cluster missions suggested that an examination of data from the older International Sun Earth Explorer (ISEE 1 and 2) satellites may indicate encounters with the cusp. This would allow the very good energy and angular resolution of the energetic particle experiment on these satellites to be used. Two events, where ISEE 1 and 2 were in the cusp, have been reported by Whitaker et al. [22, 23] and Walsh et al. [21]. On September 29, 1978, the two ISEE satellites were outbound in near identical orbits close to local noon and each encountered a CDC. The event happened during a major magnetic storm where the upstream Bz was about 30 nT, Dst went to 224 nT, the hourly AE index reached 775 nT and the dynamic pressure increased by a factor of 3. Surprisingly ISEE-2 slightly ahead of ISEE-1 entered the CDC almost 30 min before ISEE-1 and stayed in the cavity for almost 1 h as seen in Fig. 28.6. Both satellites exited the CDC within 6 min of one another. This implies that the boundary of the CDC maintained a location between the two satellites for 27 min and must therefore have been in motion. Figure 28.7 shows ISEE-1 data as that satellite entered and exited the CDC. Although the time resolution of the composition data is poorer than the particle and magnetic field data, it is clear that the CDC was filled with a combination of solar HeCC

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Fig. 28.6 Trajectory in GSM of ISEE-1 and 2 on September 29, 1978 (figure 1 from [21]).The X’s indicate the initial entrance and final exit of the CDC cavity

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Fig. 28.7 ISEE-1 data on September 29, 1978. The top panel shows data from the Plasma Experiment (40 eV–17.36 keV), where triangles, X’s, open squares, and diamonds correspond to HC , HeCC , HeC , and OC ions respectively. The time resolution for the plasma data is 18 min. The second and third panels contain the proton and electron fluxes respectively, integrated over all pitch angles for four energy channels measured by ISEE-1. The proton and electron flux are presented with a time resolution of 36 s. Panel four shows the total local magnetic field strength. The local magnetic field strength is displayed with 4 s resolution. The four zones of increased flux are marked with vertical dotted lines and labeled sequentially in panels three and four (figure 2 from [21])

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Fig. 28.8 ISEE-1 energetic ion spectrum for the event period of Fig. 28.7. Note the lack of any energy dispersion with time in the intensity of the ions during this encounter with a CDC (From the MIDL Application at http://sd-www.jhuapl.edu/MIDL/)

and ionospheric HeC ; OC ions. There appear to have been multiple cavities that ISEE-1 encountered with the energetic electrons defining each cavity exactly. This is true of the fluxes at all energies shown from 20 to 190 keV. The variation of the ions is similar to the electrons with the ions intensities remaining high and extending beyond the sharp cavity boundary locations shown in the magnetic field and electron data. There is an absence of any velocity dispersion in the case of both the electrons and the ions indicating there was essentially no magnetic gradient or curvature drift from the source responsible for their energization. An energy spectrum of the ions is shown in Fig. 28.8 indicating that there is little, if any, energy dispersion in the appearance of the energetic ions and the process for energization of these ions must be able to produce energies in excess of 1 MeV. Furthermore the pitch angle distributions of these particles shown below in Figs. 28.10–28.12 provide strong evidence of a local mechanism for the acceleration of these particles. In order to interpret the format of these figures the energetic ions (24 to 45 keV) are displayed in a latitude/longitude mapping of the unit sphere and shown in Fig. 28.9 for a normal peaked-at-90ı pitch angle distribution. In Fig. 28.10 the three dimensional distribution these ions are presented in the format described in Fig. 28.9 and its caption. These ions have a consistent distribution showing the hemisphere centered on a pitch angle of 180ı fully filled while the opposite hemisphere is devoid of particles indicative of these fluxes moving away from Earth. Figures 28.8 and 28.11 illustrate that the source of these energetic ions is active into the 100s of keV of energy. Figure 28.12 is the display for same period but for energetic electrons with energy from 22.5 to 39.0 keV. The electron 3-D distributions are different from the ions in that they show a sharply peaked at 90ı distribution indicative of a trapped distribution. If the CDC is the energization source/location of these electrons they can become trapped in the magnetic field minimum of the cavity producing the distribution observed. Note the three panels on the left side of the bottom row which show a region where electrons were flowing from a region closer to the Earth just before ISEE-1 left the CDC cavity. The hemisphere centered on the anti-field line


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Fig. 28.9 This figure demonstrates how one interprets Figs. 28.10–28.12. The detector scans through the unit sphere in 36 s (left) and the fluxes are linearly translated from elevation and azimuth onto an orthogonal Cartesian coordinate system (right) that is essentially the GSE coordinate system. The horizontal axis has GSE X at 0ı and GSE Y at 90ı . The vertical axis has the GSE X, Y plane at the midplane of the figure, the GSE – Z axis is at the bottom and the GSE C Z axis at the top of the figure. The red line corresponds to the locus of all 90ı pitch angles. The pitch angle contours are determined by calculating the angle between the instantaneous magnetic field vector [17] and the sensor viewing direction and then overlaying the contoured array onto the plot on the right. The blue arrow is the magnetic field vector, where it points from the center of the 30ı contour to the center of the 150ı contour in the display on the right

direction remains filled for over 100 s. The velocity of these electrons is about 0.3 c at these energies so they will travel over 15 earth radii in 1 s. The most likely explanation for their being observed for 100 s is that they are created by a local source. The cusp is therefore most likely the location for the energization of ions and electrons to many 10s and 100 of keV. A possible engerization mechanism for such a source in the cusp has recently been described by Chen [2].

28.5 Conclusions The observations presented here demonstrate that the cusp is most likely a location capable of producing electrons and ions with energies of many 10s and 100s of keV from a source population that consists of a combination of ionospheric and solar wind ions. These ions and electrons will have easy access to the equatorial magnetosphere via their gradient and curvature drifts following a trajectory described initially by Shabansky [19]. In addition they will form a layer of energetic particles on the magnetopause and as shown by Fritz [7] and Zhou et al. [25]

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Fig. 28.10 ISEE-1 3-D PAD for ions with energy from 24 to 45 keV. The figure spans the time period 12:54:40–13:03:10 UT

Fig. 28.11 ISEE-1 3-D PAD for ions with energy from 142 to 210 keV. The figure spans the time period 12:54:40–13:03:10 UT

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Fig. 28.12 ISEE-1 3-D pitch angle distributions of electron flux (22.5–39.0 keV) as the spacecraft exits the CDC for the final time. The figure spans the time period 12:54:40–13:03:10 UT. Throughout the CDC and prior to the satellite exiting the CDC, the flux shows a clear peak at a PA of 90ı (figure 7 from [21])

they could be the source of the ring current. Due to the size of the CDC cavities and their common occurrence, the role of these energetic particles must be factored into any model that purports to describe the topology and dynamics of the magnetosphere. Acknowledgements I would thank the reviewers of this paper, Drs. Jiasheng Chen, George Siscoe, Hui Zhang and Q.-G. Zong and graduate students Brian Walsh, Kate Whitaker, and Jon Niehof for many useful discussions and to acknowledge the contributions of the various instrument teams for CAMMICE, CEPPAD, and Hydra on Polar and RAPID on Cluster. The Polar effort has been supported at Boston University under a series of NASA grants: NAG5–2578, NAG5–7677, NAG5–11397, and NNG05GD23G. The Cluster effort at Boston University has been supported under another series of NASA grants: NAG5–10108 and NNG05GE90G.

References 1. Asikainen, T. and K. Mursula, Energetic particle fluxes in the exterior cusp and the high latitude dayside magnetosphere: statistical results form the Cluster/RAPID instrument, Ann. Geophys., 23, 2217–2230 (2005). 2. Chen, J., Evidence for particle acceleration in the magnetospheric cusp, Ann. Geophys., 26, 1993–1997 (2008).

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3. Chen, Jiasheng, T. A. Fritz, R. B. Sheldon, H. E. Spence, W. N. Spjeldvik, J. F. Fennell, S. Livi, A new, temporarily confined population in the polar cap during the August 27, 1996 geomagnetic field distortion period, Geophys. Res. Lett., 24 (12), 1447–1450 (1997). 4. Chen, Jiasheng, Theodore A. Fritz, Robert B. Sheldon, Harlan E. Spence, Walther N. Spjeldvik, Joseph F. Fennell, Stefano Livi, Christopher T. Russell, Jolene S. Pickett, and Donald A. Gurnett, Cusp energetic particle events: Implications for a major acceleration region of the magnetosphere, J. Geophys. Res., 103 (No. A1), 69–78 (1998). 5. Dunlop, M. W., B. Lavraud, P. Cargill, M. G. G. T. Taylor, A. Balogh, H. Reme, P. Decreau, K.-H. Glassmeier, R. C. Elphic, J.-M. Bosqued, A. N. Fazakerley, I. Dandouras, C. P. Escoubet, H. Laakso and A. Marchaudon, Cluster Observations of the Cusp: Magnetic Structure and Dynamics, Surveys in Geophysics 26: 1–51, DOI: 10.1007/s10712–005–1871–7 (2005). 6. Finkemeyer, B U, Harris, J J, Fritz, T A, Chen, J, Matthews, D L, A Survey of the Frequency of Occurrence of CEP Events During the First Two Years of POLAR Operations, SM-42A-02 at the 1999 AGU Spring Meeting (1999). 7. Fritz, Theodore A., The Role of the Cusp as a Source for Magnetospheric Particles: A New Paradigm, ESA Special Publication of the Proceedings of the Cluster II Workshop on Multiscale/Multipoint Plasma Measurements held at Imperial College, London 22–24 September 1999, ESA SP-499 (2000). 8. Fritz, T A, Karra, M, Finkemeyer, B, Chen, J, Statistical Studies with Polar of Energetic Particles near the dayside Cusp, SM22B-04 at the 1999 Fall AGU meeting (1999a). 9. Fritz, T.A., J. Chen, R.B. Sheldon, H.B. Spence, J.F. Fennell, S. Livi, C.T. Russell, and J.S. Pickett, Cusp energetic particle events measured by POLAR spacecraft, Phys. Chem. Earth (C), 24, 135–140 (1999b). 10. Fritz, T.A., J. Chen, R.B. Sheldon, The Role of the Cusp as a Source for Magnetospheric Particles: A New Paradigm? Adv. in Space Res., 25, No 7–8, 1445–1457 (2000). 11. Fritz, T. A., J. F. Fennell, S. Livi, J. L. Roeder, A. Daglis, H. Sommer, B. Wilken, B. Kellert, M. Henderson, M. Grande, J. B. Blake, R. Koga, J. Chen, “The Polar CAMMICE Investigation”, available on the following web site: http://www.bu.edu/buspace/papers/ cammice instrument.html 12. Lavraud, B., A. Fedorov, E. Budnik, A. Grigoriev, P. J. Cargill, M. Dunlop, H. Reme, I. Dandouras, and A. Balogh, Cluster survey of the high-altitude cusp properties: A three-year statistical study, Ann. Geophys., 22(8), 3009–3019 (2004). 13. Newell, P. T., C.-I. Meng, D. G. Sibeck, and R. Lepping, Some low-altitude cusp dependencies on the interplanetary magnetic field, J. Geophys. Res., 94, 8921–8927 (1989). 14. Newell, Patrick T., and Ching-I. Meng, Magnetopause dynamics as inferred from plasma observations on low-altitude satellites, Physics of the Magnetopause, AGU Geophysical Monograph 90, 407–416 (1995). 15. Niehof, J. T., T. A. Fritz, R.H.W. Friedel, and J. Chen, Interdependence of magnetic field and plasma pressures in cusp diamagnetic cavities, Geophys. Res. Lett., 35, L11101, doi:10.1029/2008GL033589 (2008). 16. Rae, I. J., F. R. Fenrich, M. Lester, K. A. McWilliams, J. D. Scudder, Solar wind modulation of cusp particle signatures and their associated ionospheric flows, J. Geophys. Res., 109, A03223, doi:10.1029/2003JA010188 (2004). 17. Russell, C.T., Snare, R.C., Means, J.D., Pierce, D., Dearborn, D., Larson, M., Barr, G. and Le, G., The GGS/Polar Magnetic Fields Investigation, Space Sci. Rev., 71 (1/4), also published as The Global Geospace Mission, in C.T. Russell (ed.), 877 pp, Kluwer, Dordrecht, The Netherlands, pp. 563–582 (1995). 18. Russell, C. T., J. A. Fedder, S. P. Slinker, X-W. Zhou, G. Le, J. G. Luhmann, F. R. Fenrich, M. O. Chandler, T. E. Moore and S. A. Fuselier, Entry of the POLAR spacecraft into the polar cusp under northward IMF conditions, Geophys. Res. Lett., 25, 3015–3018 (1998). 19. Shabansky, V. P., Some processes in the magnetosphere, Sp. Sci. Rev., 12, 299–418 (1970). 20. Vogiatzis, I. I., T. E. Sarris, E. T. Sarris, O. Santol´ık, I. Dandouras, P. Robert, T. A. Fritz, Q.-G. Zong, and H. Zhang, Cluster observations of particle acceleration up to supra-thermal energies in the cusp region related to low-frequency wave activity–possible implications for the substorm initiation process, Ann. Geophys., 26, 653–669 (2008).

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21. Walsh, B. M.,T. A. Fritz, N. M. Lender, J. Chen, and K. E. Whitaker, Energetic Particles Observed by ISEE-1 and ISEE-2 in a Cusp Diamagnetic Cavity on September 29, 1978, Ann. Geophys., 25, 2633–2640 (2007). 22. Whitaker, K. E., J. Chen, and T. A. Fritz, CEP populations observed by ISEE 1, Geophys. Res. Lett., 33, L23105, doi:10.1029/2006GL027731 (2006). 23. Whitaker, K.E., T.A. Fritz, J. Chen, and M.M. Klida, Energetic particle sounding of the magnetospheric cusp with ISEE-1, Ann. Geophys., 25, No. 5, p1175–1182 (2007). 24. Zhang, H., Q.-G. Zong, T. A. Fritz, S. Y. Fu, S. Schaefer, K. H. Glassmeier, P. W. Daly, H. Rème, and A. Balogh, Cluster observations of collisionless Hall reconnection at high-latitude magnetopause, J. Geophys. Res., 113, A03204, doi:10.1029/2007JA012769 (2008). 25. Zhou, X.-Z., T. A. Fritz, Q.-G. Zong, Z. Y. Pu, Y.-Q. Hao, and J.-B. Cao, The cusp: a window for particle exchange between the radiation belt and the solar wind, Annales Geophysicae, 24, 3131–3137 (2006).

Chapter 29

Energetic Particles in the Cusp: A Cluster/RAPID View T. Asikainen

Abstract Energetic particles have been persistently observed in the exterior cusp by different satellite missions such as POLAR, Cluster-II, Viking, ISEE etc. Yet the source and the acceleration mechanism of these particles have remained unclear. In this paper I review our studies of energetic particles in the cusp and the nearby high-latitude region of closed magnetospheric field lines (HLPS, high-latitude dayside plasma sheet) using the data obtained by the RAPID instrument onboard the Cluster-II satellites. We conducted a large scale statistical study to examine the dependence of the energetic particle fluxes in the cusp and HLPS on solar wind/IMF conditions as well as on geomagnetic activity. The study showed that energetic ion fluxes in the HLPS correlate strongly with substorm activity and electron fluxes with solar wind speed and geomagnetic activity. In the exterior cusp a clear correlation between lower energy ions (E < 75 keV) and IMF jBy j was found while the more energetic particles in the cusp (E > 75 keV) correlated with substorm activity. Our case studies have shown that when IMF By dominates reconnection can take place near the cusp and release energetic particles from closed field lines to the cusp. Coupled with these detailed observations the statistical results imply that the energetic particles in the HLPS and the cusp originate in the near-Earth magnetotail from where they can drift to the HLPS region. From the HLPS the higher energy particles diffuse more or less directly into the cusp while the lower energy particles are released into the cusp by reconnection. These observations provide a consistent explanation for the cusp energetic particles without a need for significant local acceleration of shocked solar wind plasma to MeV energies. While some energy transfer from the electromagnetic waves to plasma particles is known to occur in the cusp it cannot explain the observations discussed here.

T. Asikainen () Department of Physics Centre of Excellence in Research, P.O. Box 3000, FIN-90014, University of Oulu, Finland e-mail: [email protected]


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29.1 Introduction As the solar wind blows past the Earth and confines the geomagnetic field into the magnetospheric cavity two null points of magnetic field are formed at high latitudes on the dayside magnetopause. The field lines around these points form a funnel, a cusp, that extends all the way from the magnetopause into the ionosphere. The cusps have a central role in the magnetospheric dynamics as most of the solar wind plasma that enters the magnetosphere during dayside magnetospheric reconnection travels through them (e.g., Reiff et al. [14], Wing et al. [22], Onsager and Lockwood [12]). When reconnection occurs on the magnetopause shocked solar wind plasma from the magnetosheath gains access to the cusp and forms a turbulent diamagnetic cavity. Accordingly, the high altitude cusp is typically seen as a region of enhanced plasma density with a fluctuating and depressed magnetic field relative to the surroundings. In the classical model of the magnetosphere, the high-latitude dayside magnetosphere and the adjacent cusp regions cannot trap particles stably [16] because they are swept to the dayside magnetopause by the convection before they can execute a complete drift orbit. Still, a number of studies concerning the high altitude cusp [1, 2, 5, 6, 9, 10, 23, 24] have reported persistent and significant fluxes of energetic particles in this region. Numerical studies based on realistic magnetic field models have also revealed that the high-latitude dayside regions around the cusp can quasistably trap energetic particles whose motion is primarily governed by the magnetic gradient-curvature drift rather than the convection [19]. It has also been shown that the regions around the cusp are connected to the night side magnetotail by so called Shabansky drift orbits [7, 18]. Despite the vast observational evidence of energetic particles in the cusp and related numerical modeling, the origin of these particles has remained controversial. Three different scenarios have been suggested to account for these particles: (1) local acceleration in the cusp [5], (2) inner magnetospheric source and transport from there to the cusp [1], (3) a bow shock source [4]. Chen et al. [5] and Fritz et al. [8] have reported a correlation between the energetic ion fluxes in the cusp and the power of the magnetic fluctuations in the cusp diamagnetic cavity. Based on this and other suggestive observations they have argued that the energetic particles are accelerated locally in the cusp by electromagnetic waves. Chang et al. [4] and Trattner et al. [20] have argued that the lower energy particles in the cusp may be accelerated at the quasi-parallel bow shock, entering from there into the cusp along field lines connecting the two regions. They also speculate that higher energy particles observed in the cusp may diffuse there from within the magnetosphere. Kremser et al. [10] studied the low-altitude cusp and showed that ions with energy above about 50 keV in the cusp are of magnetospheric origin while a separate lower energy ion population in the cusp (E < 15 keV) is of magnetosheath origin. Nearly all the work done on the energetic particles in the cusp has been concentrated purely on the particles observed within the cusp itself while much less attention have been given to the surrounding closed field line regions of the

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magnetosphere which can efficiently trap energetic particles. In our work we have studied the energetic particle fluxes in the cusp and also on the adjacent closed field line region equatorward of the cusp (which we call the high-latitude dayside plasma sheet or HLPS) as well as possible particle transport between these regions. In this paper I review our work on the subject and present statistical and detailed evidence for magnetospheric origin of energetic particles in the cusp.

29.2 Instrumentation Much of the work on cusp energetic particles dates to the era of POLAR satellite (launched in February 1996) whose orbit was ideal for such studies. To provide an alternate view of the same region we have used the Cluster-II satellites whose orbital configuration allows the study of high-latitude dayside regions like the cusp, magnetopause and the high-latitude dayside plasma sheet during the northern hemisphere vernal equinox (January to May season). Each Cluster spacecraft includes a versatile set of instruments for measuring electromagnetic fields at different frequencies and charged particles at different energies. In this work we have utilized magnetic field data from the FGM instrument [3] and particle data from the CIS plasma instrument which measures low energy ion species from spacecraft potential up to 40 keV/q [15]. However, our most important source of energetic particle data is the RAPID instrument which measures electrons from 20 to 400 keV and ions (protons, helium ions and CNO group ions) at the energy range 28–1,500 keV for protons, 138–1,500 keV for He ions and 90–1,500 keV for CNO-group ions. The RAPID is capable of measuring the full 3D distribution of electrons at spacecraft spin resolution (4 s) and the 3D distribution of ions at 32 spin resolution (128 s). However, the corruption of the central ion detector heads has rendered the 3D ion distributions almost useless. A detailed description of the RAPID instrument is given by Wilken et al. [21] and an updated description of RAPID instrument and all the other Cluster instruments is available at the Cluster Active Archive website (http://caa.estec.esa.int/caa/instr doc.xml).

29.3 The High-Latitude Dayside Regions During vernal equinoxes the apogee of the Cluster orbit is at about 19.6 RE at the dayside, i.e., well outside the magnetosphere in the solar wind. On such an orbit the satellites traverse from the nightside ring current over the auroral regions and the polar cap into the high latitude dayside regions. Depending on the solar wind conditions (dynamic pressure, IMF etc.) and the geodipole tilt angle, which affect the orientation of the whole dayside magnetosphere relative to the Cluster orbit, the satellites can enter different regions on the dayside magnetosphere.

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Fig. 29.1 Cluster-1 data from 17 February 2003. Panels from top to bottom are magnetic field intensity (FGM), plasma flow velocity (CIS), low energy ion spectrum (CIS/CODIF), energetic proton spectrum (RAPID) and energetic electron spectrum (RAPID)

Figure 29.1 shows a collection of data from Cluster 1 during a typical Cluster dayside pass on 17 February 2003. The panels from top to bottom depict magnetic field intensity, plasma flow velocity, low energy proton spectrum (CIS), high energy proton spectrum (RAPID) and electron spectrum (RAPID). At the beginning of the depicted time interval the satellite was flying in the northern tail lobe over the polar cap towards the dayside. At about 03:00 UT the plasma density and energetic particle fluxes were greatly enhanced indicating a mixture of magnetospheric and magnetosheath plasma. By 04:00 UT the satellite had moved into a region where only magnetospheric energetic particles were present, the plasma density was low and the plasma flow velocity was small. At the same time the magnetic field intensity behaved rather smoothly without any high frequency fluctuations or turbulence. This region, which is equatorward of the cusp funnel and inside the magnetopause with high fluxes of energetic particles, is the high-latitude dayside plasma sheet, HLPS, or the high latitude trapping region. In the HLPS significant energetic particle fluxes are persistently present as will be discussed later on. At about 07:10 UT the satellite crossed the dayside magnetopause into the magnetosheath, which is seen as an abrupt change in all the depicted parameters. Most notably the magnetic field intensity dropped and became very turbulent, the flow velocity increased to a steady level, plasma density increased and energetic particles all but disappeared (except for the few enhancements mostly seen in energetic protons). The satellites do not observe the HLPS region on every orbit. If the orientation of the dayside magnetosphere relative to the Cluster orbit is suitable the satellites

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may enter the exterior cusp. A collection of data from such an orbit is shown in Fig. 29.2. Again the panels from top to bottom depict magnetic field intensity, plasma flow velocity, low energy proton spectrum (CIS), high energy proton spectrum (RAPID) and electron spectrum (RAPID). At the beginning of the depicted time interval the satellite flied over the polar cap in the northern tail lobe and began to see plasma of increasing density as it approached the high-latitude magnetopause. After about 22:00 UT the satellite observed a region of decreased and highly fluctuating magnetic field with increased plasma density and small and turbulent plasma flow velocity. This is the cusp diamagnetic cavity. High fluxes of energetic particles (both electrons and ions) were present in the cusp as can be seen from the RAPID electron and ion spectra in Fig. 29.2. Such elevated fluxes of energetic particles are seen nearly every time the satellite observes the cusp although the flux level depends on a variety of things as will be discussed later. The satellite left the cusp around 23:00 UT skimming the dayside magnetopause and entering the magnetosheath. As the satellite exited the cusp it observed a number of sharp fluctuations in the magnetic field intensity and associated strong peaks in energetic particle fluxes from about 22:50 to 23:30 UT. Such signatures are not a feature particular to this orbit alone but are actually observed often as the satellite exits the cusp and the IMF By component dominates (like in the event under discussion). The two types of orbits discussed above are the most typical ones during vernal equinoxes. As mentioned above, whether the satellites observe the cusp or the HLPS mainly depends on the orientation of the whole dayside magnetosphere relative to the Cluster orbit. It is well known that the dipole tilt angle affects the cusp position greatly. The greater the dipole tilt angle the more equatorward the cusp is. In addition it has been shown that the cusp position is affected by IMF direction [11, 13, 17] being generally more equatorward during negative IMF Bz . It is thus expected that Cluster sees the HLPS region more preferentially when the dipole is tilted away from the Sun and the IMF is northward, while the cusp would preferentially be observed when the dipole is tilted towards the Sun and the IMF being southward. However, also the inclination of the Cluster orbit has an effect. In seven years since the launch of Cluster-II late in 2000 the inclination of the orbit has decayed from the initial 0ı to more than 30ı below the ecliptic. The orbital decay has led to the fact that the northern cusp is now rarely seen by the Clusters while in the beginning of the mission the northern cusp was seen more often. The southern cusp in contrast is now seen more often than at the beginning of the mission.

29.4 Reconnection Near the Cusp Asikainen and Mursula [2] studied the event shown in Fig. 29.2 in detail and showed that the sharp fluctuations in the magnetic field and associated energetic particle peaks seen at the cusp edge were associated with reconnection near the cusp. Figure 29.3 shows a close-up of the time interval from 22:50 to 23:30 UT from Cluster 4 satellite. The panels from top to bottom depict the magnetic field components

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Fig. 29.2 Cluster-1 data from 2–3 February 2003. Panels from top to bottom are magnetic field intensity (FGM), plasma flow velocity (CIS), low energy ion spectrum (CIS/CODIF), energetic proton spectrum (RAPID) and energetic electron spectrum (RAPID)

in a boundary normal (LMN) coordinate system, energetic proton spectrum and energetic electron spectrum. One can see that each energetic particle enhancement occurs during a bi-polar variation in the magnetic field normal component which is a well known signature of transient reconnection at the magnetopause or a flux transfer event (FTE). In an FTE a reconnected flux tube moves along the magnetopause across the spacecraft giving rise to the bi-polar signature in the magnetic field normal component. During the time interval in Fig. 29.3 the IMF was rather steady with By D 10 nT and Bz D 3 nT. During such an IMF one expects the antiparallel reconnection to occur near the dusk edge of the cusp funnel. Asikainen and Mursula [2] showed indeed that the observations are consistent with such a reconnection and that the energetic particles observed during the FTEs were particles released from the magnetospheric closed field lines. The particles were streaming antiparallel to the reconnected flux tube towards the cusp. This work showed that reconnection near the cusp can release particles from the closed field lines of HLPS and some of these particles have access into the cusp. As mentioned, such reconnection events and similar (e.g., Zong et al. [25]) are often observed near the cusp magnetopause when IMF By dominates suggesting that energetic particle fluxes in the cusp might be dependent on IMF direction.

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Fig. 29.3 Close-up of flux transfer events observed by Cluster-4 at 2 February 2003 22:50–23:30. Panels from top to bottom show magnetic field components in boundary normal coordinate system (BN is the normal component), energetic electron spectrum (RAPID) and energetic proton spectrum (RAPID)

29.5 Statistics of Energetic Particles in the HLPS and the Cusp In order to understand the origin of the energetic particles in the cusp we have to study the energetic particle fluxes in the adjacent HLPS also. To this end, we performed an extensive statistical analysis of energetic particles in the HLSP and the cusp which was presented in Asikainen and Mursula [1]. Since then we have revised and extended our database to cover the January–April in 2002 and 2003. For this study on each Cluster orbit in this time range we identified the HLPS (22 observations) and cusp (26 observations) regions. We calculated average energetic proton and electron fluxes measured by the RAPID at different energy channels. In addition we calculated the simultaneous average solar wind and IMF parameters as well as Kp and AE indices. For solar wind and IMF we used the high resolution (1 min) OMNI data from OMNIWeb (see http://omniweb.gsfc.nasa.gov/) in which the data have been time shifted to the bow shock nose (for the details of the time shifting procedure please refer to the OMNIWeb website). Assuming a connection between

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the near-Earth tail and the high-latitude dayside we have to take into account the propagation time of energetic particles from the tail into the dayside. For 10s to 100s of keV particles the drift time was estimated to be at most 3 h. When we calculated the AE index averages we took the average from up to 3 h before the Cluster observation time to account for the particle drift. We found a good correlation between the energetic ion fluxes and AE/Kp indices in the HLPS at all energy channels. The correlation coefficients between ion fluxes and AE and Kp indices were between 0.52 and 0.75 at all energy channels and they were all statistically significant. Electron fluxes in the HLPS were found to correlate with solar wind speed with correlation coefficients at different energy channels ranging from 0.51 to 0.6. The electron fluxes also correlated with the magnitude of IMF By component (i.e., IMF jBy j). The correlation coefficients with IMF jBy j ranged from 0.55 to 0.6, thus the electron fluxes tend to be higher in the HLPS when IMF jBy j is small. These correlations suggest that the energetic particles observed in the HLPS adjacent to the cusp come from the inner magnetosphere and/or near-Earth magnetotail where they are accelerated by substorms (thus the ion flux-AE correlation) or processes responsible for the acceleration of radiation belt electrons (thus the electron flux-solar wind speed correlation). The transport of energetic particles especially during substorms from the near-Earth magnetotail to the HLPS/cusp has been shown possible by Delcourt and Sauvaud [7]. The negative correlation between IMF jBy j and the electron fluxes may be understood in terms of reconnection. When By dominates the reconnection has been observed to occur near the cusp edges, i.e., at the closed HLPS field lines (see the discussion in the previous section). At these times electrons which are faster than ions and bound to the field lines more tightly than ions escape along the opened field lines more readily than ions. Turning on to the cusp we found significant differences in the behavior of energetic particle fluxes compared to the HLPS region. We found that ion fluxes in the cusp correlate mainly with IMF jBy j and AE index and that the correlation depends strongly on ion energy. Figure 29.4 shows the partial correlation coefficients between energetic ion flux and log(AE) and IMF jBy j. Because partial correlation measures linear correlation we calculated the coefficient for log(AE) which displays better linear relation with ion flux than just AE. One can see that at lower energies the fluxes correlate more with IMF jBy j and at higher energies more with AE index. The crossover takes place at the second energy channel which corresponds to about 75 keV. These relationships show that the reconnection near the cusp when By dominates has a strong and statistically significant role in the release of energetic ions into the cusp from closed field lines. It seems that reconnection is the dominant factor for ions below 75 keV. At higher energies the fluxes depend more on the AE index which suggests that ions above 75 keV can more or less directly diffuse into the cusp from closed field lines. Furthermore, transport of energetic particles with 100s of keV energy from the near-Earth tail to the high-latitude dayside regions has been shown to be enhanced during substorms [7]. Energetic electrons in the cusp behave totally differently from the ions. They show correlation only with IMF Bz and the correlation coefficients are in the range

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Fig. 29.4 Partial correlation coefficients between energetic ion flux in the cusp and log(AE) index and IMF jBy j as a function of ion energy

0.51 to 0.65 at all energy channels. Thus the electron fluxes are higher in the cusp when IMF is northward. The electrons in the cusp do not show statistically significant dependence on AE or Kp indices or solar wind speed (as was observed in the HLPS region). To understand the correlation with IMF Bz let’s consider the cusp geometry during northward and southward IMF. During northward IMF the reconnection preferentially occurs poleward of the cusp producing a more closed field line topology than during southward IMF when subsolar reconnection opens the cusp field lines. At 10s to 100s of keV energy electrons are relativistic and in an open field line topology they are lost within seconds. A more closed field line topology is expected to trap them for a longer time and more efficiently. Thus regardless of the strength of the source producing the electrons, their fluxes in the cusp are mainly determined by how efficiently they can be confined there, i.e., how closed the cusp field line topology is. To reveal a possible dependence of the electron fluxes on a source process inside the magnetosphere we separated from the data those events where IMF was northward. Figure 29.5 shows the lowest energy channel electron flux (energy about 40 keV) with respect to AE index. One can see that taking all the observations (left hand side of Fig. 29.5) there is no correlation. However, taking only events with northward IMF (right hand side of Fig. 29.5) when the cusp electron trapping is expected to be more efficient, a weak but statistically significant correlation of 0.41 between the electron fluxes and AE index is revealed.

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Correlation coefficient 0.41

103 electron flux. [1/cm2 s sr keV]

electron flux. [1/cm2 s sr keV]

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Fig. 29.5 Relationship between energetic electron flux (energy approx. 40 keV) in the cusp and AE index. Left hand side: All events included, right hand side: only events with northward IMF included

This suggests that also electrons in the cusp come from within the magnetosphere and are transported into the cusp from the near-Earth magnetotail especially during substorms.

29.6 Conclusions The results reviewed above suggest that the origin of energetic particles in the high-latitude dayside regions, both the HLPS and the cusp is in the near-Earth magnetotail. During substorms the transport of energetic particles from the tail is enhanced and this is reflected in the positive correlation between the energetic ion fluxes and AE index in the HLPS and the cusp. Detailed case studies and large scale statistics showed that two mechanisms operate in transporting energetic particles into the cusp: release by reconnection from the adjacent closed field lines and direct diffusion. For ions below 75 keV energy release by reconnection seems to dominate and for more energetic ions direct diffusion dominates. Electrons in the cusp are also transported there from within the magnetosphere but their flux is mostly determined by cusp magnetic field topology, i.e., whether cusp field lines are open (southward IMF) or closed (northward IMF). Electron fluxes are higher when the cusp field lines are closed. These observations provide a consistent explanation for the cusp energetic particles without a need for significant local acceleration of shocked solar wind plasma to MeV energies. While some energy transfer from the electromagnetic waves and turbulence does occur in the cusp it cannot explain the observations presented here.

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Acknowledgements The author would like to thank K. Mursula for fruitful co-operation and P. Daly for useful discussions regarding the RAPID instrument. The Cluster Active Archive, FGM, CIS and RAPID PI-groups are greatly acknowledged for providing high quality data used in this paper.

References 1. Asikainen, T., Mursula, K.: Energetic particle fluxes in the exterior cusp and the high-latitude dayside magnetosphere: Statistical results from the Cluster/RAPID instrument, Annales Geophysicae, 23, 2217–2230 (2005) 2. Asikainen, T., Mursula, K.: Reconnection and energetic particles at the edge of the exterior cusp, Annales Geophysicae, 24, 1949–1956 (2006) 3. Balogh, A., Dunlop, M. W., Cowley, S. W. H., Southwood, D. J., Thomlinson, J. G., et al.: The Cluster Magnetic Field Investigation, Space Science Reviews, 79, 65–91 (1997) 4. Chang, S.-W., Scudder, J. D., Fuselier, S. A., Fennell, J. F., Trattner, K. J., Pickett, J. S., Spence, H. E., Menietti, J. D., Peterson, W. K., Lepping, R. P., Friedel, R.: Cusp energetic ions: A bow shock source, Geophys. Res. Lett., 25, 3729–3732 (1998) 5. Chen, J., Fritz, T. A., Sheldon, R. B., Spence, H. E., Spjeldvik, W. N., Fennell, J. F., Livi, S., Russell, C. T., Pickett, J. S., Gurnett, D. A.: Cusp energetic particle events: Implications for a major acceleration region of the magnetosphere, J. Geophys. Res., 103, 69–78 (1998) 6. Chen, J., Fritz, T. A., Sheldon, R., Pickett, J., Russell, C.: The discovery of a new acceleration and possible trapping region of the magnetosphere, Adv. Space Res., 27, 1417–1422 (2001) 7. Delcourt, D., Sauvaud, J.-A.: Populating of Cusp and Boundary Layers by energetic (hudreds of keV) equatorial particles, J. Geophys. Res., 104, 22 635–22 648 (1999) 8. Fritz, T. A., Chen, J., Sheldon, R., Spence, H., Fennell, J., Livi, S., Russell, C., Pickett, J.: Cusp Energetic Particle Events Measured by POLAR Spacecraft, Phys. Chem. Earth, 24, 135–140 (1999) 9. Fritz, T. A., Chen, J., Siscoe, G.: Energetic ions, large diamagnetic cavities and ChapmanFerraro cusp, J. Geophys. Res., 108, 1028, (2003) 10. Kremser, G., Woch, J., Mursula, K., Tanskanen, P., Wilken, B., Lundin, R.: Origin of energetic ions in the polar cusp inferred from ion composition measurements by the Viking satellite, Ann. Geophys., 13, 595–607 (1995) 11. Meng, C.-I., Case studies of the storm time variation of the polar cusp, J. Geophys. Res., 88, 137 (1983) 12. Onsager, T. G., and Lockwood, M.: High-latitude particle precipitation and its relationship to magnetospheric source regions, Space Sci. Rev., 80, 77–107 (1997) 13. Palmroth, M., Laakso, H., Pulkkinen, T., Location of high-altitude cusp during steady solar wind conditions, J. Geophys. Res., 106, 21109–21122 (2001) 14. Reiff, P. H., Hill, T. W., Burch, J. L.: Solar wind plasma injection at the dayside magnetospheric cusp, J. Geophys. Res., 82, 479–491 (1977) 15. Rème, H., Bosqued, J. M., Sauvaud, J. A., Cros, A., Dandouras, J., Aoustin, C., et al.: The Cluster Ion Spectrometry (CIS) Experiment, Space Sci. Rev., 79, 303–350 (1997) 16. Roederer, J. G., Dynamics of geomagnetically trapped radiation, Springer-Verlag Berlin Heidelberg New York, pp. 66 (1970) 17. Russell, C., POLAR eyes the cusp. In R. Harris (Ed.), Proceedings of the Cluster-II Workshop: Multi-scale/Multipoint Plasma Measurements, ESA SP-44, vol. 90, pp. 47–55, European Space Agency, Noordwijk, 2000 18. Shabansky, V. P.: Some processes in the magnetosphere, Space Sci. Rev., 12, 299–418 (1971) 19. Sheldon, R., Spence, H., Sullivan, J., Fritz, T. A., Chen, J.: The discovery of trapped energetic electrons in the outer cusp, Geophys. Res. Lett., 25, 1825–1828 (1998) 20. Trattner, K., Fuselier, S., Peterson, W., Chang, S.-W., Friedel, R., Aellig, M.: Origins of energetic ions in the cusp, J. Geophys. Res., 106, 5967–5976 (2001)

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21. Wilken, B., Axford, W. I., Daglis, I., Daly, P., Guttler, W., Ip, W. H., Korth, A., et al.: RAPID: The Imaging Energetic Particle Spectrometer on Cluster, Space Science Reviews, 79, 399–473 (1997) 22. Wing, S., Newell, P. T., Onsager, T. G.: Modeling the entry of magnetosheath electrons into the dayside ionosphere, J. Geophys. Res., 101, 13155–13167, (1996) 23. Zhang, H., Fritz, T. A., Zong, Q.-G., Daly, P. W.: Stagnant exterior cusp region as viewed by energetic electrons and ions: A statistical study using Cluster Research with Adaptive Particle Imaging Detectors (RAPID) data, J. Geophys. Res., 110, A05211, doi:10.1029/ 2004JA010562, (2005) 24. Zong, Q.-G., Fritz, T. A., Korth, A., et al.: Energetic electrons as a field line topology tracer in the high latitude boundary/cusp region: Cluster RAPID observations, Surveys in Geophysics, 26, 215–240, (2005a) 25. Zong, Q.-G., Fritz, T. A., Spence, H., Zhang, H., Huang, Z. Y., Pu, Z. Y., Glassmeier, K.-H., Korth, A., Daly, P. W., Balogh, A., Rème, H.: Plasmoid in the high latitude boundary/cusp region observed by Cluster, Geophys. Res. Lett., 32, doi:10.1029/2004GL020960, (2005b)

Part VII

Observations of Magnetospheric Tail

Chapter 30

Plasma Flow Reversals in the Magnetotail and Their Implications on Substorm Models A.T.Y. Lui

Abstract Intervals of plasma flow reversals in the magnetotail are considered as times when the observing satellite encounters the process responsible for substorm disturbances. We consider the expected signatures during plasma flow reversals to evaluate the validity of two prevalent substorm models.

30.1 Introduction Magnetospheric substorms represent an explosive energy release phenomenon in space plasmas that can be investigated with in situ and remote sensing measurements. This unique property of magnetospheric substorms thus constitutes a window for exploration on explosive energy release phenomena in the plasma universe that cannot be studied with in situ measurements. At present, there are two prevalent substorm models, namely the near-Earth initiation (NEI) model with the substorm process located in the downstream distance of 6–15 RE and the mid-tail initiation (MTI) model with the substorm process located in the downstream distance beyond 15 RE [6]. These two models predict different substorm disturbances in the plasma sheet, in particular, around the site of plasma flow reversal of significant speeds above the ‘noise level’ of flow measurements. In this paper, we shall examine what different plasma behavior is expected around plasma flow reversals from these two models to guide us in evaluating the validity of these models.

30.2 Features Around Plasma Flow Reversal for MTI Model In the MTI model, plasma flow reversal arises from an X-line moving tailward [4]. Flow reversal implies the encounter of the X-line during its tailward motion. Figure 30.1 depicts the essential features of the model and the associated X-line A.T.Y. Lui () The Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20723, USA e-mail: [email protected] H. Laakso et al. (eds.), The Cluster Active Archive, Astrophysics and Space Science Proceedings, DOI 10.1007/978-90-481-3499-1 30, c Springer Science+Business Media B.V. 2010

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reconnection. There is a quadruple magnetic perturbation perpendicular to the plane of magnetic reconnection, i.e., tailward of the X-line, Bx By < 0 in both north and south of the neutral sheet, while similarly earthward of an X-line, Bx By > 0. If plasma flow reversal were due to tailward motion of an X-line, then one would expect the product Bx By < 0 before flow reversal and Bx By > 0 after the passage of the X-line. The plasma flow pattern is well organized by the magnetic field configuration. Tailward of the X-line, the Lorentz force has a component pointing tailward, thus accelerating plasma tailward. This component of the Lorentz force changes sign at the X-line location. Therefore, plasma flow reversal should be accompanied by the x-component of the Lorentz force changing its sign. Plasma flow reversal due to

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tailward motion of an X-line would predict the x-component of the Lorentz force changing sign simultaneous with the flow reversal. Magnetic reconnection requires dissipation, which is assumed to take place around an X-line. One therefore would expect to find the y-component of the dot product between current density and electric field jy Ey to be positive in the region. The y-component of this dot product is expected to be the largest in comparison with the other components since the current density and the electric field have the largest component in this direction normally.

30.3 Features Around Plasma Flow Reversal for NEI Model In the near-Earth initiation model, current disruption is a turbulent phenomenon and causes reduction of the cross-tail current in the magnetotail. Current disruption also reduces the magnetic field normal to the current sheet, i.e. the Bz component, at tailward and azimuthally adjacent locations [9]. This magnetic field reduction causes thinning of the current sheet, instigating further development of the physical process for current disruption. The tailward motion of current disruption initiated in the near-Earth region arises from progressive tailward thinning of the plasma sheet, possibly by the launching of rarefaction waves downstream. Plasma flow reversal during substorms corresponds to the passage of this region of multiple current disruption sites to further downstream in the magnetotail. The current disruption region is highly turbulent, with highly variable magnetic field especially near the neutral sheet, as illustrated in Fig. 30.2. The magnetic field fluctuations reveal multiscale phenomena up to the ion cyclotron frequency [3, 8]. No clear quadruple magnetic perturbation is anticipated in association with this region. However, there is a Hall current system earthward of the current disruption region. This arises from the fact that ions are unmagnetized while electrons are still magnetized and follow the collapsing field line motion in dipolarization. Consequently, electrons move Earthward with the dipolarizing magnetic field lines while the unmagnetized ions cannot follow the electron motion completely, giving rise to a Hall current system and a dynamo in the magnetotail [7]. In contrast to magnetic reconnection, the plasma flow is not organized by the magnetic field. The Lorentz force is highly dependent on changes of current density and magnetic field locally as well as its vicinity. Therefore, the x-component of the Lorentz force does not necessarily change direction with the passage of the current disruption region. Based on the particle simulation of the cross-field current instability in Lui [6], the turbulence associated with current disruption shows highly fluctuating current density with occasional reversal in its direction, so is the electric field along the current direction. Overall, the turbulence region is generally a dissipative region, i.e., jy Ey > 0, although it exhibits occasional dynamo behavior, i.e., jy Ey < 0, as well.

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30.4 Comparison of Observations with Model Predictions One notable work using the above characteristics to evaluate the two substorm models was reported by Lui et al. [11]. They investigated the possible signatures expected from these models around a plasma flow reversal event (from Vx < –800 km=s to Vx > 800 km=s) observed by Cluster satellites during a substorm on 22 August 2001. They found (1) no clear quadruple magnetic perturbation associated with this flow reversal, (2) the x-component of the Lorentz force does not reverse simultaneously with flow reversal, (3) the presence of episodic dynamo effect, i.e., jy Ey < 0, in the general region of flow reversal, and (4) the expected sequence of flow reversal among the Cluster satellites to be consistent with multiple tailward moving plasma flow sources and not with a single tailward moving plasma flow source. These features are all consistent with the NEI model and not with the MTI model. However, this is only one example and the general applicability of this result needs to be examined with statistical study of such plasma flow reversal events.

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30.5 Summary and Discussion This paper discusses the various features that one may use on observations of plasma flow reversals to evaluate the two prevalent substorm models. Since both current disruption and magnetic reconnection sites are known to be very localized, the choice of plasma flow reversal observations eliminates the possible argument that negative results of a model prediction are due to the observing site not being at the location where these localized phenomena occur. Recently, observations of highly variable magnetic field components, especially the Bz component, accompanied by tailward plasma flow are interpreted as undeniable evidence of magnetic reconnection (e.g., Sergeev et al., [14]). However, this interpretation ignores the fact that current disruption can produce tailward plasma flow and highly fluctuating magnetic field as well. Lui et al. [10] have provided a criterion to determine the direction of plasma acceleration due to the force imbalance resulting from current disruption. Furthermore, a crude agreement of the quadruple magnetic perturbation in the current disruption region can result from the mere fact that electrons, being lighter than ions, can leave the current disruption region faster than the ions, producing a crude trend of the quadruple magnetic perturbation similar to the magnetic reconnection region but in addition superposed by large deviations from this trend. It should be noted that almost all simulations of magnetic reconnection, especially those two-dimensional ones, produce very laminar magnetic field configuration, nothing resembling the high magnetic fluctuations seen in current disruption events. In terms of physical process for the two substorm models, tearing instability is presumed to be the agent for the MTI model to create the magnetic field geometry. However, the viability of tearing instability onset is still an open question. Although there are recent efforts to enable its onset [15, 17], the proposed current sheet features required to initiate the instability have not been verified observationally at the presumed magnetic reconnection site in the magnetotail. Assuming the existence of magnetic reconnection without addressing how it occurs is highly unsatisfactory in understanding the substorm onset process. For the NEI model, there are many potential candidates for the onset process, which include the various forms of ballooning instability, magnetosphere-ionosphere coupling, cross-field current instability, entropy anti-diffusion instability, current-driven Alfvénic instability, convection reduction, and “akis” structure in a thin current sheet. There are some efforts already attempting to identify precisely the onset process from observations [1, 2, 5, 12, 13, 16]. Acknowledgements This work was supported by the NASA grant NNX07AQ50G.

References 1. Chen, L-J, Bhattacharjee A, Sigsbee K, Parks G, Fillingim M, Lin R (2003) Wind observations pertaining to current disruption and ballooning instability during substorms, Geophys. Res. Lett., 30, 68–1, doi 10.1029/2002GL016317.

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2. Cheng, C Z and Lui A T Y (1998) Kinetic ballooning instability for substorm onset and current disruption observed by AMPTE/CCE, Geophys. Res. Lett., 25, 4091–4094. 3. Consolini, G, Kretzschmar M, Lui A T Y, Zimbardo G, Macek W M (2005) On the magnetic field fluctuations during magnetospheric tail current disruption: A statistical approach, J. Geophys. Res., 110, A07202, doi:10.1029/2004JA010947. 4. Hones, E. W., Jr. (1979), Transient phenomena in the magnetotail and their relation to substorms, Space Sci. Rev., 23, 393–410. 5. Lui, A T Y (1996) Current disruption in the Earth’s magnetosphere: Observations and models, J. Geophys. Res., 101, 13067–13088. 6. Lui, A. T. Y. (2001), Current controversies in magnetospheric physics, Rev. of Geophys., 39 (4), 535–564. 7. Lui, A T Y and Kamide Y (2003) A fresh perspective of the substorm current system and its dynamo, Geophys. Res. Lett., 30 (18), 1958, doi:10.1029/2003GL017835. 8. Lui, A T Y and Najmi A-H (1997) Time-frequency decomposition of signals in a current disruption event, Geophys. Res. Lett., 24, 3157–3160. 9. Lui, A T Y, Chang C-L, Mankofsky A, Wong H-K, and Winske D (1991) A cross-field current instability for substorm expansions, J. Geophys. Res., 96, 11389–11401. 10. Lui, A T Y, Yoon P H, and Chang C-L (1993) Quasi-linear analysis of ion Weibel instability, J. Geophys. Res., 98, 153–163. 11. Lui, A T Y, Zheng Y, Zhang Y, Rème H, Dunlop M W, Gustafsson G, Mende S B, Mouikis C, and Kistler L M (2006) Cluster observation of plasma flow reversal in the magnetotail during a substorm, Ann. Geophys., 24, 2005–2013. 12. Roux, A, Perraut S, Robert P, Morane A, Pedersen A, Korth A, Kremser G, Aparicio B, Rodgers D, Pellinen R (1991) Plasma sheet instability related to the westward traveling surge, J. Geophys. Res., 96, 17697–17714. 13. Saito, M H, Miyashita Y, Fujimoto M, Shinohara I, Saito Y, and Mukai T (2008) Ballooning mode waves prior to substorm-associated dipolarizations: Geotail observations, Geophys. Res. Lett., 35, L07103, doi:10.1029/2008GL033269. 14. Sergeev, V, Semenov V, Kubyshkina M, Ivanova V, Baumjohann W, Nakamura R, Penz T, Runov A, Zhang T L, Glassmeier K-H, Angelopoulos V, Frey H, Sauvaud J-A, Daly P, Cao J B, Singer H, and Lucek E (2007) Observation of repeated intense near-Earth reconnection on closed field lines with Cluster, Double Star, and other spacecraft, Geophys. Res. Lett., 34, L02103, doi:10.1029/2006GL028452. 15. Sitnov, M I, Malova H V, and Lui A T Y (1997) Quasineutral sheet filamentation instability induced by electron preferential acceleration from stochasticity, J. Geophys. Res., 102, 163–173. 16. Voronkov, I, Rankin R, Frycz P, Tikhonchuk V T, and Samson J C (1997) Coupling of shear flow and pressure gradient instabilities, J. Geophys. Res., 102, 9639–9650. 17. Zelenyi, L, Artemiev, A, Malova H, and Popov V (2008) Marginal stability of thin current sheets in the Earth’s magneotail, J. Atmos. Solar-Terr. Phys., 70, 325–333.

Chapter 31

Spatial and Temporal Structures in the Vicinity of the Earth’s Tail Magnetic Separatrix Cluster Observations E.E. Grigorenko, L.M. Zelenyi, M.S. Dolgonosov, and J.-A. Sauvaud

Abstract The processes of non-adiabatic particle acceleration occurring in the vicinity of magnetic neutral lines produce highly accelerated (up to 2,500 km/s) field-aligned ion beams. Ion beams are usually observed in the Plasma Sheet Boundary Layer (PSBL) i.e. in the vicinity of magnetic separatrix between open and closed magnetic field lines. These acceleration processes have different spatial and temporal scales depending on the topology of the magnetic field and local plasma conditions in the Current Sheet (CS) and their peculiarities produce distinct manifestations in various characteristics of accelerated PSBL ion structures. Multipoint Cluster observations have led to a new understanding of these phenomena since they give an opportunity to separate spatial and temporal effects in registration of accelerated plasma structures. Our observations in the PSBL of the Earth’s magnetotail revealed two different types of ion beam populations. The first type represents energy collimated ion beams having a duration of several minutes and energies < 20 keV. Along with such ion beams isotropic electron distributions are observed. Multipoint observations of such type of beams revealed that they represent long-living plasma filaments. We suggest that such ion beams were accelerated by the quasi-steady dawn-dusk electric field in a number of spatially localized regions in the CS located in wide vicinity earthward from the distant X -line. Electron observations confirm that these phenomena occur in a region with closed magnetic field geometry. The simultaneous operation of, at least, two resonant sources is evident from the observation in PSBL of intersection of two ion beams with very different parallel velocities. Another type of distributions represents powerful (with energies up to 10s of keV) ion beams having velocity distributions wide in parallel energies. They are observed along with the anisotropic electron velocity distributions forming by counterstreaming electron beams. This feature is peculiar for the magnetic separatrix and indicates that the spacecraft crossed yet open or recently closed magnetic field

E.E. Grigorenko (), L.M. Zelenyi, and M.S. Dolgonosov Space Research Institute of RAS, Moscow, Profsoyuznaya str, 84/32, Russia e-mail: [email protected]; [email protected] J.-A. Sauvaud Centre d’Etudie Spatial des Rayonnements, Toulouse cedex4, France


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lines. Such ion beams may be produced by spatially extended “merged” acceleration source which is formed due to the overlapping of initially spatially separated resonances near X-line.

31.1 Introduction The manifestations of powerful acceleration processes occurred in the Current Sheet (CS) of the Earth magnetotail are often observed in Plasma Sheet Boundary Layer (PSBL) as field-aligned ion beams streaming from the source with high velocities ( 1;000 km=s). It is widely believed that PSBL ion beams are non-adiabatically accelerated in the CS in the region where ion motion already cannot be described by the guiding center approximation and experiences a chaotic character. This phenomenon has been addressed in many theoretical papers which considered ion beam acceleration by the dawn–dusk electric field either near the quasi-stationary distant X -line [8, 13, 21, 23] or in the regions where the normal component of the magnetic field, BZ , has a finite constant or slowly varying positive value [4, 12, 27]. In the last case, it was suggested that the magnetotail has a “stretched” magnetic configuration with the X -line located in its distant part (at jX j 100 RE ) so a wide region of finite positive BZ may exist in the distant CS earthward from the X -line. In such case, ion acceleration takes place in the region with closed magnetic field lines. Later, the resonant nature of the non-adiabatic ion interaction with the CS has been revealed q [1, 5]. Particle motion depends on the so-called parameter of

adiabaticity æD R0 introduced by Buchner and Zelenyi [4] (where R is the radius of curvature of the magnetic field line crossing the CS and 0 is the maximum value of particle’s Larmor radius). If æ 1:0 ion motion consists of fast oscillations across the neutral plane (along Z) and of slow gyration in Bn(X ) field in (XY) plane. Particle motion can be described by the action invariant over the fast variH able IZ D 1=2 zPdz. When a particle crosses the CS plane (Z D 0) the value of IZ experiences stochastic jumps and IZ D 3=2 æ.X / ln j2 sin j, (where is the phase of fast component of particle motion) and IZ has very sensitive dependence on . Since each particle intersects the CS plane twice: at the entry to and at the exit from the CS, the IZ experiences two jumps during each CS crossing. If the phase gain between entry to and exit from the CS becomes equal N (where N is an arbitrary integer number called the resonance number), the remarkable effect happens: IZ 0 and the dependence on random phase disappears. So for local CS parameters which support the resonant condition D N stochastic jumps are exactly compensated and motion of particle becomes effectively regular. So there are certain regions in the CS where particle dynamics escapes chaotization and particles follow the almost unperturbed classical Speiser orbits and thus, form field-aligned PSBL ion beams. The dependence on æ is very non-monotonic and can result in a phase space structuring. In this case, ion distribution consists of small-scale ion beams which are localized in phase and physical space. Such smallscale spatially localized ion beams were initially predicted in a model developed

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by Ashour-Abdalla et al. [1] and were called “beamlets”. According to this theory, beamlets are produced by the spatially localized resonant sources simultaneously operating in the distant CS. Later observations of beamlets in auroral PSBL and in the magnetotail confirmed this theory [10, 29]. It is natural to assume that the properties of velocity distributions of charged particles observed in PSBL may have an imprint of spatial and temporal characteristics of the magnetic and electric fields in the acceleration source(s). To explain the peculiarities of ion velocity distributions Onsager et al. [16] suggested field-aligned ion acceleration at an extended CS source with approximately a constant value of the magnetic field everywhere in the source. Thus, ion distributions in the nearEarth PSBL are controlled only by the velocity-filter (VF) effect due to magnetotail convection which produces the equatorward drift of accelerated ions while they are moving from the source to the observation point. Ashour-Abdalla et al. [1], on the contrary, proposed that generation of field-aligned beamlets may simultaneously takes place in several spatially localized resonances located in the wide vicinity earthward of distant X -line. The efficiency of ion acceleration at each resonance depends on local characteristics of the magnetic field BZ .X / which generally depends on the distance from the Earth. As a result energy gain of ions may vary with the location of their acceleration site (so-called place of birth effect). This scenario simultaneously accounts for two effects: (1) the global latitude dispersion of emerging structure qualitatively similar to the one considered for example by Takahashi and Hones [24]; (2) fragmentation of this structure on a set of a small-scale substructures each of them might experience their own dispersion [9]. An estimation of temporal scales of PSBL ion beam is another difficult task, especially for one-point observations. Earlier measurements of plasma characteristics in PSBL reported the short duration of ion beams (few minutes). It was assumed that ion beams have transient nature which could be addressed either to the transient character of their acceleration in the source or to the spatial effect due to the relative motion of PSBL boundary (so-called flapping). Some authors considered ion beams as mostly spatial (i.e. very long living) structures [1] and explained their short duration by fast magnetotail flappings. Other authors attributed short observation of PSBL beams to their impulsive generation in the CS with the characteristic time scales 1–2 min [3]. The impulsive character of acceleration provides time of flight effect (TOF) which spreads ions having different energies along the magnetic field line so that more energetic ions are observed first. This phenomenon was considered as origin of Time-Dispersed Ion Structures (TDIS) which are often registered in auroral PSBL during active periods [18]. But, in presence of convection the TOF unavoidably produces the latitudinal (spatial) energy dispersion. As a result, it is almost impossible to separate spatial and temporal effects when a spacecraft moves in one direction towards the NS. The temporal nature of TDIS is easier to identify when a spacecraft moves from the NS towards the lobe. In this case VF and TOF effects produce an opposite character of ion energy dispersion. This analysis was used by Sauvaud and Kovrazhkin [19] in order to identify spatial and temporal characteristics of ion dispersed structures observed in PSBL at low altitudes. Grigorenko et al. [7] applied the similar analysis to Cluster observations in magnetotail PSBL

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and showed that the typical duration of PSBL ion beam during quiet and moderately disturbed periods is 5–15 min. Because of the slow motion of spacecraft in apogee of its orbit, rapid cuts of the PSBL-Plasma Sheet (PS) region are nonavailable. Thus for reliable identification of spatial and temporal characteristics of ion beam one should compare the values of ion field-aligned velocity observed at the lobeward edge of PSBL in its successive crossings by the spacecraft. In case of frequent flapping oscillations such analysis may help to identify transient effects in ion acceleration. In this paper we present two examples of PSBL ion beams which are the manifestations of transient and quasi-steady character of ion acceleration. We will show that the presence of transient effects in ion velocity distributions observed in PSBL may be related with the proximity of acceleration source to the magnetic separatrix. In our analysis, we will use measurements of ion three-dimensional velocity distribution functions collected every 12 s by the hot ion analyzers (HIA) onboard Cluster-1 (Cl-1) and Cl-3 and the HC velocity distribution functions compiled for 8 s by composition and distribution function analyzer (CODIF) onboard Cl-4 [17]. The magnetic field data were obtained with 4 s resolution by the fluxgate magnetometer FGM [2]. We will also use electron data provided by Plasma Electron and Current Experiment (PEACE) [9].

31.2 Observations of Magnetic Separatrix Crossing and Transient Effects in PSBL Plasma Distributions On 12.09.2001 at 15:05 UT Cluster was located in the southern lobe at [19.2, 2.3, 1.8] RE (GSE) and at 15:07 UT all Cluster spacecraft encountered PSBL. During the period of interest the magnetic activity was moderate (AE 300 nT). Cl-4 observations from the CODIF, PEACE and FGM instruments between 15:05 and 15:12:30 UT are shown in Fig. 31.1. Ion and electron velocity distribution functions displayed in (V? ; Vjj ) plane for selected time sequences indicated by arrows are presented in the upper part of the Fig. 31.1. HC and electron Energy-Time spectrograms and three components of the magnetic field are presented in the three upper panels. The bottom panel of the figure shows the values of HC field-aligned velocities Vjj corresponding to the maximum of velocity distribution functions which are displayed by black dots together with a half-maximum widths of the corresponding velocity distribution functions displayed by the vertical lines crossing each dot. jBX j=jBj time profile displayed by grey line is also shown in this panel. At 15:07 UT Cl-4 crossed the lobeward edge of PSBL and observed high-velocity field-aligned ion beam streaming earthward with Vjj D 1;700 km=s (see “1i” velocity distribution) and having the half-maximum width of velocity distribution function Vjj 600 km=s Vjj =Vjj D 0:35 . Before this moment at 15:06:14 UT a tailward electron beam started (see “1e” velocity distribution). Three spins later, at 15:06:26 UT the earthward streaming electron beam with higher energy appeared (2e) and became stronger at 15:06:30 UT (3e). Simultaneously the energy

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Fig. 31.1 Experimental observation of magnetic separatrix crossing on 12.09.2001 between 15:05–15:12:30 UT Cluster was located at [19.2, 2.3, 1.8] RE (GSE). From top to bottom: ion and electron velocity distribution functions in (V? ,Vjj ) plane, measured by CODIF and by PEACE instruments (onboard Cl-4) respectively at the moments indicated by the arrows; E-T spectrograms of ions and electrons; three components of the magnetic field and values of ion field-aligned velocity corresponding to the maximums of velocity distribution functions and displayed by black dots. Half maximum widths of velocity distribution functions along the magnetic field direction are shown by vertical lines crossing the corresponding dots. In the same panel the time profile of BX =jBj is shown by grey line. The intervals of field-aligned ion beam registrations are shaded by pink color

of tailward electron beam increased, so that, by the moment of field-aligned ion beam registration the counterstreaming velocity distribution consisting of two fieldaligned electron beams was formed. It became more hot and isotropic inside the PSBL region (4e). These features of electron velocity distributions indicate on the magnetic separatrix crossing by Cluster spacecraft.

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Inside the PSBL but still close to its lobeward edge (jBX j=jBj was of the order of 1.0) field-aligned ions with lower parallel velocities were registered. Then, 40 s after the first encounter with the ion beam, when Cl-4 was already inside PSBL (jBX j=jBj decreased) it observed sudden increase of ion beam energy (Vjj D 1;900 km=s) followed by the widening (Vjj D 1;460 km=s and Vjj =Vjj 0:8) of its velocity distribution function (see “2i” distribution measured at 15:07:40 UT). At this time Cl-1 and Cl-3 also observed the same energetic ion beam (not shown). Simultaneously, electron energy increased up to a few keV, which is typical for the PS. Then, between 15:07:56–15:08:28 UT and between 15:08:36–15:11:41 UT Cl-4 registered more isotropic ion velocity distributions without signatures of field-aligned beams, like one observed at 15:10:52 UT (3i). It is worth to note that Cl-3 which was located farther from the NS registered field-aligned ion beam at 15:08:01, 15:08:37, 15:09:49, 15:11:01 UT, i.e. then Cl-4 observed only PS-like ion velocity distribution. This ion beam had the characteristics of velocity distribution function (Vjj and Vjj ) similar to ones observed by Cl-4 at 15:07:48 UT. This indicates that ion beam acceleration probably had rather quasi-steady character. However the observations of sudden increase of ion beam energy registered by all spacecraft at 15 W 07 W 40 UT may be related with transient effects superimposed on quasi-steady acceleration.

31.3 PSBL Manifestations of Quasi-Steady Resonant Acceleration of Ions in the CS 31.3.1 Event of 21 September 2001 On 21.09.2001 at 19:45 UT Cluster was located in the northern lobe (at Œ16; 3; 5:5 GSE ) and moved equatorward. This was magnetically very quiet day: AE index did not exceed 50 nT. Figure 31.2 shows Energy-Time spectrograms and velocity distribution functions in (V? , Vjj ) plane of ions (HIA data) and electrons obtained by Cl-1 and Cl-3 between 19:44–19:57 UT. The observations provided by Cl-4 (from CODIF instrument) are similar to ones measured by Cl-3 and are not presented. The bottom panel of Fig. 31.2 shows the values of ion field-aligned velocities Vjj corresponding to the maximums of velocity distribution functions measured by three Cluster spacecraft and displayed by the colored dots. Although the values of Vjj provided by Cl-1 and Cl-3 were measured by HIA instruments while the values of Vjj given by Cl-4 were measured by CODIF instrument the differences in energy, angular and time resolutions between these instruments do not significantly affect our results. At 19:45 UT Cl-3 and Cl-4, which were located closer to the PS, encountered PSBL and observed field-aligned energy collimated ion beam streaming earthward with Vjj D 650 km=s.Vjj =Vjj 0:2/. During 2 min of its observation the parallel velocity of ion beam does not change (see the bottom panel of Fig. 31.2). In this

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Fig. 31.2 Experimental observation of quasi-steady energy collimated ion beam on 21.09.01 between 19:44–19:57 UT. From top to bottom: ion and electron velocity distribution functions in (V? ,Vjj ) plane, measured by HIA and PEACE instruments respectively onboard Cl-1, E-T ion spectrogram obtained by Cl-1; the same data provided by Cl-3. The bottom panel shows the values of ion field-aligned velocities (Vjj ) derived from velocity distribution functions measured by HIA instruments onboard Cl-1 and Cl-3 and by CODIF instrument onboard Cl-4 and indicated by the colored dots. Half maximum widths of velocity distribution functions along the magnetic field direction are shown by vertical lines

event, contrary to the previous one, isotropic electron velocity distribution functions were observed not only together with the ion beam but also above it, in higher latitude region. It is worth to note, that electrons observed in this PSBL crossing are colder than in the previous event and have energies 0. Each resonance produces energy collimated ion beam with energy W (shown by the colored line) increasing with the distance from the Earth (red color represents most energetic ion beam). Since ion acceleration takes place at closed magnetic field lines ions beams are observed inside the layer of isotropic electrons (shown by the light-yellow color). (b) Ion beam acceleration in the single spatially extended source located near X-line. The source generates ion beam consisting from ions of different energies which form in PSBL wide in parallel energy ion velocity distribution and are observed together with anisotropic electron velocity distributions (shown by the light-pink color)

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already closed magnetic field lines (with finite BZ > 0). The acceleration process lasts, at least, several minutes and has rather a quasi-steady than transient character. The simultaneous quasi-steady operation of several resonances in the CS leads to the possibility of observation in the PSBL of set of localized ion beams with different velocities VN (where VN is the velocity of the ion beam accelerated in some particular N -th resonance). This was first demonstrated in numerical simulations by Ashour-Abdalla et al. [1] and finally proved experimentally by Zelenyi et al. [29]. In this paper we presented another example of observation (on 24.09.01) the double-peaked velocity distribution functions formed by two ion beams moving with different field-aligned velocities and intersecting in PSBL at X D 16 RE . It is worth emphasizing that this model implicitly assumes the operation of a quasistationary reconnection process but it does not associate any particular features of the acceleration process with steady reconnection itself. For such a model, reconnection is just a topological process which creates the magnetic geometry of a stationary model. Now let us consider ion beam observed in PSBL on 12.09.2001. The anisotropic electron velocity distributions consisting of low-energy beam streaming tailward (i.e. towards the acceleration source) and high-energy beam streaming earthward (i.e. from the source) which were observed at the lobeward edge of PSBL indicate that Cluster spacecraft crossed the magnetic separatrix. The crossing of magnetic separatrix had occurred just before the registration of accelerated ion beam, i.e. ion acceleration source was located closer to the X-line than in the previous case. The anisotropic electron velocity distribution functions consisting of a cold electron component counterstreaming in respect of the accelerated ion beam and a hot electron component moving in the same direction as the ion beam were observed in magnetotail PSBL by Nagai et al. [14], Fujimoto et al. [6], Nakamura et al. [15]. The authors related such distributions to the field-aligned current due to the Hall effect in the diffusion region of magnetic X-line which was located rather close to the observation point. In the event considered here the reflected accelerated electron beam was observed together with the “direct” ion beam. One may roughly estii , mate the distance from the point of observation to the X-line as: X D .V2XV e Vi / where X is the distance from the observation point to the Earth, Vi and Ve are correspondingly ion and electron field-aligned velocities estimated from the velocity distribution functions. For the event observed on 12:09:2001X 3 RE (so X-line was located at X 22 RE ). As we mentioned above the ion beam observed in PSBL on 12.09.2001 has comparatively wide in parallel energies velocity distribution function (Vjj =Vjj 0:35 0:8). It is natural to suggest that near the X -line, the gradient of magnetic field d ln B.X/ may be so large that its spatial scale becomes comparable or even smaller dX than the Larmor radius of accelerated ions. In this case, the initially spatially separated resonances overlap and form a single (“merged”) spatially extended acceleration source. Ions coming to such a source, propagate in the CS different distances Y and, thus, obtain different energy gains. This results in formation in PSBL of ion velocity distributions wide in parallel energies (Fig. 31.5b). Moreover, the transient increase of ion beam energy observed around 07:40 UT by all Cluster spacecraft

31


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located inside PSBL may indicate on the importance of inductive electric fields for ion acceleration. Such energy growth along the spacecraft trajectory cannot be explained neither by VF nor by TOF effects, since VF effect results in energy decrease in the direction from PSBL to the NS. Also for the TOF effect high energy ions should arrive before the low-energy ones. The phenomenon of the appearance of more energetic ions after the low energy ones (inverse energy dispersion) was theoretically explained earlier by Taktakishvili and Zelenyi [25], Taktakishvili et al. [26] as a result of fast growth of inductive electric field at the late stage of the acceleration process. It is worth also to note that this powerful acceleration has stopped after 07:40 UT since ions with Vjj 2;000 km=s were not observed during the remaining time interval. In the conclusion we would like to notice that ion beams observed in PSBL on 12.09.01 and on 21.09.01 may be related with two types of PSBL manifestations of powerful plasma acceleration processes occurring in the CS of the Earth magnetotail. We speculate that these manifestations may be related with different magnetic topologies associated, in the first case, with X-line located in mid- or near-Earth tail and in the last case – in distant magnetotail. As a result different spatial and temporal peculiarities of particle acceleration may be realized. Although the observations of accelerated plasma in magnetotail PSBL and in auroral PSBL at low altitudes are visually dissimilar, we would like to emphasize some important common features. Quasi-steady ion beams like one observed on 21.09.01 have long duration and may be a part of Velocity Dispersed Ion Structures (VDIS) precipitating in auroral PSBL. According to the previous studies VDIS have spatial origin with durations about 10s of minutes, are produced in the sources located in the distant CS and are observed during quiet or moderately disturbed geomagnetic periods together with electrons having typical PSBL energies 1 keV [19, 28]. All these features were presented in event of 21.09.01. On the contrary, the transient features observed in PSBL ion distributions on 12.09.01 may result in formation of complicated dispersed structures in the auroral PS resembling TDIS. TDIS are registered mostly during active periods and have a source located in near-Earth or mid- magnetotail. The typical duration of these transient structures is 1–3 min. The ion energies in TDIS are 14 keV and electrons have energies several keV [18, 19]. The similar features were observed in PSBL ion beam event on 12.09.01. One may assume that two observations of PSBL ion beams presented in this paper represent two extreme cases of ion acceleration in the magnetotail: (i) near X-line which was probably located in the mid – tail and (ii) earthward from the distant X-line, in the region of closed magnetic field lines. The dynamic processes leading to switching between these two types of ion beams present special interest and require additional studies. Acknowledgements The authors would like to thank Cluster CIS and FGM teams for providing data, Dr. C. Owen for providing electron data. This work was supported by INTAS grant Nr. 06–1000017–8943; RFBR grants Nr. 06–02–72561; 07–02–00319 and by grant of HIII472.2008.2.

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References 1. Ashour-Abdalla M., J.P. Berchem, J. Buchner, L.M. Zelenyi (1993) Shaping of the magnetotai from the mantle: global and local structuring, J. Geophys. Res., 98, 5651. 2. Balogh A., et al. (2001) The Cluster magnetic field investigation: Overview of in-flight performance and initial results, Ann. Geophys., 19, 1207. 3. Baumjohann W., G. Paschmann, N. Sckopke, C.A Cattell, C.W. Carlson (1988) Average ion moments in the plasma sheet boundary layer, J. Geophys. Res., 93, 11,507. 4. Buchner J. and Zelenyi L.M. (1986) Determenistic chaos in the dynamics of charged particles near a magnetic field reversal, Phys. Lett., A, 118, 395. 5. Burkhart G.R. and J. Chen (1991) Differential memory in the Earth’s magnetotail, J. Geophys. Res., 96, 14033. 6. M. Fujimoto, T. Nagai, N. Yokokawa, Y. Yamade, T. Mukai, Y. Saiti, S. Kokubun (2001) Tailward electrons at the lobe-plasma sheet interface detected upon dipolarizations, J. Geophys. Res., 106, A10, 21,255–21,262. 7. E.E. Grigorenko, J.-A. Sauvaud, L.M. Zelenyi (2007) Spatial-Temporal characteristics of ion beamlets in the plasma sheet boundary layer of magnetotail. J. Geophys. Res., 112, A05218, doi:10.1029/2006JA011986. 8. M. Hoshino, T. Mukai, T. Yamamoto, S. Kokubun (1998) Ion dynamics in magnetic reconnection: Comparison between numerical simulation and Geotail observations, J. Geophys. Res., 103, A3, 4509–4530. 9. Johnstone A.D., Alsop C., Burge S., Carter P.J., Coates A.J., Coker A. J., Fazakerley A.N., Grande M., Gowen R.A., Gurgiolo C., Hancock B.K., Narheim B., Preece A., Sheather P.H., Winningham J.D., Woodliffe R.D. (1997) PEACE: a Plasma Electron and Current Experiment, Space Sci. Rev., 79, 351–398. 10. Keiling A., H. Reme, I. Dandouras, J.M. Bosqued, G.K. Parks, M. McCarthy, L. Kistler, E. Amata, B. Klecker, A. Korth and R. Lundin (2004) Transient ion beamlet injections into spatially separated PSBL flux tubes observed by Cluster-CIS, Geophys. Res. Lett., 31, L12804, doi:10.1029/2004GL020192. 11. A. Keiling, G.K. Parks, H. Reme, I. Dandouras, M. Wilber, L. Kistler, C. Owen, A.N. Fazakerley, E. Lucek, M. Maksimovic, N. Cornilleau-Wehrlin (2006) Energy-dispersed ions in the plasma sheet boundary layer and associated phenomena: Ion heating, electron acceleration, Alfven waves, broadband waves, perpendicular electric field spikes and auroral emissions, Ann. Geophys., 24, 2685–2707. 12. Lyons L.R. and T.W. Speiser (1982) Evidence for current sheet acceleration in the geomagnetic tail, J. Geophys. Res., 87, 2276. 13. Martin R.F. Jr. (1986) Chaotic particle dynamics near a two-dimensional magnetic neutral point with application to the geomagnetic tail, J. Geophys. Res., 91 11,985. 14. T. Nagai, I. Shinohara, M. Fujimoto, M. Hoshino, Y. Saito, S. Machida, T. Mukai, Geotail observation of the Hall current system: Evidence of magnetic reconnection in the magnetotail (2001) J. Geophys. Res., 106, A11, 25,929–25,949. 15. Nakamura R., W. Baumjohann, T. Nagai, M. Fujimoto, T. Mukai, B. Klecker, R. Treumann, A. Balogh, H. Reme, J.A. Sauvaud, L. Kistler, C. Mouikis, C. J. Owen, A.N. Fazakerley, J.P. Dewhrust, Y. Bogdanova (2004) Flow shear near the boundary of the plasma sheet observed by Cluster and Geotail, J. Geophys. Res., 109, A05204, doi:10.1029/2003JA010174. 16. Onsager T.G., M.F. Thomson, R.C. Elphig, J.T. Gosling (1991) Models of electron and ion distributions in the plasma sheet boundary layer, J. Geophys. Res., 96, 2099. 17. Reme H., C. Aoustin, J.M. Bosqued, I. Dandouras et al. (2001) First multispacecraft ion measurements in and near the Earth’s magnetosphere with identical Cluster ion spectrometry (CIS) experiment, Annales Geophysicae, 19, 1303. 18. Sauvaud J.-A., D. Popescu, D.C. Delcourt, G.K. Parks, M. Brittnacher, V.A. Sergeev, R.A. Kovrazhkin, T. Mukai, and S. Kokubun (1999) Sporadic plasma sheet ion injections into the high altitude auroral bulge – satellite observations, J. Geophys. Res., 104, 28,565.

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19. Sauvaud J.-A., R.A. Kovrazhkin (2004) Two types of energy-dispersed ion structures at the plasma sheet boundary, J. Geophys. Res., 109, A12213, doi:10.1029/2003JA010333. 20. Sauvaud J.-A., P. Louarn, G. Fruit, H. Stenuit et al. (2004) Case studies of the dynamics of ionospheric ions in the Earth’s magnetotail., J. Geophys. Res., 109, A01212, doi:10.1029/2003JA009996. 21. Savenkov B.V., L.M. Zelenyi, M. Ashour-Abdalla, and J. Buchner (1991) Regular and chaotic aspects of charged particle motion in a magnetotail-like field with a neutral line, Geophys. Res. Lett., 18, 1587. 22. Seki K., M. Hirahara, T. Terasawa, T. Mukai, Y. Saito, S. Machida, Y. Yamamoto, S. Kokubun (1998) Statistical properties and possible supply mechanism of tailward cold OC beams in the lobe/mantle regions, J. Geophys. Res., 103, 4477. 23. Speiser T.W. (1965) Particle trajectories in the model current sheet based on the open model of the magnetosphere, with applications to auroral particles, J. Geophys. Res., 70, 1717. 24. Takahashi K. and E.W. Hones (1988) ISEE 1 and 2 observations of ion distributions at the plasma sheet-tail lobe boundary, J. Geophys. Res., 93, 8558. 25. A.L. Taktakishvili, L.M. Zelenyi (1990) Bursts of energetic protons in the Earth’s magnetotail. Proceedings of the Joint Varenna-Abastumani-ESA-Nagoya-Potsdam Workshop on “Plasma Astrophysics” held in Telavi, Georgia. ESA SP-331, 51–55. 26. A.L. Taktakishvili, L.M. Zelenyi, E.T. Sarris, R.E. Lopes, D.V. Sarafopoulos (1993) Temporal dispersion structures of proton and electron bursts in the Earth’s magnetotail. Planet. Space Sci., 41, no. 6, 461–467. 27. Zelenyi L.M., J. Buchner and D.V. Zogin (1988) Quasiadiabatic ion acceleration in the Earth’s magnetotail, paper presented at Varenna-Abustumani Workshop on Plasma Astrophysics, Eur. Space Agency, Publ. SP-285, 227. 28. Zelenyi L.M., R.A. Kovrazhkin and J.M. Bosqued (1990) Velocity-dispersed ion beams in the nightside auroral zone: AUREOL-3 observations, J. Geophys. Res., 95, 12119 29. Zelenyi L.M., E.E. Grigorenko, J.-A. Sauvaud and R. Maggiolo (2006) Multiplet structure of acceleration processes in the distant magnetotail, Geophys. Res. Lett., 33, L06105, doi:10.1029/2005GL024901. 30. Zelenyi L.M., Dolgonosov M.S., Grigorenko E.E., Sauvaud J.-A. (2007) Universal properties of the nonadiabatic acceleration of ions in Current Sheets, JETP Letters, 85, 4, 187–193. 31. Zelenyi L.M., M.S. Dolgonosov, E.E. Grigorenko, J.-A. Sauvaud (2008), Fine structure of PSBL plasma process: filamentation, nonlinear and dispersive effects, in Future Perspectives of Space Plasma and Particle Instrumentation and International Collaborations edited by M. Hirahara, I. Shinohara, Y. Miyoshi, N. Terada, and T. Mukai, American Institute of Physics, pp.5–14, 2009.

Chapter 32

Cluster Observations of Energy Conversion Regions in the Plasma Sheet O. Marghitu, M. Hamrin, B. Klecker, K. Rönnmark, S. Buchert, L.M. Kistler, M. André, and H. Rème

Abstract Cluster allows for the first time a systematic examination of energy conversion, by the evaluation of the power density, E J, with E the electric field and J the current density. Following a careful inspection of the Cluster plasma sheet data from the summer and fall of 2001, we selected 43 energy conversion regions (ECRs), out of which 26 concentrated load regions (CLRs, E J > 0) and 17 concentrated generator regions (CGRs, E J < 0). As expected in the tail, at about 19 RE geocentric distance, the energy conversion is more intense for CLRs, on average some 25 pW=m3 , compared to some 5 pW=m3 for CGRs. The CLRs are located closer to the neutral sheet and dominated by E and J in the GSE y direction, unlike the CGRs, that prefer locations towards the plasma sheet boundary layer, where the deviations of E and J from the GSE y direction can be significant. The ECRs are often associated with high speed bulk flows, on average faster and hotter for

O. Marghitu () Institute for Space Sciences, Bucharest, Romania and Max-Planck-Institut für extraterrestrische Physik, Garching, Germany e-mail: [email protected] M. Hamrin Department of Physics, Ume˚a University, Ume˚a, Sweden and Swedish Institute of Space Physics, Ume˚a, Sweden B. Klecker Max-Planck-Institut für extraterrestrische Physik, Garching, Germany K. Rönnmark Department of Physics, Ume˚a University, Ume˚a, Sweden S. Buchert and M. André Swedish Institute of Space Physics, Uppsala, Sweden L.M. Kistler Space Science Center, University of New Hampshire, Durham, USA H. Rème CESR-CNRS, Toulouse, France


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CLRs. The CLRs appear to be associated also with density drop and sometimes with temperature anisotropy, Tk > T? , features which are observed less frequently for CGRs.

32.1 Introduction Although the plasma sheet behaves, on average, as a load, because of the large scale dawn–dusk electric field and cross-tail current, its structure is highly inhomogeneous. The energy stored in the magnetic field is supposed to be converted into plasma kinetic and thermal energy at rather localized acceleration sites, and then transported away, by means of e. g. the bursty bulk flows (BBFs [1]). A fraction of the energy carried towards the Earth is re-converted into Poynting flux (e.g. [2]), and eventually powers the aurora (e.g. [10]). Concentrated generator regions have been recently identified in the plasma sheet boundary layer by means of Cluster data [7,8], consistent with simulation results on energy conversion and transport in the tail [4]. This paper is a first attempt towards a systematic investigation of the energy conversion in the plasma sheet, to make use of the multi-point capabilities of the Cluster mission. We focus on a set of 43 energy conversion regions (ECRs), most of them located near the spacecraft apogee (at 19RE geocentric distance), selected from the Cluster plasma sheet crossings in 2001. Energy conversion appears often to be quite structured, and the traversal of the ECRs in our set, essentially in the GSE –z direction, takes of the order of 10 min – to be compared with the several hours plasma sheet crossing. Therefore, we call the ECRs either concentrated load regions (CLRs, E J > 0) or concentrated generator regions (CGRs, E J < 0). The word ‘concentrated’ refers specifically to the z direction, but a case study analysis [8] suggests that the CGRs might be ‘concentrated’ as well in the other directions, and in time. More extended ECRs are also visible in the data occasionally, but a quantitative assessment is difficult in such cases because of the large relative errors in the small electric fields and currents. In order to evaluate E J we use data from three experiments: the ion spectrometer CIS [9], the electric field instrument EFW [6], and the fluxgate magnetometer FGM [3]. The CIS experiment provides a proxy for E, based on the frozen-in condition, E D –V B, to be derived both from the CODIF and HIA sensors (with, respectively without mass resolution). The EFW experiment measures only the electric field in the spacecraft spin plane, and uses the assumption that the parallel electric field is zero, E B D 0, in order to derive the third component of E. Since in the plasma sheet B is close to the spacecraft spin plane, the third component of E is typically not available. Although EFW does not provide the full E vector, the partial redundancy between CIS and EFW is useful to validate the events. The FGM magnetic field data allows the evaluation of the current density, via the curlometer method [5]. The reference system to be used throughout the paper is GSE. The reader is referred to [8] for a detailed discussion on the evaluation of E J and on the selection of the reference system.

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Fig. 32.1 Left: CLR event. Right: CGR event. All quantities are averaged in time, over 24 s, and some in space, over the available spacecraft. (a) Time-energy spectrogram for SC1. (b) Density for the spacecraft where CIS was operational. (c) Bulk velocity. (d) Parallel and perpendicular temperature. (e) Magnetic field. (f, g) Current density and ratio div B/curl B, used as quality index for the current estimate. Over a good fraction of the CLR event SC3 probes the close vicinity of the neutral sheet, while the other spacecraft are still above the neutral sheet (not shown), which makes the application of the curlometer problematic. However, since divB/rotB is small, there is a good chance that J is reasonably correct. (h) Ex (blue), Ey (green), and Ez (red), as derived from CODIF data, and Ey (cyan) as derived from EFW data. (i, j) Ex Jx , Ey Jy , Ez Jz (same colors as in panel (h)), E J (black), and the cumulative sums. The vertical bands indicate the ECRs, around 21:45 UT in the CLR plot and around 22:15 UT in the CGR plot. The HIA data are similar to the CODIF data and not shown. One notes the pretty good agreement between the CODIF and EFW y quantities in the bottom three panels. The peak (absolute) value of E J is 20 pW=m3 for the CLR and 5 pW=m3 for the CGR. The CLR is located close to the neutral sheet, unlike the CGR, located near the plasma sheet boundary (e). Both cases show high-speed flow in the x direction (c). The CLR shows also density drop (b) and temperature anisotropy, Tk > T? (d)

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The CLR event was observed near midnight and close to the neutral sheet (e), during the growth phase of a modest substorm .AE 300 nT/, after a prolonged quiet time. This explains the high background density (b), n > 1 cm3 , and low ion temperature (d), T < 1 keV. E J and its cumulative sum based on CODIF (i, j), HIA (not shown), and EFW (i, j cyan) data are comparable, with maximum values of 20 pW=m3 , and step variations of 300 pW=m3 . The main contribution to E J is provided by Ey Jy . The CLR is associated with high speed plasma flow, Vx Š 500 km=s (c), density drop (b), and temperature anisotropy (d). The CGR event was observed in the pre-midnight sector, in the southern plasma sheet boundary layer. E J reaches a peak (absolute) value of 5 pW=m3 and its cumulative sum has a step variation of 30 pW=m3 . Similar to the CLR event, there is good agreement between the CODIF, EFW, and HIA data (not shown), and the dominant contribution to E J is made by Ey Jy . The CGR is associated with lower velocity flow and with little temperature anisotropy. Some of the results based on the examination of the full set of events are presented in Fig. 32.2. Each panel includes two plots, one for CLRs and one for CGRs,

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in order to emphasize the differences. Since the two subsets are not very big, we have not included further refinements, e. g. with respect to geomagnetic activity. The values of the step variation in the cumulative sum (SVCS) of Ey Jy derived from CODIF, HIA, and EFW data, are compared in panel (a). The agreement is good for CLRs, where the correlation coefficient and slope of the linear regression are 0.97/0.93 and 0.96/0.94, respectively, for the CODIF–HIA/CODIF–EFW points. For CGRs, where the slope drops to 0.90/0.64, with a correlation coefficient of 0.83/0.98, the agreement is not as good. The difference is presumably related to the substantially smaller magnitude of the energy conversion in CGRs (b), which makes the respective measurements less reliable. While for CLRs the typical peak E J is a few 10 pW=m3 , for CGRs it is just a few pW=m3 . The CGRs appear to be more ‘elusive’ entities that prefer locations towards the plasma sheet boundary layer, where the fluctuations of E and J are more significant. A quantitative evaluation has not been performed so far, but based on the Bx profile, 10 out of the 17 CGRs were found to be located ‘away from the neutral sheet’ and 7 ‘close to the neutral sheet’. The relationship between the SVCS of Ey Jy , computed from CODIF/HIA/EFW data, and the SVCS of E J, computed from CODIF data (c), is not very tight, with correlation coefficient 0.75/0.74/0.76 and slope 1.55/1.68/1.03. The CLRs, on the other hand, tend to be located near the neutral sheet, where E and J are oriented predominantly in the y direction (c). 18 out of the 26 CLRs were identified ‘close to the neutral sheet’ and only eight ‘away form the neutral sheet’, six of which had very low magnitude .< 10 pW=m3 /. The prevalence of Ey Jy is well reflected by correlation coefficients and slopes equal to 0.89/0.86/0.93 and 1.00/0.96/1.07, respectively, for the dependence between the SVCS of Ey Jy and E J. Nevertheless, the CLR with the highest peak E J, not included in panel (c), is dominated by Ez Jz . Energy conversion is often associated with high speed bulk flows (d), on average faster for CLRs than for CGRs. The average speed is 500 km=s in 23 CLR events, compared to just 250 km=s in 12 CGR events; for three CLRs and five CGRs the plasma flow is rather weak. The examination of the proton distribution function in a few cases shows that, for CGRs, the bulk flow is often field-aligned, while for CLRs the E B drift prevails – consistent with the respective locations of the CGRs and CLRs ‘away from’ and ‘close to’ the neutral sheet. No obvious tendency is seen in the flow speed, with respect to the magnitude of the energy conversion, except that most of the time the speed is positive, as expected at 19RE . An outstanding exception is, again, the CLR event with the highest peak E J, coincident with a major intensification of a substorm (the AE index jumps from 750 to 1;500 nT), which makes this event a good candidate for a detailed case study. With one exception (of just 4 pW=m3 ), the CLRs associated with high speed flows show also density drops, similar to the BBFs. While this suggests a strong relationship between CLRs and BBFs, the details are still to be explored. Unlike the CLRs, only 5 CGRs of the 12 associated with high speed flows show also density drops. The average temperature (e) is also higher for CLRs than for CGRs, 3.8 keV compared to 3.0 keV. In a general sense, the larger flow speeds and temperatures for CLRs are consistent with the expectations, since the CLRs behave as sources,

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while the CGRs as sinks, for the mechanical energy, in bulk kinetic or thermal form. For 15 CLRs (more than half of the cases) and five CGRs the temperature is anisotropic, Tk > T? (f), to our knowledge a feature not pointed out so far. For CLRs, when the plasma is accelerated locally by the Lorentz force, whose work is equal to (J B/V D .–V B/J Š E J; Tk > T? could be related to a faster thermalization in parallel direction, with a corresponding increase in Tk . If the observation is made close enough to the acceleration site, the anisotropy is still visible, otherwise the distribution becomes fully thermalized, with Tk D T? . The temperature anisotropy is more difficult to explain for CGRs, although it is conceivable that energy conversion is in general associated with wave-particle interactions, that can result in Tk > T? .

32.3 Prospects For additional insight on energy conversion more case study work is required, as well as further systematic investigation, e. g. of the temperature anisotropy and density drop. In order to improve the data processing speed and the statistics, an automated ECR recognition procedure is needed. Such a tool would enable a more comprehensive examination of the plasma sheet data, as well as of data from other regions, like the boundary layers at the magnetospheric flanks. The THEMIS mission opens new possibilities for the investigation of energy conversion. The data from the current disruption region make a perfect candidate in this sense, provided that a method to derive the current from only three satellites will be developed. Acknowledgements O.M. acknowledges support through the PECS contract ECSTRA, C98048, and the kind hospitality of Max-Planck-Institut für extraterrestrische Physik, Garching.

References 1. Angelopoulos, V., Baumjohann, W., Kennel, C. F., et al.: Bursty bulk flows in the inner central plasma sheet. J. Geophys. Res. 97, 4027–4039 (1992) 2. Angelopoulos, V., Chapman, J. A., Mozer, F. S., et al.: Plasma sheet electromagnetic power generation and its dissipation along auroral field lines. J. Geophys. Res. 107 (2002). doi: 10.1029/2001JA900136 3. Balogh, A., Carr, C., Acuña, M. H., et al.: Overview of in-flight performance and initial results. Ann. Geophys. 19, 1207–1217 (2001) 4. Birn, J., Hesse, M.: Energy release and conversion by reconnection in the magnetotail. Ann. Geophys. 23, 3365–3373 (2005) 5. Dunlop, M., Balogh, A., Glassmeier, K.-H., Robert, P.: Four-point Cluster application of magnetic field analysis tools: The Curlometer. J. Geophys. Res. 107 (2002). doi:10.1029/2001JA005088 6. Gustafsson, G., André, M., Carozzi, T., et al.: First results of electric field and density observations by Cluster EFW based on initial months of operation. Ann. Geophys. 19, 1219–1240 (2001)

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7. Hamrin, M., Marghitu, O., Rönnmark, K., et al.: Observations of concentrated generator regions in the nightside magnetosphere by Cluster/FAST conjunctions. Ann. Geophys. 24, 637–649 (2006) 8. Marghitu, O., Hamrin, M., Klecker, B., et al.: Experimental investigation of auroral generator regions with conjugate Cluster and FAST data. Ann. Geophys. 24, 619–635 (2006) 9. Rème, H., Aoustin, C., Bosqued, J., et al.: First multispacecraft ion measurements in and near the Earth’s magnetosphere with the identical Cluster ion spectrometry (CIS) experiment. Ann. Geophys. 19, 1303–1354 (2001) 10. Wygant, J., Keiling, A., Cattell, C., et al.: Polar spacecraft based comparisons of intense electric fields and Poynting flux near and within the plasma sheet – tail lobe boundary to UVI images: An energy source for the aurora. J. Geophys. Res. 105, 18 675–18 692 (2000)

Chapter 33

Acceleration of > 40 keV Electrons in Near-Earth Magnetotail Reconnection Events ˚ A. Asnes, M.G.G.T. Taylor, and A.L. Borg

Abstract Reconnection of magnetic field lines have been invoked as an acceleration mechanism producing significant amounts of super-thermal electrons in the high ˚ energy range. However, in a recent paper by Asnes et al., 2008, energetic particle generation during geomagnetic active times was shown to be mainly caused by plasma sheet heating rather than reconnection driven acceleration. To examine this discrepancy we present observations from an ensemble of near-Earth reconnection events observed by the Cluster spacecraft near apogee in the years 2001–2004, and compare electron fluxes with values obtained during the surrounding time intervals and statistical results obtained in the same region in the plasma sheet. We find that observations in the proximity of the X-line only sometimes yield high fluxes of energetic electrons. The maximum flux level is always observed near the neutral sheet, and typically occurs when the distribution is near Maxwellian. It appears that although reconnection immediately heats the cold inflowing plasma, this acceleration is typically only sufficient to bring the electron fluxes up to a level approximate to the pre-existing plasma sheet levels.

33.1 Introduction Observations of solar flares indicate that as much as 10–50% of the energy released by magnetic reconnection goes to acceleration of electrons to supra-thermal energies [1], illustrating that collisionless reconnection should be considered as an important element of particle acceleration in plasmas. In the Earth’s magnetosphere reconnection takes place in many different regions, with very different boundary conditions in the distant tail, at the dayside magnetopause and the magnetosheath [2–4]. Here we focus on Cluster observations of near-Earth magnetotail reconnection, observed at ˚ A. Asnes () and M.G.G.T. Taylor ESA/ESTEC, Keplerlaan 1, 2200AG, Noordwijk, The Netherlands e-mail: [email protected] A.L. Borg Norwegian Defense research Institute, Kjeller, Norway


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distances in the XGSM direction between 16 and 19RE and within a few hours of midnight local time. The onset of reconnection in this region is not well understood, but is believed to occur when the current sheet becomes sufficiently thin to allow plasma instabilities to grow and demagnetize the particles. Reconnection in the nearEarth tail must initiate within the closed field line region of the plasma sheet, but may continue onto the open field lines of the lobe. Although the geometry of the Xline region remains the same for closed and open field line reconnection, there are significant differences in the inflow (pre-reconnected) plasma, which may be decisive for the reconnection rate. Modeling (magneto-hydrodynamic (MHD), hybrid and particle in cell-PIC) of the reconnection problem indicates that reconnection rate is proportional to the Alfvén velocity vA in the inflow region [5], which varies from 100s of km/s in the central plasma sheet up to several 1,000s km/s in the lobe region. It is likely that the direct reconnection acceleration of electrons depends strongly on the reconnection rate, which is equivalent to the “out of plane” reconnection electric field. This suggests that the most intense acceleration occurs when near-Earth reconnection has reached open field lines. The direct acceleration mechanism is a straightforward acceleration occurring as particle trajectories fall in the reconnection electric potential. The particle trajectories might be Speiser-like [6], but PIC simulations show a variety of possible trajectories where forces conspire to allow the particles to travel significant distances within the diffusion region [7]. In the case of a strong guiding field the electrons will stay magnetized, but may also undergo a significant amount of acceleration [8]. In addition to direct particle acceleration in the diffusion region, the larger scale plasma transport occurring as a result of near-Earth reconnection can accelerate the particles further, through the betatron and Fermi mechanisms [9]. The outflow regions Earthward and tailward are not symmetric, and the plasma pile up towards the dipolar field leads to more efficient betatron acceleration on the earthward side [10, 11]. Recent simulation results indicate that particles can also be accelerated within magnetic islands (or flux ropes) by the Fermi mechanism [12]. It is likely that coalescence of small-scale magnetic islands will also allow particles to be accelerated several times within reconnection diffusion regions.

33.2 Reconnection Events The 15 reconnection events used for the statistical results were observed by Cluster in the magnetotail between 19 < XGSM < 16RE at the times listed in Table 33.1. In all the events the Cluster spacecraft observe both tailward and earthward flows (usually in that sequence), which have been identified [13]. as reconnection outflow The table lists the peak differential electron fluxes s1 cm2 sr1 keV1 measured by a sample channel (E3: 70.3–96.7 keV) of the RAPID IES instrument [14]. In order to examine the effects of reconnection acceleration on the plasma sheet population the observations are separated into three intervals: (1) the period 1.5 h before the event; (2) during the event (inside the reconnection outflow) and (3) 1.5 h after

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Table 33.1 Energetic electron flux in channel 70.3–96.7 keV for reconnection events from tail seasons 2001–2004 Peak flux Reconnection time Te, MK Ne cm3 Va km/s Before X-line After B nT interval (UT) 2001–08–17 16:23–16:44 2001–08–22 09:42–10:00 2001–09–10 07:48–08:04 2001–09–15 05:01–05:16 2001–10–01 09:37–09:47 2001–10–08 12:33–13:02 2001–10–11 03:25–03:42 2002–08–18 17:03–17:16 2002–08–21 07:54–08:25 2002–09–13 18:07–18:25 2002–10–02 21:20–21:23 2003–08–17 16:38–16:43 2003–08–24 18:30–19:10 2003–09–19 23:25–23:35 2004–09–14 23:01–23:07

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1 2.3 0.9 1 2.8 5 3.5 6.5 1.3 2.0 230 keV down to L 3:0. The two largest events cause electron enhancements at all energies from >130 keV to >3 MeV down to L 2:5. We found that the Cluster IES observations of the source populations in the pre midnight plasma sheet were quite intense with strong field aligned distributions during the early main phase of the storm on July 24. The combined results indicate that these early main phase electron fluxes at Cluster may be directly linked to the rapid response of electrons at low L observed by HEO3 and could have been the source for the 1:55 MeV electron fluxes taken at geosynchronous orbit [44]. However, we also know that electron flux enhancements do not occur with all solar wind speed increases nor with all magnetic storms. To generate energetic electron flux increases may require a substantial solar wind speed increase associated with a precursor solar wind density enhancement and combined with a southward turning of the IMF as was shown in Blake et al. [7]. Reeves et al. [45] showed that magnetic storms could produce cases of energetic electron flux increases, decreases, or no change in flux. They also showed that, during an 11-year period in which they examined 226 storms, 53% were followed by flux enhancements, 28% were associated with flux decreases and 19% showed no change in the electron fluxes or an adiabatic response. They indicated that the magnitude of the storms, as measured by the minimum DST did not matter nor did the L-value of the observations for L 3 MeV. E4 to E6 are omni directional sensors while E1-E2 and E3 are two telescopes. (Note: The HEO3 E1-E2 telescope temperature rose rapidly with altitude for the regions with L 5 during the period of the study, because of increased solar illumination as its attitude changed with altitude. The >130 and >230 keV electron channels became noisy as the temperatures rose. This raised their background levels and limits their usefulness at large L.) The HEO3 trajectory is close to the magnetic equator from L 1:75 to 3 but significantly far from it by L 6:5 (B/Bo 6:6 in the Olson-Pfitzer [40, 41] field model). For more details about HEO3 see Fennell et al. [16]. The Cluster data is from the RAPID IES sensor [61]. IES measures electrons with energies of 40–400 keV in eight channels. It obtains 3D angular distributions in two broad energy channels. We will show the angular data for the 42–53 keV electrons. The data used here were taken when the Cluster spacecraft were traversing the plasma sheet near their apogee in the pre midnight region on July 24, 2004.

34.3.2 HEO3 Observations of July 2004 Storms There was a sequence of magnetic storm events starting late on July 16 with a 80 nT event followed by events on July 22, 24, and 26 with DST minima of 101, 148 and 197 nT respectively, as shown in Fig. 34.8. Note that the DST minima were reached at 0300 UT on July 17, 0300 UT on July 23, 1200 UT on July 25, and 1400 UT on July 27. Examples of the electron responses in the inner magnetosphere are shown in Fig. 34.9 using HEO3 data. Figure 34.9 shows the electron rates

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Fig. 34.8 DST , LPP , and KP for the period 14 July to 8 August in 2004. The red bar indicates the period of the Cluster data used. The HEO3 data spanned the full time interval of the plots. LPP is calculated from DST using the O’Brien and Moldwin [38] formulation

Fig. 34.9 Coded electron intensity plots. The left and right hand vertical axes have different ranges for the channels indicated. Dashed vertical lines identify the time of the DST minimum for each event. The L, L , and MLT are labeled at the top of each plot. The legends relate the colors to the electron energy channels with E1, E2, E3, E4, E5, and E6 having energies >0:13 (red), >0:23 (gray), >0:45 (blue), >0:63 (purple), >1:5 (green), and >3 MeV (black), respectively

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measured at nine different L and L values for the interval from 14 July to 8 August 2004. (L and L were obtained from the HEO3 magnetic ephemeris data base which was generated using the Olson-Pfitzer field model [40,41].) Each panel is annotated with the L, L and MLT where the data were taken and the data from the individual energy channels are color-coded (see legends and caption for Fig. 34.9). We binned the HEO3 data into L-bins corresponding to L D 1:75, 2.0, 2.25, etc. up to L D 10 and show only a subset in Fig. 34.9 to show the trends in the data. The vertical dash lines in Fig. 34.9 correspond to the times of the DST minima for the storms in the 16–26 July 2004 interval. Figure 34.10 shows the solar wind parameters for only

Fig. 34.10 Interplanetary magnetic field (top four panels), solar wind density, speed and proton temperature (bottom three panels) on July 24, 2004. The arrow marks the interval where the intense energetic plasma sheet electron fluxes were observed

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July 24. There was a sudden commencement-like positive excursion in DST prior to the main phase of the July 24 event as seen in Fig. 34.8. This was associated with a rotation in the interplanetary magnetic field and the solar wind speed jump near 1200 UT on July 24 as shown in Fig. 34.10. The solar wind speed was above 550 km/s the whole day and, after the field rotation, the interplanetary field intensity was relatively constant for the remainder of the day. We start by using the HEO3 data to examine the electron responses to magnetic activity preceding 24 July 2004 to see if there are residual effects in the inner magnetosphere. The data in Fig. 34.9 show that very deep in the inner magnetosphere at L D 2 .L D 1:9/ the electron fluxes did not start rising until about 0000 UT on 25 July and then only in the lowest energy channels (see panel a). The 450 and 630 keV fluxes started rising near 0000 UT on 27 July and the >1:5 MeV fluxes rose about a day later. At L D 2 there was not an electron response to the 16 and 22 July 2004 events and there wasn’t a response in the >3 MeV channel to any of the events. The electrons with energies that would correspond to a “source” population were observed to rise about half way through the main phase of the 24 July event at L D 2. The higher energies did not start rising until 48 h later during the secondary main phase that started late on 26 July. Thus while there is evidence that “source” population electrons reached L D 2 during the 24 July event there was not a corresponding increase in the relativistic electron population that deep in the inner magnetosphere. At L D 2:5 (L 2:41; see panel b) the electron responses to the 24 July event were significantly stronger than at L D 2. However, except for a gradual rise in the 130 and 230 keV electron fluxes over the 14–23 July interval, there was no clear higher energy electron response to the July 16 and 22 storms at L D 2:5. The 130 and 230 keV electron fluxes started a gradual rise near 0000 UT on July 24 that steepened near 1200 UT on 25 July. The 450 and 630 keV fluxes rose sharply near 1200 UT (i.e. near DST minimum) on 25 July at L D 2:5. The higher energy, >1:5 and >3 MeV, flux rises were more delayed, as is generally observed for all stormtime events, with the >3 MeV fluxes starting to rise after 0800 UT on July 27 during the main phase of the July 26 storm. We note that the time history of the estimated L position of the plasma pause .LPP / shown in Fig. 34.8 had values LPP 3:15 for the July 16 and July 22 events but had values of LPP D 2:9 and 2.6 during the July 24 and July 26 events, respectively. (The LPP values were obtained from DST using the O’Brien and Moldwin [38] formulation.) The fact that relativistic electron fluxes were not observed at small L in response to the July 16 and July 22 storms may be consistent, if the LPP values are accurate, with chorus waves not being present at these L values because they are inside the plasmapause boundary. Separately, we note that if we used the LMAX curve in Fig. 34.4 we would expect the peak in the relativistic electron flux to be at L 4:3 and 4:1 for the July 16 and July 22 events respectively. Observationally, the peak fluxes occurred at L 4 for the July 16 event at the four lowest energies with no response at the two highest energies. The peak fluxes were at L 3:75–4 at the three lowest energies and at L 4:25 for the three highest energies for the July 22 event. Similarly, the LMAX curve in Fig. 34.4 would indicate that the flux peaks for the July 24 and

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July 26 events should be at L 3:7 and 3:5 respectively. The HEO3 data had the peak fluxes near L 3:5–3:75 for the two lowest energies. It was difficult to tell for the July 24 event since near their peak values these lower energy electron fluxes only had a short plateau before they continued to rise in response to the July 26 event. They had well defined temporal peaks at higher L values but those were not the maximum fluxes. For July 24 and July 26 events the higher energy channels .>450 keV/ had their peak fluxes near L 3:5 for both events. At this L value these higher energy fluxes were nearly constant for several days, following the July 26 event, after achieving their peak values (see Fig. 34.9 panels (c-e)). The largest electron responses were to the July 24 and July 26 events. These events are only 2 days apart. At the highest L values, the July 26 event main phase caused a flux drop so we are somewhat unsure of the peak flux from the July 24 event. We note that all the available L values, not just those in Fig. 34.9, were used in searching for the L of maximum flux for event. At L values from 3.0–6.5 the fluxes were observed to rise on 23 July and reached an initial peak or a plateau early on 24 July, and then further increased on 25 July or fell depending on the L value. The main response to the July 16 event was a flux drop for >450 keV electrons at all L’s and a rise in the 130 and 230 keV “source” electron fluxes only at L D 3:0–4:0 RE (Fig. 34.9, panels (c–e)). (The HEO3 low energy telescope temperature rose rapidly with altitude for the regions with L 5 because of increased solar illumination. The 130 and 230 keV electron channels started getting noisy and their background levels rose. The E1 channel was unusable while the E2 channel has a relatively high background for those L values. Thus, our measurements of the source electron fluxes are uncertain for L 4:5.)

34.3.3 Cluster Observations of July 24, 2004 Storm As noted above, the July 24 event caused a strong response in electrons deep in the inner magnetosphere. During the interval, 24–26 July the solar wind speed was enhanced and IMF Bz turned southward starting at 2100 on July 24 (see Fig. 34.10), reaching a level of 20nT early on July 25 and remained at that level until 1520 UT that day (not shown). Cluster transitioned from the near-earth tail-lobe, boundary layer and plasma sheet region prior to and during the main phase of this event, as evidenced by the IES electron fluxes in Fig. 34.11. The spin average energetic electron fluxes were very similar at all four Cluster spacecraft throughout July 24. The spacecraft were in the magnetotail on the morning side, near 3 MLT, during the onset of a 148 nT storm that started gradually near 1200 UT (ref. Fig. 34.8). At the time of the storm onset the Cluster spacecraft appeared to be in the tail lobe or near the high latitude boundary of the plasma sheet as evidenced by the lack of electron fluxes observed by the IES sensor on all four cluster satellites in Fig. 34.11 and the weak ion fluxes observed by CIS (not shown).

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Fig. 34.11 Spectrograms of spin averaged electron fluxes measured by RAPID IES on all four Cluster spacecraft for 24 July 2004

As the main phase of the July 24 storm progressed a bit, the Los Alamos geosynchronous satellites near midnight observed a substorm injection around 1300 UT (not shown). The Los Alamos satellites also observed a second injection near 2320 UT but none in between. The Cluster spacecraft entered the plasma sheet about 3 h later, just before 1600 UT, while the DST 30 nT and Kp was falling from C6 to C5. The steepest decline in DST occurred after 2200 UT on July 24. Between 1700 and 2400 UT, the Cluster IES instruments observed intense fluxes of field aligned electron (FAE) distributions as shown in Fig. 34.12. These FAE distributions were not constant but occurred whenever Cluster entered the plasma sheet during this interval, as indicated by the FGM [6] Bx and BT measurements in Fig. 34.12a. These FAE fluxes, with pitch angles 450 keV electrons had reached low L values by the time of or just after DST minimum. The sequence is less clear for L 3 because of the preexisting enhanced >100 keV fluxes that remained from the earlier activity. However the >3 MeV fluxes are definitely rising by 1200 UT on July 25 at L D 3. So not only are the source type electrons present by the time of early recovery so are the accelerated or high energy fluxes. The fact that the intense 40–400 of keV electron fluxes were observed at Cluster during the early storm main phase, very late on July 24, combined with the clear rise of fluxes of electrons at low L with energies consistent with those observed in the plasma sheet (but raised in energy by transport as in Fig. 34.5) provides strong circumstantial evidence that the electrons observed by Cluster are very possibly the source for the subsequent enhancements of MeV fluxes deep in the inner magnetosphere.

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34.4 Summary Examination of historical and current results that describe and attempt to understand what causes the enhancements of electron fluxes in the inner magnetosphere’s radiation belts has narrowed the current research focus onto basically two mechanisms. Radial transport from the near earth plasma sheet while conserving the particle’s magnetic moment has been considered the primary mechanism for a long time. More recently, in the last decade, mechanisms that break conservation of M have been strongly considered. Much of the recent observational evidence points to the necessity for M breaking mechanisms in localized regions, for example 5 L 6, if one is to explain PSD peaks there even if radial transport is also operating. However the discussion is not closed because there is conflicting evidence and the number of observational studies is still relatively small. The Cluster and HEO3 storm response example shown above hints that transport could explain the rapid appearance of particles to near 0.5 MeV energies at very low L values prior to or at DST minimum during some storms. This provides a reason to continue to look carefully at the processes and to try to find ways to test the different models. However, one major difficulty that we currently have to contend with is that it usually takes multiple observation platforms to obtain the necessary physical space and energy sampling to trace the PSD from the distant plasma sheet to low L values in the magnetosphere. This requires very careful intercalibration of disparate data sets. In addition, except for the CRRES observations [34–37], there are not simultaneous wave measurements that can be used to assess whether the M breaking mechanisms are operating or not in most of the recent studies. It is hoped that the NASA RBSP mission will help solve some of this difficulty because it covers the whole inner magnetosphere with electron instruments that have a wide range, covering plasmasheet to highly relativistic energies, has the wave and field measurements needed, and with its two platforms, will increase the sampling cadence for determining the L dependence of the PSD profiles. However the RBSP must still rely on a second set of measurements within the distant plasma sheet. Acknowledgements The authors would like to acknowledge their many colleagues at The Aerospace Corporation that have supported their efforts, provided references, and participated in discussions on the topic of energetic electron sources and process in the magnetosphere. This work was supported by grants GC189637NGA from Boston University, 64361 from University of Colorado, and by The Aerospace Corporation’s Mission Oriented Investigation and Experimentation program.

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