Handbook on Solar Wind: Effects, Dynamics and Interactions

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HANDBOOK ON SOLAR WIND: EFFECTS, DYNAMICS AND INTERACTIONS

No part of this digital document may be reproduced, stored in a retrieval system or transmitted in any form or by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained herein. This digital document is sold with the clear understanding that the publisher is not engaged in rendering legal, medical or any other professional services.

HANDBOOK ON SOLAR WIND: EFFECTS, DYNAMICS AND INTERACTIONS

HANS E. JOHANNSON EDITOR

Nova Science Publishers, Inc. New York

Copyright © 2009 by Nova Science Publishers, Inc.

All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Library of Congress Cataloging-in-Publication Data Handbook on solar wind : effects, dynamics, and interactions / editors, Hans E. Johannson. p. cm. Includes bibliographical references and index. ISBN 978-1-61324-976-5 (eBook) 1. Solar activity--Environmental aspects. 2. Solar wind. 3. Climatic changes. I. Johannson, Hans E. QB524.H36 2009 523.5'8--dc22 2009009167

Published by Nova Science Publishers, Inc. Ô New York

CONTENTS Preface

vii

Chapter 1

On The Relationship between Solar Activity and Forest Fires Milan Rodovanovic and João Fernando Pereira Gomes

Chapter 2

Statistical Characteristics of the Heliospheric Plasma and Magnetic Field at the Earth's Orbit during Four Solar Cycles 20-23 A.V. Dmitriev, A.V. Suvorova and I.S. Veselovsky

Chapter 3

Solar Energy Research, Sustainable Development and Applications Abdeen Mustafa Omer

Chapter 4

Experimental and Modeling Evidence of the Solar Wind Energy Influence on the Earth Atmosphere L.N. Makarova, and A.V. Shirochkov

1

81 145

177

Chapter 5

Electrostatic Wind Propulsion Alexander Bolonkin

197

Chapter 6

Solar Wind and Motion of Interplanetary Dust Grains J. Klačka, L. Kómar, P. Pástor and J. Petržala

227

Chapter 7

A Role of the Solar Wind in Dynamics of Interstellar Dust in the Solar System M. Kocifaj and J. Klačka

275

Chapter 8

Solar Wind, Large Diamagnetic Cavities, and Energetic Particles Jiasheng Chen

291

Chapter 9

Solar Wind Interaction with Artificial Atmospheres L. Gargaté, R. A. Fonseca, R. Bamford, R. Bingham and L. O. Silva

319

Short Communications

339

Short Communication A Solar Radiation over Dongola, Northern Sudan Abdeen Mustafa Omer

341

vi

Contents

Short Communication B Electrostatic Solar Light-Wind Sail Alexander Bolonkin

353

Short Communication C Solar and Solar Wind AB-Sail Alexander Bolonkin

367

Short Communication D Electrostatic MagSail Alexander Bolonkin

379

Short Communication E The 27-Day Periodicity in Geomagnetic Activity and Solar Wind Parameters over Solar Cycle 23 Ana G. Elias, Virginia M. Silbergleit, Ana Curcio and Patricia A. Larocca

391

Short Communication F Weibull Parameters for Wind Speed Distribution at Fifteen Locations in Algeria Y. Himri,, S. Himri, and A. Boudghene Stambouli

403

Short Communication G On the Limits of Applicability of the Ray Interference Integral Method for Calculations of the Temporal Structure of Solar Radio Bursts A.N. Afanasiev and N.T. Afanasiev Index

413 419

PREFACE The solar wind is a stream of charged particles —a plasma—ejected from the upper atmosphere of the sun. It consists mostly of electrons and protons with energies of about 1 keV. These particles are able to escape the sun's gravity, in part because of the high temperature of the corona, but also because of high kinetic energy that particles gain through a process that is not well-understood at this time. The solar wind creates the Heliosphere, a vast bubble in the interstellar medium surrounding the solar system. Other phenomena include geomagnetic storms that can knock out power grids on Earth, the aurorae such as the Northern Lights, and the plasma tails of comets that always point away from the sun. This new book presents the latest research in the world on this topic. Chapter 1 - Fires of large dimension destroy forests, harvests and housing objects. Apart from that, combustion products and burned surfaces become large ecological problems. Very often fires emerge simultaneously on different locations of a region so a question could be asked if they always have been a consequence of negligence, pyromania, high temperatures or maybe there has been some other cause. This study is an attempt of establishing the possible connection between forest fires that numerous satellites registered and activities happening on the Sun immediately before fires ignite. Fires emerged on relatively large areas from Portugal and Spain on August 2005, as well as on other regions of Europe. The cases that have been analyzed show that, in every concrete situation, an emission of strong electromagnetic and thermal corpuscular energy from highly energetic regions that were in geo effective position had preceded the fires. Such emissions have, usually, very high energy and high speeds of particles and come from coronary holes that also have been either in the very structure or in the immediate closeness of the geo effective position. It should also be noted that the solar wind directed towards the Earth becomes weaker with deeper penetration towards the topographic surface. However, the obtained results suggest that, there is a strong causality relationship between solar activity and the ignition of these forest fires taking place in Southwestern Europe. Chapter 2 - The review presents analysis and physical interpretation of available statistical data about solar wind plasma and interplanetary magnetic field (IMF) properties as measured in-situ at 1 A.U. by numerous space experiments during time period from 1964 to 2007. The experimental information have been collected in the OMNI Web/NSSDC data set of hourly averaged heliospheric parameters for last four solar cycles from 20th to 23rd. We studied statistical characteristics of such key heliospheric parameters as solar wind proton number density, temperature, bulk velocity, and IMF vector as well as dimensionless

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parameters. From harmonic analysis of the variations of key parameters the authors found basic periods of 13.5 days, 27 days, 1 year, and ~11 years, which correspond to rotation of the Sun, Earth and to the solar cycle. The authors also revealed other periodicities such as specific five-year plasma density and temperature variations, which origin is a subject of discussion. They have found that the distribution of solar wind proton density, temperature and IMF is very close to a log-normal function, while the solar wind velocity is characterized by a very broad statistical distribution. Detailed study of the variability of statistical distributions with solar activity was performed using a method of running histograms. In general, the distributions of heliospheric parameters are wider during maximum and declining phase of the solar cycle. More complicated behavior was revealed for the solar wind velocity and temperature, which distribution is characterized by two- or even tree-peak structure in dependence on the phase of solar cycle. Our findings support the concepts of solar wind sources in the open, closed and intermittent magnetic regions on the Sun. Chapter 3 - People relay upon oil for primary energy and this for a few more decades. Other orthodox sources may be more enduring, but are not without serious disadvantages. Power from natural resources has always had great appeal. Coal is plentiful, though there is concern about despoliation in winning it and pollution in burning it. Nuclear power has been developed with remarkable timeliness, but is not universally welcomed, construction of the plant is energy-intensive and there is concern about the disposal of its long-lived active wastes. Barrels of oil, lumps of coal, even uranium come from nature but the possibilities of almost limitless power from the atmosphere and the oceans seem to have special attraction. The wind machine provided an early way of developing motive power. The massive increases in fuel prices over the last years have however, made any scheme not requiring fuel appear to be more attractive and to be worth reinvestigation. In considering the atmosphere and the oceans as energy sources the four main contenders are wind power, wave power, tidal and power from ocean thermal gradients. The renewable energy resources are particularly suited for the provision of rural power supplies and a major advantage is that equipment such as flat plate solar driers, wind machines, etc., can be constructed using local resources and without the advantage results from the feasibility of local maintenance and the general encouragement such local manufacture gives to the build up of small-scale rural based industry. This chapter gives some examples of small-scale energy converters, nevertheless it should be noted that small conventional i.e., engines are currently the major source of power in rural areas and will continue to be so for a long time to come. There is a need for some further development to suit local conditions, to minimise spares holdings, to maximise interchangeability both of engine parts and of the engine application. Emphasis should be placed on full local manufacture. Chapter 4 - So far the solar wind energy contribution to energetic balance of the Earth atmosphere was ignored in any atmospheric and climatic research. However the solar wind is a permanent source of a significant amount of the electromagnetic energy emitted by the Sun which is constantly supplied to the near-Earth space. Traditionally this energy was attributed entirely to sustain a definite level of geomagnetic activity expressed as intensity of the geomagnetic substorms and storms. The authors of this paper found in 1997 after analysis of the data of the Russian rocket sounding in the Arctic that enhancement of the solar wind dynamic pressure do influence thermal regime of the polar middle atmosphere. Similar analysis of the atmospheric balloon sounding data obtained at different stations in both the Arctic and the Antarctica shows that the stratospheric temperature closely correlated with the

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ix

solar wind electromagnetic energy. After establishing these statistically confident relations it was necessary to find a plausibly reasonable physical mechanism which could explain reality of the found coupling. A concept of the global electric circuit as a physical mechanism for explanation of a direct coupling between the solar wind and the middle atmosphere was suggested. The authors proposed a new, modified version of the global electric circuit with two Electro-Motive Force (EMF) generators: internal EMF generator driven by the thunderstorm activity of the Earth (a common feature of previous circuit configurations) and an external EMF generator driven by the solar wind energy. The passive elements of this circuit are the ionospheric E-layer (external element of previous version of the circuit), stratospheric conducting layer of heavy ions (h=20-25 km) and conducting layer of the Earth surface. In this configuration a previous scheme of the global electric circuit is a part of the proposed version of it. Numerical evaluation of the electromagnetic energy of the solar wind is a very difficult task. It can be done only approximately. Structure of the Earth magnetosphere is changing constantly upon influence of the solar wind as well as a position of a boundary of the magnetosphere (magnetopause). The problem could be solved if the authors present boundary of the Earth magnetosphere and the ground surface as a giant capacitor with external and internal plates correspondingly. The external plate of this capacitor (magnetopause) could be moved toward the Earth under the solar wind pressure. The energy of the solar wind roughly can be calculated by estimation of energy which is required to move the magnetopause for a definite distance. The magnetopause is located at ~ 12 Re (were Re is the Earth radius) under a quite condition of the solar wind. During strong disturbances of the solar wind the magnetopause could approach the Earth at distance of approximately ~ 6 Re. Such estimation shows that energy required for movement of magnetopause at a distance of 6 Re is equal to ~ 5 10 15J. Preliminary numerical estimations showed that under typical conditions such amount of the Joule heating dissipated in stratosphere is comparable with a rate of heating of ozone layer by the solar UV radiation. Furthermore, such amount of energy is sufficient for enhancement of cyclonic activity in the Earth atmosphere. As the next step of exploration a numerical calculation scheme was elaborated, which took into account the abovementioned processes. This numerical scheme was successfully used in one of the global dynamical photo-chemical models of the atmospheric circulations. The results of these model simulations confirmed all previously made preliminary estimations concerning influence of the solar wind energy on the atmospheric processes. There are the definite plans to improve the effectiveness of the proposed physical mechanism describing interaction of the solar wind with the Earth atmosphere. Evaluation of the effects of different degree of the Earth electric conductivity must be taken into account in the next explorations on the subject. Chapter 5 - A method for space flights in outer space is suggested by the author. Research is present to shows that an open high charged (100 MV/m) ball of small diameter (4–10 m) made from thin film collects solar wind (protons) from a large area (hundreds of square kilometers). The proposed propulsion system creates many Newtons of thrust, and accelerates a 100 kg space probe up to 60–100 km/s for 100–800 days. The 100 kg space apparatus offers flights into Mars orbit of about 70 days, to Jupiter about 150 days, to Saturn about 250 days, to Uranus about 450 days, to Neptune about 650 days, and to Pluto about 850 days. The author developed a theory of electrostatic wind propulsion. He has computed the amount of thrust (drag), to mass of the charged ball, and the energy needed for initial

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charging of the ball and discusses the ball discharging in the space environment. He also reviews apparent errors found in other articles on these topics. Computations are made for space probes with a useful mass of 100 kg. Chapter 6 – Effect of solar wind particulates on motion of dust grain moving in Solar System is derived in space-time. Acceleration of the grain under the effect of solar wind (including the non-radial component of its velocity vector) and grain's mass change are obtained. The results for the effect of solar wind are used in space-time derivation of the effect of electromagnetic radiation. The contribution considers simultaneous action of the solar electromagnetic radiation and solar wind, together with gravity of the Sun and planets, on motion of interplanetary dust grains with radii of several microns and tens of micrometres. Applications for the standardly used radial solar wind and real solar wind velocity vector are compared. The important results can be summarized as follows: 1. Spherical dust grain can be captured in mean-motion orbital resonances with planet Neptune when the secular evolution of the grain's semimajor axis is an increasing function of time. Nothing like this exists for the Poynting-Robertson effect and radial solar wind. The effect of the real solar wind velocity vector mimics the behavior of the complicated case of the behavior of nonspherical dust grain under the action of solar electromagnetic radiation. 2. Simultaneous action of the Poynting-Robertson and real solar wind effects causes spiralling of the dust grain outward from the Sun, in the zone of outer planets. The flux of interstellar gas is also important in this zone. This additional nongravitational effect stabilizes dust grain's orbit in the zone of the Edgeworth-Kuiper belt. Chapter 7 – Interstellar dust grains have been detected by the dust detectors onboard the Ulysses and Galileo spacecrafts. Motion of the interstellar dust particles in the Solar System is driven by gravitational and nongravitational forces. As for gravity, theaction of the Sun is the dominant gravitational effect. Nongravitational forces are represented by solar electromagnetic radiation force, similar effect of the solar wind, and, Lorentz force for submicrometer-sized dust grains. Lorentz force originates from the action of interplanetary magnetic field on electrically charged grains and solar wind velocity plays a crucial role in this nongravitational force. Chapter 8 – The Earth's magnetospheric cusp is a key region for transferring the solar wind energy, mass, and momentum into the Earth's magnetosphere. The solar wind particles can directly access the dayside high-altitude cusp, creating large diamagnetic cavities with strong electromagnetic fluctuations. Different from magnetic reconnection, the cusp diamagnetic cavities are created by the interactions of the solar wind with the local magnetic field, which could depress the field from more than 200 nT into near zero nT, tearing wide and deep magnetic holes in the Earth's magnetosphere. The power spectral density of the electromagnetic fluctuations inside the cavities shows increases by up to four orders of magnitude in comparison to adjacent regions. The strong electric field fluctuations can efficiently energize the cusp charged particles by cyclotron resonant acceleration. The discovery of cusp energetic particle (CEP) events is a major breakthrough in space science. It is changing the traditional view about the structure and dynamics of the magnetosphere and has opened a great avenue for the Sun-Earth connection investigations. The CEPs are detected in the high-altitude cusp region and are always there day after day. They have energies from 20 keV up to 15 MeV, which is also the typical energies of the ring current and outer radiation belt populations. The CEP intensities are observed to increase by as much as four orders of magnitude during cusp diamagnetic cavity crossings. These recent in situ

Preface

xi

observations reveal a new, broad and dynamic region of acceleration and trapped radiation in geospace, which centers at the Earth's magnetospheric cusp and has a size of up to 10.5 Earth radii. The new region of radiation can extend to low-latitude region, and can reach 6.6 Earth radii from the Earth's center, providing a direct particle source for the outer Van Allen radiation belt. Chapter 9 – Active experiments in space involving artificial atmospheres began with the AMPTE releases. In these seminal experiments, a cloud of Barium or Lithium was released and photoionized by the UV radiation from the sun. The cloud expanded and interacted with flowing solar wind, thus providing important data about pick-up ion behaviour, diamagnetic cavity formation, and shock formation. More recently, systems consisting of a dipole magnetic field and a plasma source are being considered and studied in spacecraft propulsion, and as a spacecraft shield from Solar Energetic Particles (SEP) from the sun. The authors use a 3D massively parallel hybrid code to analyze the behaviour of such systems in the presence of a plasma flow. The model is ideal to study artificial atmospheres interacting with the solar wind, covering the relevant physical scales, and allowing a kinetic treatment of the ions. Arbitrary density distributions, and arbitrary initial velocity distributions can be set, while dynamic load balancing algorithms are used to guarantee parallel efficiency. The authors focus our analysis in the differences between two distinct scenarios: the unmagnetized scenario of a plasma cloud expanding in the solar wind in the presence of the Interplanetary Magnetic Field (IMF), and the magnetized scenario of a laboratory plasma flow shock against a dipole magnetic field structure. Our results show that both configurations effectively deflect the incoming plasma. The nature of the shocks formed in both situations is different, with a bow shock being formed in the first case, while in the second case there is a compression of the magnetic field, but no bow shock is observed. In the unmagnetized case, the diamagnetic cavity formation is the most significant aspect, with the cloud particles producing the diamagnetic currents as they expand outwards due to their temperature. The dependency of the plasma standoff distance with the plasma density, velocity, and with the dipole field intensity in the magnetized case is highlighted, and the relevance of these scenarios for the shielding of spacecrafts is also addressed. Short Communication A - A number of years worth of data concerning the solar radiation on a horizontal surface and sunshine duration at Dongola, Northern Sudan have been compiled, evaluated and presented in this short communication. Measurements of global solar radiation on a horizontal surface at Dongola for a whole year are compared with predictions made by several independent methods. In the first method, Angstrom formula was used to correlate relative global solar irradiance to the corresponding relative duration of bright sunshine. Regression coefficient are obtained and used for prediction of global solar irradiance. The predicted values were consistent with measured value (±6% variation). In the second method, by Barbaro et al. (1978) sunshine duration and minimum air mass were used to derive an empirical correlation for the global radiation. The predicted values compared well with measured values (±6% variation). The diffuse solar irradiance is estimated using Page’s, Lui and Jordan’s correlations. The results of the two formulas have a close agreement. The annual daily mean global radiation ranges from 5.27 to 7.65 kW h m-2 per day. It is concluded that Northern Sudan is enjoyed with abundant solar energy. Short Communication B - The solar sail has become well-known after much discussion in the scientific literature as a thin continuous plastic film, covered by sunlight-reflecting

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appliquéd aluminum. The Solar wind propulsion also has many researches. Any solar sail simultaneously is the solar wind sail because the light and solar wind have a same direction and adsorb by a sail material. Earlier, there were attempts to launch and operate solar light and solar wind sails in near-Earth space and there are experimental projects planned for long powered space voyages. However, as currently envisioned, the solar light-wind sail has essential disadvantages. Solar light-wind pressure in space is very low and consequently the solar light-wind sail has to be very large in area. Also it is difficult to unfold and unfurl the solar sail in space. In addition it is necessary to have a rigid framework to support the thin material. Such frameworks usually have great mass and, therefore, the spacecraft’s acceleration is small. Here, the author proposes to discard standard solar light-wind sail technology (continuous plastic aluminum-coated film) with the intention instead of using millions of small, very thin aluminum charged plates and to release these plates from a spacecraft, instigated by an electrostatic field. Using this new technology, the solar sail composed of millions of plates can be made gigantic area but have very low mass. The acceleration of this new kind of solar sail may be as much as 300 times that achieves by an ordinary solar sail. The electrostatic solar sail can even reach a speed of about 300 km/s (in a special maneuver up to 600–800 km/sec). The electrostatic solar sail may be used to move a large spaceship or to act as an artificial Moon illuminating a huge region of the Earth’s surface. Short Communication C - The Solar and Solar Wind sail is a large thin film used to collect solar light and solar wind pressure for the moving of space apparatus. Any solar sail simultaneously is the solar wind sail because the light and solar wind have a same direction. The light (photons) and solar wind (protons and electrons) are adsorbed by a sail material. Unfortunately, the solar radiation pressure is very small, about 9 μN/m2 at Earth's orbit. The solar wind pressure is much less. However, the light and wind forces significantly increases up to 0.2 - 0.35 N/m2 near the Sun. The author offers his research on a new revolutionary highly reflective solar sail which performs a flyby (after a special maneuver) near Sun and attains a velocity up to 400 km/sec enabling reaching far planets of the Solar system in short time, and enabling escape flights out of the solar system. New, highly reflective sail-mirror allows avoiding overheating of the solar sail. It may be useful for probes close to the Sun as well as probes to Mercury and Venus Short Communication D - The first reports on the “Space Magnetic Sail” concept appeared more 30 years ago. During the period since some hundreds of research and scientific works have been published, including hundreds of research report by professors at major research universities. The author herein shows that all these works related to Space Magnetic Sail concept are technically incorrect because their authors did not take into consideration that solar wind impinging a MagSail magnetic field creates a particle magnetic field opposed to the MagSail field. In the incorrect works, the particle magnetic field is hundreds times stronger than a MagSail magnetic field. That means all the laborious and costly computations revealed in such technology discussions are useless: the impractical findings on sail thrust (drag), time of flight within the Solar System and speed of interstellar trips are essentially worthless working data! The author reveals the correct equations for any estimated performance of a Magnetic Sail as well as a new type of Magnetic Sail (without a matter ring). Short Communication E - Geomagnetic activity and solar wind parameters are analyzed in terms of the periodicity linked to solar rotation that is the 27-day cycle. Its fluctuation in

Preface

xiii

frequency and time is studied using the wavelet power spectrum. For this purpose the authors used the geomagnetic activity aa index and three solar wind parameters: magnetic field magnitude (B), density (d) and velocity (v). The sunspot number, Rz, is also analyzed to have a solar activity reference. The study was carried out for the period July 1996 – December 2005, which corresponds to solar cycle 23, except for the last years corresponding to its final minimum level. For the time period and parameters here analyzed, the 27-day periodicity is observed to have enhanced power during maximum and falling phase of the solar activity cycle, with no significant power during the ascending phase, not even in solar activity. Besides the time evolution, a periodicity variation is also noticed along the solar cycle. In some cases the period decreases as the solar cycle approaches minimum levels, as expected from the meridional movement of active regions towards lower solar latitudes during this time. However, periodicites lower than 27.27 days (synodic period at the solar equator ) are also observed, pointing out inner regions of the sun as possible sources of the active regions, or a surface phenomenon arising because of solar activity shifts during solar rotation. Short Communication F - In the present study the Weibull parameters distribution function were computed for 15 locations in Algeria. The wind data which covers a period of almost 10 years between 1977 and 1988 was adopted. The average wind speed at a height of 10 m above ground level was found to range from 2.3 to 5.9 m/s. The Weibull distributions parameters (c & k) were found to vary between 3.1 and 7.2 m/s and 1.19 to 2.15 respectively. Higher wind speeds were observed in the day time between 09:00 and 18:00 h and relatively smaller during rest of the period. Generally the long-term seasonal wind speeds were found to be relatively higher during spring to the autumn month of September compared to other months. The two parameters of a Weibull density distribution function for the three areas namely (Littoral, Highlands and Sahara) were compared and wider distributions were observed in the Sahara. It is also noticed from this work that the Weibull distribution give a good fit to experimental data. The aim of this work is to provide information about the distribution of wind in different regions of Algeria (Littoral, Highlands and Sahara) and give useful insights to engineers and experts dealing with wind energy. Short Communication G - The authors discuss the possibility of using the ray interference integral method to carry out calculations of scattering of radio emission from sources embedded in the corona and solar wind. The authors point out that preliminary analysis of the topology of caustics produced by geometrical optics rays and by partial waves forming the interference integral enables correct calculations of the solar radio burst structure.

In: Handbook on Solar Wind: Effects, Dynamics … Editor: Hans E. Johannson

ISBN: 978-1-60692-572-0 © 2009 Nova Science Publishers, Inc.

Chapter 1

ON THE RELATIONSHIP BETWEEN SOLAR ACTIVITY AND FOREST FIRES Milan Rodovanovic1 and João Fernando Pereira Gomes2 1

Geographical Institute “Jovan Cvijic”, Serbian Academy of Sciences and Arts – SANU, Belgrade, Serbia 2 Chemical Engineering Department/IBB - IST - Instituto Superior Técnico, Torre Sul, Lisboa, Portugal and Chemical Engineering Department, ISEL - Instituto Superior de Engenharia de Lisboa, Lisboa, Portugal,

Abstract Fires of large dimension destroy forests, harvests and housing objects. Apart from that, combustion products and burned surfaces become large ecological problems. Very often fires emerge simultaneously on different locations of a region so a question could be asked if they always have been a consequence of negligence, pyromania, high temperatures or maybe there has been some other cause. This study is an attempt of establishing the possible connection between forest fires that numerous satellites registered and activities happening on the Sun immediately before fires ignite. Fires emerged on relatively large areas from Portugal and Spain on August 2005, as well as on other regions of Europe. The cases that have been analyzed show that, in every concrete situation, an emission of strong electromagnetic and thermal corpuscular energy from highly energetic regions that were in geo effective position had preceded the fires. Such emissions have, usually, very high energy and high speeds of particles and come from coronary holes that also have been either in the very structure or in the immediate closeness of the geo effective position. It should also be noted that the solar wind directed towards the Earth becomes weaker with deeper penetration towards the topographic surface. However, the obtained results suggest that, there is a strong causality relationship between solar activity and the ignition of these forest fires taking place in Southwestern Europe.

2

Milan Rodovanovic and João Fernando Pereira Gomes

1. Global Climate Changes and Forest Fires On the basis of contemporary data realization, it has become obvious that relatively frequent forest fires, seizing areas in several states almost simultaneously, cannot be simply explained by intentional or unintentional anthropogenic cause. It has been logical the causes should look for in climate changes. “The frequency, size, intensity, seasonality, and type of fires depend on weather and climate in addition to forest structure and composition. Fire initiation and spread depend on the amount and frequency of precipitation, the presence of ignition agents, and conditions (e.g. lightning, fuel availability and distribution, topography, temperature, relative humidity, and wind velocity)” (Dale et al., 2001). However, problem of fires emerged in the area of (not only) Europe out of time, e.g. at the beginning of March or at the end of November. Cases occurring during winter months (as shown in figure 1) and at the beginning of spring are especially interesting for the scientific researches. “Since the winter season add very a few amount of rain, there where 6 841 fires between January and March. These fires where responsible for 10 777 ha of burned area. On the 10th of January there was a fire in the Guarda district that burned 348 ha of shrub land. In the month of March, there were 7 fires larger than 100 ha mostly of those, concentrated in littoral district of Viana do Castelo and Aveiro” (http://www.fire.uni-freiburg.de/programmes/eu-comission/EU-Forest-Fires-inEurope-2005.pdf)1 On the other side, it seems there are severely opposing opinions even in the field of climatology itself. “The biggest problem we have with the climate debate is that the big mathematical models can't predict what'll really happen since the models contain simplifications that are probably wrong in important ways. We end up having to guess what will happen. Nature continually makes the climate change even without humans getting involved. So, even once, a change has happened and it is yet impossible to figure out how much of this change was caused by humans” (http://www.futurepundit.com/). Many pages could be written on this theme, but for this occasion a concise survey of the results in the last ten years will be presented. Taking over the role of the institution for arousing human conscience the Intergovernmental Panel on Climate Change (IPCC) according the estimation from 1995 claimed the Earth’s temperature increased between 0.3 and 0.6 °C during the 20th century. According the estimation from 2001, the increase is from 0.6 to 0.2C. According the World Meteorological Organization Report (WMO, 1999) that increase in the previous century is 0.7 °C. By the year 2100. models of the IPCC (the making of which 2 500 scientists took participation) predict the increase of global temperature of 1.4-5.8 °C. The last estimations date from 2007. and according them the air temperature could increase between 2 and 4.5 °C till the end of this century, providing the anthropogenic CO2 emission continues.

1

The data relate on 2005 for Portugal

On The Relationship between Solar Activity and Forest Fires

3

Figure 1. Numerous fires were scattered across Southeast Asia on January 21, 2007, when the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua satellite passed overhead and captured this image http://earthobservatory.nasa.gov/NaturalHazards/ natural_hazards_v2.php3?img_id=14085)

The paper by Mann et al., (1998) gave was significant stimulus to global warming advocates because of excessive atmosphere pollution with greenhouse effect gases. The results they came to have pointed that the 20th century, which is the period from 1990 was the warmest in the previous 600 years (it looks like hockey stick in the figure, by which this term was included into scientific literature). Citing Mann and Jones (2003), McGuire (2004) concluded the period after 1980 was the warmest in the last 2 000 years. He also writes that “another nail in the coffin of the global warming skeptics was provided by a research team led by Qiang Fu”. Schär et al., (2004), similarly to Beniston (2004) and Beniston and Diaz (2004) conclude that the only explanation for the heat wave in Europe i.e. in Switzerland in 2003 is that increasing concentration of greenhouse gases in the atmosphere increases climate variability as it simply raises global temperatures. Regarding eventual solar influence on weather and climate, very often the views similar to what Barron (1995) stated could be met: “Solar variability over the next 50 years will not induce a prolonged forcing significant in comparison with the effects of the increasing concentrations of CO2 and other greenhouse gases”. In common representation of papers from this field, we get an impression that thousands and thousands of pages were written, which convincingly present evidences, on the basis of which the base for Kyoto protocol was founded, above others. “The biggest catalyst for climate change today are greenhouse gases". (http://www.giss.nasa.gov/research/news/20011206/)2. 2

Shindell D. T.

4


Above many others, the paper of Girardin et al., (2006) has also appeared where it is written: “Human-induced climate change could lead to an increase in forest fire activity in Ontario, owing to the increased frequency and severity of drought years, increased climatic variability and incidence of extreme climatic events, and increased spring and fall temperatures. Climate change therefore could cause longer fire seasons, with greater fire activity and greater incidence of extreme fire activity years… Fire has also been recognized as a significant source of greenhouse gas emissions into the atmosphere. Most of this is in the form of carbon dioxide (CO2), but quantities of carbon monoxide, methane, long-chain hydrocarbons, and carbon particulate matter are also emitted”. One of the arguments showed in this paper are also described in figure 2.

Figure 2. (a) Reconstruction of area burned in the province of Ontario for 1782–1981 (thick line). Thin line represents instrumental data (1917-2003). (b) 10-year window polynomial curve (Girardin et al., 2006).

However, very soon serious criticisms have appeared on the account of the presented results. “This recent article is a perfect example of confusion the public must feel regarding important elements of the greenhouse debate. One camp could take the article and claim that numerical models are forecasting an increase in forest fires (actually, no global climate model makes such a direct prediction) and that the evidence from Ontario indeed shows an increase in burned area in recent decades. You decide, but as this essay shows, the deeper you dig into this article, the less evidence there is for any claim that the buildup of greenhouse gases has resulted in an increase in wildfires in Ontario”. (http://www.worldclimatereport.com/index.php/2007/04/25/torching-the-forest-firemyth/#more-232). Advocates of the dominant influence of the anthropogenic greenhouse effect on climate changes, i.e. global warming published a large number of scientific papers. Nevertheless, it seems those conditionally claiming opposite, more and more persistently try to leave the category of sporadic and isolated achievements. It was necessary to point out the opinions of


5

the scientists who are less present both in science and public due to the criticism of possible suggesting the views by selective approach. “Just when you were starting to believe that variations in the amount of energy coming from the sun weren’t responsible for much of the observed surface warming during the past 20 years, comes along a Scafetta and West (2006), that concludes otherwise: “We estimate that the sun contributed as much as 45–50% of the 1900–2000 global warming, and 25–35% of the 1980–2000 global warming. These results, while confirming that anthropogenic-added climate forcing might have progressively played a dominant role in climate change during the last century, also suggest that the solar impact on climate change during the same period is significantly stronger than what some theoretical models have predicted”. (http://www.worldclimatereport.com/index.php/category/climate-forcings/). Regarding concretely established links between Sun and climate in the past, Hallett et al., (2003) point out: “Highinferred water levels during solar (sunspot) minima and lower water levels during solar maxima suggest a response to climate and solar variability. …A broad distribution of sites would increase our understanding of the potential impacts of global warming on fire regimes and water balance in British Columbia. …High fire frequencies also occur in the giant sequoia forests of the Sierra Nevada between AD 1000 and 1300 …and tree-ring data from subalpine conifers in the Sierra Nevada indicate that summer temperatures exceeded late twentieth-century values between ad 1100 and 1375”. It follows the claims of Mc Guire (2004) and Mann and Jones (2003) do not refer to British Columbia. Komitov (2005) described the existing relations very picturesquely “Unfortunately during the 70s years the WMO demonstrate a very negative position to the results of these studies. As a result after 1975 all solar-climatic studies results are ignored and this is labeled as a ‘forbidden’ area for all scientific conferences and symposiums under the aegis of WMO. This is the cause why on the field of solar-climatic relations during the last around 30 years mainly space physics specialists, but not meteorologists are working”. Agerup’s (2004) “brave” results have also appeared: “For all climate scientists know, climate might have cooled by the year 2 100!” Considering that CO2 concentration reached the level of 0.037% at the end of the last century, terms “global warming” and “greenhouse effect” became the part of the standard scientific vocabulary (Ducic, Radovanovic, 2005). The attempt to study as much material on global climate changes as possible has influenced to meet many scientific papers classified in so-called opposition science. In other words, contrary to the prevailing opinion, there are more and more papers treating the question of global warming as over dimensioned. Dmitriev (1997), Michaels (1998), Arking et al., (2001), Agerup (2004), Agerup et al., (2004), Radovanovic, Ducic (2004), as well as many others have stated very severe criticisms on the account of applied methodology and results in the scenarios of IPCC. Mentioned authors point out the phenomenon of global (that is regional) climate changes does certainly exist, but they are in the first place the consequence of the natural processes, while man’s influence on them is far less. “Having examined all 40 scenarios, we have noticed the projected anthropogenic CO2 emission in all models is 6900 GT for 2000. However, on the basis of the recent data, it may be seen the emission was 6315 GT. It is 10.7% lower than the one IPCC predicted. This could be the significant failure in the projections of the future CO2 emission, especially because the period from the prognosis to the prognosticated year was relatively short. That points out the fact one should be careful in

6


accepting these prognosis, especially those of the long-term character”. (Ducic, Radovanovic, 2005). Contrary to catastrophic predictions of IPCC for the 21st century, Landschieidt (2000a) expects mild temperature decrease in period to 2010. Similar conclusions Komitov (2005) also came to: “As a result near to 2050 AD the mean Earth nearsurface air temperature will be at about 1°C lower than present. The warming will start again at the beginning of 22nd century when for a very short time the level from the end of 20th century will be reached”. Some reports from this (2007) year point to the occurrences that will come after but also contrary to those predictions the scientists of IPCC have given. (Abdusamatov3) emphasized that NASA’s data on warming on Mars and researches of ice from deep holes on Antarctica and in Greenland have confirmed the conclusion of the study from the Pulkov laboratory that the natural causes, not man’s industrial activity dictated global warming on Earth. Nevertheless, as he said, the Chinese scientists’ researches, whose results were published in January 2007 and have also predicted the natural reduction of Earth’s global temperature during next 20 years and confirmed the results of the Russian research”. (http://www.mycity.co.yu/Geografija/Precizna-prognoza-klimatskih-promena.html). Even on the short temporal series (for period 1979-1998) level, Santer et al., (2000) have got negative trends. “All model surface – 2LT trend differences are negative, unlike the observations”, shown in figure 3..

Figure 3. Least-squares linear trends and associated 95% confidence intervals in modeled and observed surface (A), 2LT (B), and surface − 2LT (C) temperature time series. 3

Habibulo Abdusamatov, laboratory manager for cosmic researches of the Main Pulkov Observatory of the Russian Academy of Sciences.


7

Areas where man’s influence is much expressed locally and regionally (urban areas, industrial areas) are not controversial. Those areas where such influence is reduced, while the warming trend is also proved are not controversial either. However, changes on the regional level are the focus of the research, i.e. there are also areas on Earth showing the trend of, conditionally saying, stagnation, as well as those areas where decreasing air temperature trend was noticed also including some urban areas. Przybylak (2002) calculated for period 19512000 that the linear trend of air temperature (C/10 years) in the area of Arctic has the following values: the Atlantic region 0.00, Siberian region 0.04, the Pacific region 0.33, the Canadian region 0.17, the region of Baffin Sea -0.19, the Arctic 1 (the data from 37 Arctic stations) 0.08, the Arctic 2 (for 60-90 N geographic latitude) 0.16 and NH (land and oceanaverage temperature for the Northern hemisphere) 0.09.

Figure 4. Changes on glaciers since 1970 (http://en.wikipedia.org/wiki/Effects_of_global_warming)

We may see from the previous figure the changes on glaciers are really impressive. In some cases it is the reduction of 1.4 meters/year. However, it is not clear why is the phrase “thinning” used in the lower part of the figure when numerous locations may be noticed whereto it comes to their increase, i.e. growth, disregarding significantly smaller amount. Climate changes which also included the area of Antarctica have reflected on the changes within vegetation. “In particular, there are reports from Antarctica that show a dramatic reaction by vegetation to the recent changes in climate; there were 700 species found growing in 1964 and 17,500 in 1990”.4 If we only relied on this index, it was obvious it would lead us to conclusion Antarctica generally lies on dramatic turning point meaning melting the large quantities of ice. Nevertheless, it might be supposed the climate conditions are so much improved that the number of plant species increased 25 times in 27 years. However, figure 5 4

Science News. Vol. 146. N 334, 1994

8


shows very illustratively the influence of climate changes on the condition of the ice on Antarctica.

Figure 5. In some parts of Antarctica, such as East Antarctica, the ice sheet is thickening (+ symbols), whereas in others, primarily in West Antarctica it is thinning (- symbols). (Vaughn, 2005)

Looking at figure 5 it may be noticed the surfaces registering the ice growth are much larger. Contrary to them, the surfaces where ice melts are far smaller but the melting amount is considerably larger. The following quotations show it is not about the results of rare fanatics: -

-

“Measurements taken by weather stations in the McMurdo Dry Valleys - the largest ice-free area in Antarctica - show that on average this region cooled by 0.125 Fahrenheit a year between 1986 and 2000. Scientists found the cooling was especially strong during the autumn and summer seasons, and they theorize it is due to a complex interplay between ocean currents. The distorted view that the continent is warming might be traced to the fact that most weather monitoring stations are based in the Antarctic Peninsula - the tongue of land projecting northward from the continent toward South America - an area which is, indeed, warming dramatically”.


9

(http://www.ncpa.org/iss/env/2002/pd011402d.html)”5. Egorova et al., (2000) point out the analysis of temperature, pressure and wind observation in the Arctic station of Vostok shows the variations of the cosmic radiation make the crucial influence on the condition of the troposphere in the vicinity of the polar region in winter conditions. Perhaps this may be a subjective impression, but it seems that around 15 references used by the authors in the first part of the paper, do not belong the group of those that could be relatively frequently met in high-cited scientific papers. It is about the studies which prove the cosmic and solar radiation influence on the circulation regime of the troposphere, cyclone activity, cloudiness, air pressure, air temperature and ozone shell. According van Geel et al., (1999) “We therefore postulate, that - periodically - sudden and strong increases of cloudiness, precipitation (snow) and declining temperatures as a consequence of solar/cosmic ray forcing have played a crucial role in the regularly occurring iceberg discharges as recorded in North Atlantic deep sea cores and the synchronous events in the Southern Hemisphere”. On the results of the researches of mentioned Mann et al., (1998) serious criticisms have appeared. McIntyre and McKitrick (2003, 2005) have used a part of the program Mann et al., (1998) used, and they have found serious problems. Not only the program does not perform the conventional PCA6 but the data normalization was performed in a way that can be described only as the wrong one. The results Soon et al., (2001) came to may be summarized through the following conclusions: 1. “The increased surface temperature of about 0.5 °C to 0.6 °C over the last one hundred years is a natural phenomenon - because 80% of the rise in levels of atmospheric CO2 during the twentieth century occurred after the initial major rise in temperature. 2. Surface temperatures (based on land and sea measurements) peaked by around 1940, then cooled until the 1970s; since then, there has been a surface warming. 3. The primary impact of the greenhouse effect of added CO2 is in the lower atmosphere (rather than at the surface), but accurate measurements of that layer of air by U.S. National Oceanic and Atmospheric Administration (NOAA) satellites over the last 22 years have not shown any hint of global warming”. The beginning and the end of the text of Monibot et al., (2005) perhaps best illustrate tense confrontation of opinions: “The science of climate change is under attack …Isn’t it time you started fighting for your science?” In some cases the reactions to the researches classified as the opposition science, can hardly be called the academic ones. “Some prominent scientists are becoming increasingly restive about the shrill portrayal of global warming science in popular media. The latest round concerned a paper by A. L. Westerling (where it is written)7 …relating an dramatic increase in western forest fires to regional warming and changes in the onset of snowmelt”. 5

Peter Doran Principal Component Analysis 7 Translator’s note 6

10


(http://www.worldclimatereport.com/index.php/2006/07/). It follows stating scientifically argumentative view, which does not fit into the prevailing opinion, is almost treated as heresy. The complete problem has deeply infiltrated even the level of the political conflicts. “Famously, Inhofe declared on the Senate floor: "With all of the hysteria, all of the fear, all of the phony science, could it be that man-made global warming is THE greatest hoax ever perpetuated on the American people? It sure sounds like it". (http://www.newwest.net/index.php/city/comment/9136/C396/L396). Citing Prim (1997), Landscheidt (1998) wrote: “Recent studies show that solar variability rather than changing CO pressure is an important, probably the dominant climate forcing factor ...The current and anticipated fleet of spacecraft devoted to the study of solar and solarterrestrial physics will therefore probably prove to have more bearing on the understanding and forecasting of climate change than the orchestrated assessments by politically motivated international panels biased towards global warming exclusively by the enhanced greenhouse effect.” Gray (2000) presented the concise perception of this problem: “Three of the four methods of measuring global temperature show no signs of global warming: -

proxy measurements (tree rings, sediments etc) for the past 1000 years, weather balloons (radiosondes) for the past 44 years, satellites (MSU8) for the past 21 years.

The fourth method, surface measurement at weather stations, gives an averaged mean global rise of more than 0.6 °C over 140 years, but is intermittent and irregular. Individual records are highly variable, regional, and sometimes, particularly in remote areas, show no change, or even a fall in temperature”. In his references Gray does not make a citation that follows, simply because he could not have known for it, since it appeared six years later. However, it seems this report represents the direct confirmation to his observations. “For over a century, a national network of “weather nerds” (for lack of a better term) have monitored backyard weather stations where they kept track of daily maximum and minimum temperature and precipitation using standardized instruments and measurement techniques. Called the U.S. Cooperative Observer Network (co-op for short), these data, which were submitted monthly for many decades on paper logs, were often used to fill in gaps from the more comprehensive observations taken by trained weather service employees at far fewer locations. But the utility of the co-op records to climate analysis was limited by their cumbersome, paper format. However, recently the interest in climate change spurred the government to digitize these paper records, thus adding many new stations to the existing network. With the addition of the co-op data, the number of stations from roughly 1890 to 1947 doubled or tripled relative to the previous baseline. …Not only did the frequency of extremes vary markedly in the early 20th century days of very low greenhouse gas levels, but the frequency of extreme events in the late 1890s was at least comparable to that in our current climate. Kunkel did some statistical tests demonstrating that the most recent period (1983-2004) was not statistically different from the earliest period (1895-1916) for many combinations of event severity and return period, 8

Microwave Sounder Units


11

although a few were significantly different. At the end of the text it was written: “If we are faced with such uncertainty with the world’s best data set, how much confidence can we really place in our interpretations of the very sparse records from Africa, Asia, and South America, not to mention the paucity of records from the world’s oceans?” (http://www.worldclimatereport.com/index.php/2006/03/15/an-extreme-view-of-globalwarming/)9. The readers to whom the geographic problem is not close, it is necessary to emphasize that about 71% of our planet is under water; for such a vast part of Earth there are not longrange series of the meteorological i.e. climate element observations. Nevertheless, Wiin-Neilsen (1997) also gave similar observations: “The comparison between the MSU data and the ECMWF10 data indicate that middle tropospheric temperature deviations show a satisfactory agreement between the two data sources. …For the two data sets we may say that none of them indicate any systematic change of the middle and lower tropospheric temperatures”. Keeping in mind the importance of these results especially comes in effect if they are observed through paleo climate prism (climate changes throughout millions of years back, without any man’s influence), the statement is especially interesting: “The present man caused increase of the greenhouse effect is causing climate changes which are much faster than Milankovic’s changes of the temporal scales that lead to an unknown future.” (Krstic et al., 2004). McGuffie, Henderson-Sellers (1997) are more cautious with their statements: “While the Milankovitch forcing offers an interesting ‘explanation’ for longterm, cycle climatic changes, the energy distributions within spectral analyses of climate and of orbital variations are interestingly different, and only recently have models begun to produce observed temperature changes from observed forcing. Almost certainly, these external changes trigger large feedback effects in the climate system which are yet to be fully understood”. Solanki (2002) concludes on the basis of the presented results in his paper (figure 6) that there is agreeable causative link between open magnetic flux from the surface of the Sun and 10 Be concentrations in ice which supports, but does not prove the Sun had important, perhaps dominant influence on our climate in the past. However, in spite of that his results relate up to 2000, he also writes: “After 1980, however, the Earth’s temperature exhibits a remarkably steep rise, while the Sun’s irradiance displays at the most a weak secular trend. Hence the Sun cannot be the dominant source of this latest temperature increase, with manmade greenhouse gases being the likely dominant alternative”. It seems the author did not accept the results of already mentioned Gray (2000) who, talking on the data for the air temperature based on relatively recent observations emphasizes: “The subsequent measurements indicate the complete absence of any positive trend”. In any case, the significance of the figure 20 is that on the basis of it long-periodic links may be clearly noticed between open solar flux on one side and Be concentration in the ice crust on Earth on the other side. Transport of material from the Sun and Space towards the Earth represents an extremely significant sign of the sensitivity of our planet to the influences from the outside. “Every year the Earth accumulates about 40,000 tons of cosmic detritus, mostly as billions of tiny flecks 9

World Climate Report, March 15, 2006 European Centre for Medium-Range Weather Forecasts

10

12


ranging in size from maillist/msg21568.html)11.

sand

grains

to

peas.”

(http://www.meteorobs.org/

Figure 6. Evolution of the open magnetic flux at the solar surface since the end of the Maunder minimum in 1700. Model predictions by Solanki et al. (2000) are represented by the red curve, reconstructions by Lockwood et al. (1999) based on geomagnetic indices by the green curve and the 10 Be concentrations in ice cores (corresponding to the inverted scale on the left y-axis, Beer et al. 1990) by the dotted curve (Solanki, 2002)

Do energetic waves penetrate together with physical depositing of the material from the Space into the Earth’s magnetosphere and atmosphere? This question is extremely significant for understanding not just atmosphere disturbances. Is the total energy coming to the Earth changeable category, if we exclude already determined variability of the solar constant? The statements that “shyly” move around low value trends bring additional confusion. “Surface thermometer measurements indicate that the temperature of the Earth is warming at an average rate close to +0.20 deg. C/decade since 1979, while the satellite data shows a warming trend of about half of this. These differences are the basis for discussions over whether our knowledge of how the atmosphere works might be in error, since the warming aloft in the troposphere should be at least as strong as that observed at the surface” 12 (http://www.ghcc.msfc.nasa.gov/MSU/msusci.html). The results Fris-Crisstensen and Lassen came to, in essence prove the connection of the air temperature in the northern hemisphere on one and solar activity (i.e. the length of the solar cycles) on the other side. It is interesting that the comparison with air temperature above 11 12

Duncan Steel Roy Spencer, 2006


13

land has shown extremely good connections with straightened curves of different length cycles (Ducic, Radovanovic, 2005). Developing such approach, other authors have also shown it could be of a great importance for understanding the causative-effective Sun-Earth connection (figure 7).

Figure 7. Length of solar Cycle LSC (filled circles), maximum ionospheric electron density in respective 11-year sunspot cycle (plus signs), Northern Hemisphere temperature anomalies (empty triangles), and local temperature anomalies in San Miguel de Tucuman, Argentina (empty circles) show a significant covariation (Adler, Elías, 2000)

Commenting this figure Landscheidt, (2003b) states: “The last value in the LSC time series seems to indicate a downward movement, a switch from short cycles to longer ones, whereas the three other curves follow their upward trend. From this divergence, Thejll and Lassen …draw the conclusion that the impact of solar activity on climate, prevailing for centuries, suddenly is no longer valid. Jumping to such a conclusion is not justified. Thejll and Lassen do not take into consideration that temperature lags solar activity by several years”. With proper respect on the manner of behaving of scientific institutions toward newspaper articles, we do not know that anyone reacted to the following quotation: “Scientists have not established a direct link between global warming and the fires that became particularly devastating in Portugal, France and Spain this summer. Nor could such a link be expected. But most people see the two phenomena as related” (August 15th 2003, Inter Press Service).Therefore, what is necessary to keep in mind and clearly say is that clearly formulated conclusion may rarely be seen in the scientific papers that THERE IS NOT SCIENTIFICALLY CONFIRMED DIRECT LINK BETWEEN GLOBAL WARMING AND METEOROLOGICAL CONDITIONS WITH FIRES. Thus, we should not disregard, as it has already been emphasized, there are opposite and severely opposing opinions regarding global warming or perhaps to say more precisely regional climate changes. In other words, the presented mutually opposing results convincingly speak of how much our notions are limited viewing climate changes, but also of the insufficiently clear interaction of meteorological i.e. climate elements and forest fires the causes of which are not determined.

14


Long droughts, high temperatures, vegetation, terrain configuration, lightning and similarly may most probably in certain conditions cause and dictate the conditions of the forest fires development. “At especially dry locations, summertime blocking events can lead to increases in area burned even in the absence of antecedent drought. At particularly xeric location summertime cyclones can also lead to increased area burned, probably due to dry lightning storms that bring ignition and strong winds but little precipitation” (Gedalof et al., 2005). McKenzie, Gedalof et al., (2004) for example, with high responsibility state that above all: “Although associations between fire and quasi-periodic patterns (PDO13 and ENSO) have been identified, we have little understanding of how these indices will respond to climate warming. Thus, our ability to extrapolate these latter associations into the future is poor. ...The 10-yr running means of PDSI14 and percentage scarred are correlated (r = -0.375, p < 0.001) during the period of record (1684-1978). Prior to 1901, the 10-yr running means of PDSI and percentage scarred are more strongly correlated (r = -0.577, p < 0.001), indicating that the relationship between fire and climate in the 20th century is weaker than in the previous two centuries”. Shubert et al., (2004) point that there is correlative link of lowfrequent precipitation variation in Great Valley (USA) with the variation in Pan-Pacific part of SST15. The link is not always direct one, but noticed regularities point to the directions that should be further advanced. The mentioned authors used simulation grid point NSIPP-1 AGCM model. Every paragraph of the paper bears seriousness and professionalism. Acknowledgement the authors deserve is greater since they were also able to treat their results critically. “While SST force a global-scale response in the height field that is generally consistent with the precipitation changes over the Great Plains (including heights during pluvial conditions and enhanced heights during drought conditions), the exact mechanism by which the precipitation is impacted (in terms of changes in the storm tracks, suppressed rising motion, and changes in moisture transport) has not been established”. It is also said in the next paragraph that: “It is not clear, for example, why the model generates consistently dry conditions during the 1930s, but not during the 1950s when the pan-Pacific SST pattern has a sign and amplitude that is similar to that of the 1930s”. McKenzie, Hessl et al., (2004) showed that certain quantitative connection between fires and drought periods do exist in eastern Washington, as well as quasi-periodical connection with ENSO (3-7 years periodically) and PDO (20-30 years periodically). Let us mention one more interesting example about the results of the link between drought and fire. “An important article appeared in the literature recently with some surprising results given the predictions of the climate models. Andreadis and Lettenmaier have published a paper in Geophysical Research Letters entitled “Trends in 20th century drought over the continental United States,” and the results are peculiar — in light of climate model projections — to say the least. In the abstract, they write “Droughts have, for the most part, become shorter, less frequent, and cover a small portion of the country over the last century”. ...So, what is the relationship between drought in the western U.S. and global warming? There isn’t any. Statistically speaking, the correlation zero, which means, as 13

Pacific Decadal Oscillation Palmer Drought Severity Index 15 Sea Surface Temperature 14


15

humans have warmed the planet, they haven’t influenced western drought. This lack of a relationship holds whether one starts at the beginning of the Palmer record, which is 1895, or the starting year for Westerling’s study, which is 1970. ...Seen as we have had about a hundred years of global warming, about half of which is “natural” and the other half caused by people. The fact that there is no relationship between global temperature and western drought should be reassuring, especially because the relationship between drought and fire is quite real.”. (http://www.worldclimatereport.com/index.php/2006/07/). The essence of this concise survey of different opinions in the field of climate variability refers to the fact that we cannot claim with certainty what weather circumstances we are expecting even after a week, not to mention longer temporal intervals. “It is hard to predict accurately where and how much rain will fall next week. It is harder still to forecast next year's rainfall patterns” (http://earthobservatory.nasa.gov/Study/NAmerDrought/NAmer_drought.html). There are more and more texts showing helplessness of the contemporary science to predict climate changes that follow. “Land-use and water-use by humans; large-scale atmospheric circulation changes caused by ocean temperatures; feedbacks between the land and atmosphere: they all play a role. Climatologists can't yet put these factors together to predict what will happen many years in advance. Next winter is mystery enough. Will it bring much snow and relief? No one knows”. (http://science.nasa.gov/headlines/y2004/21may_drought.htm?friend%20). We get an impression that just because of that on September 14th 2006. ESA put the following as the strategic goal, i.e. task: -

-

-

“Quantify, as completely as possible, the Sun-induced climate oscillations on Earth, affecting its atmospheric circulations, air and sea temperature, global water and energy circulation, radiation balance including effects of clouds, global vegetation patterns, etc.; Resolve, as far as possible, the causes and effects of the observed variability in the physics of the Earth system, attempting to identify key primary parameters governing the Sun-induced oscillations; Elaborate hypotheses on the mechanisms of Sun-Earth connection, gathering as much evidence as possible; Attempt to discuss quantitatively through extrapolation of the result obtained in this study, how much of the recently observed global warming can be attributed to the Sun’s increasing activity in contrast to the part possibly caused by anthropogenic activities” (http://esamultimedia.esa.int/docs/gsp/EO_2005-2006.ppt).

We may ask ourselves whether there is any sense to plan any activities, according to the projections of climate changes in the following 50 or 100 years. Document signing referring to reduced emission of the atmosphere polluters should certainly be supported. Anti cyclonic weather conditions, especially over industrial areas and urban areas in valleys, in combination with toxic polluters of the atmosphere, certainly influence man’s health as well as climate changes of the area. However, we have seen many results on the previous pages suggesting us that the change of the connection between the Sun and Earth has stronger influence on climate changes than the contemporary anthropogenic activity is. In order not to come to

16


wrong interpretation, it is necessary to emphasize once again that one of the main messages of this book is the necessity of reducing the emission of harmful material in the atmosphere, disregarding our views on global or regional climate changes and whether we agree or not on the influence of the processes on the Sun, meteorological and climate conditions, anthropogenic activity or any other factors on the forest fire phenomenon.

2. What Is Missing in the Explanation of the Sun-Atmosphere Connection? During the last few years several papers have appeared working on the influence of the cosmic radiation and Sun to certain meteorological, i.e. climate elements from different aspects. Schuurmans (1991) reported that after solar proton events a decrease of the atmospheric temperature (about 1.4°C) was observed at altitudes between 5.5 and 11.7 km during 10 days. This effect is apparently followed by the development of clouds and aerosols. “There has been more controversy about other parameters such as the open solar flux from the Sun, the geomagnetic aa index and the galactic cosmic ray (GCR) flux, which varies inversely with solar activity” (Kristjansson et al., 2004). The results Shnidell et al., (1999) have come to are also interesting: “Solar cycle variability may therefore play a significant role in regional surface temperatures, even though its influence on the global mean surface temperature is small (0.07 K for December-February). The radiative forcing of the solar cycle, resulting from both irradiance changes and the impact of greenhouse trapping by the additional ozone, is also small (0.2 W m-2 for December-February)”. Contrary to ‘conservative’ ideas we get an impression the scientists are more and more turning toward the Sun. Landscheidt (2003 a) gives detailed list of papers where the link Sunatmospheric processes is being proved: “The empirical relationship, presented here, would have a practical value even if there were no theoretical background. Many practices in meteorology are on this heuristic level. Yet there are hundreds of observations which show that within a few days after energetic solar eruptions (flares, coronal mass ejections, and eruptive prominences)16 there are diverse meteorological responses of considerable strength (Balachandran et al., 1999; Bossolasco et al., 1973; Bucha, 1983; Cliver et al., 1998; Egorova et al., 2000; Haigh, 1996; Herman and Goldberg, 1978; Landscheidt, 1983-2003; Lockwood et al., 1999; Neubauer, 1983; Markson and Muir, 1980; Palle, Bago and Butler, 2000; Prohaska and Willett, 1983; Reiter, 1983; Scherhag, 1952; Schuurmans, 1979; Shindell et al., 1999; Sykora et al., 2000; Yu, 2002).” Having in mind the weather circumstances reflect the other physical-geographic processes, the results of Mauas, Flamenco (2005) do not surprise: “...that there is a very strong direct correlation between solar activity, as expressed by the yearly Sunspot Number, and the stream flow of Parana river, in intermediate, interdecadal, scales. This correlation implies that wetter conditions in this region coincide with periods of

16

Prominences are magnetic fields of very hot gas having a shape of an arch (noose, knot), captured inside. Sometimes, when fields become unstable, they are erupting and arise from the Sun in just a few minutes or hours. If the eruptions are directed toward Earth they may cause significant auroras and other geomagnetic activities, translator’s note.


17

higher solar activity, in agreement with the paleoclimatic studies of the Asian monsoon mentioned above.” Supposition that the significant increase of the Solar flux came during the 20th century Lockwood et al., (1999) have researched, concluding that between 1964-1996 the increase of the total magnetic flux ejected from the Sun was 41% (± 13%).

Figure 8. The total solar magnetic flux emanating through the coronal source sphere Fs. Shown are the values derived from the geomagnetic aa data for 1868–1996 (black line bounding grey shading) and the values from the interplanetary observations for 1964–1996 (thick blue line). The variation of the annual means of the sunspot number ‹R› is shown by the area shaded purple and varies between 0 and a peak of 190 for solar cycle 19 (Lockwood et al., 1999)

Previously mentioned author emphasizes in the same paper not only that there is a strong link between the solar magnetic field and spots (figure 8) but that: “The variation found here stresses the importance of understanding the connections between the Sun’s output and its magnetic field and between terrestrial global cloud cover, cosmic ray fluxes and the heliospheric field”. The estimate for making conclusion was obtained on the basis of the equation: Fs = (1/2)4πR02B0 = 2πr2Br = 2πr2sBBsw17 Shaviv (2005) has concluded that “…increased solar luminosity and reduced CRF over the previous century should have contributed a warming of 0.47 ± 0.19°K, while the rest should be mainly attributed to anthropogenic causes. Without any effect of cosmic rays, the increase in solar luminosity would correspond to an increased temperature of 0.16 ± 0.04°K”. The rest, attributed the anthropogenic causes is 0.13 ± 0.33K. Thus, according this author the 17

B0 is the coronal source field at Ro from the centre of the Sun, Bsw is the IMF magnitude, where r = 1 AU for observations near Earth. The factor of one-half arises because half the field threading the source surface is inward, the other half outward, Br observed annual means of the IMF radial component for 1964–96, Br = sBBsw

18


cosmic radiation influence in relation to solar one is at least twice as larger as regarding air temperature increase on Earth. Even in the extreme variant, according this author, the temperature increase attributed to anthropogenic activities is a little lower than cosmic and solar influence. Kristjansson et al. (2004), Svensmark, Friis-Christensen (1997), Marsh, Svensmark (2000), Udelhofen, Cess (2001), Kristjansson et al. (2002), Usoskin et al.(2004), Palle (2005), Zherebtsov et al. (2005) and many others wrote on the link of the cosmic radiation (also including the solar one) and global i.e. regional cloudiness. According Tinsley, Yu (2004) “there is no decisive result at present to determine how much of the observed decadal variations are due to particle flux inputs as compared to total or spectral irradiance changes. However, there is no such ambiguity concerning the correlations of atmospheric dynamics with particle fluxes on the day-to-day timescale.” Perhaps these words illustrate best the notions they have come to: “Although a detailed physical model quantifying this connection is still missing, correlation studies support its validity” (Usoskin et al., 2004). McGuffie, Henderson-Sellers (1997) had similar confusions: “The situation is still further complicated by the lack of understanding of how the radiative properties of clouds may change. The size of the droplets in a cloud has an important influence on how the clouds interact with the radiation, and the amount of water in the clouds also changes the way the clouds interact with radiation. Clouds with larger drops have a lower albedo than clouds composed of smaller drops but with the same amount of liquid water must account for the competing effects of changing drop size and liquid water path which will ultimately affect the nature of the interaction with the solar and terrestrial radiation streams.” However, Sun, Bradly (2004) thought differently: “This reply thus further confirms our earlier conclusion that there is a lack of evidence to support the GCR-cloud hypothesis.” Above all mentioned, Litensten, Bornarel (2006) still have suggested that: “It seems that cosmic radiation favors the formation of nucleation cores in the lower atmosphere, on which droplets of water can condense, giving rise to clouds. The physico-chemical process is still not well understood, but measurements taken during the last solar cycle showed that on a planetary scale nebulosity is higher during a period of low solar activity than during a period of high activity, probably owing to this process. …A whole field of geophysics remains to be pioneered.” If there are already strong indications (in most of presented papers) referring to the connection of the solar and/or cosmic radiation with cloudiness phenomenon, we may ask whether it means the precipitation is also predisposed by influences from outside? The justification of such ‘heretic’ question is based on the fact that high precipitations (rain, snow, hail) may only occur from cloud. In that sense, the paper Bhattacharyya, Narasimha (2005) wrote seemed shockingly: “Using wavelet techniques it is also found that the power in the 816 years band during the period of higher solar activity is higher in 6 of the 7 rainfall time series, at confidence levels exceeding 99.99 %. These results support existence of connections between Indian rainfall and solar activity.” That certain predispositions do exist between the processes on the Sun and not only those climate elements which were mentioned, Mukherjee (2006) has also shown: “It may be noted that the sudden snowfall on the northern hemisphere continents on the 25th of December, 2004 has sufficient bearing on Star-Sun-Earth’s atmosphere interaction.” Habbal, Woo (2004) consider that: “The combination of solar wind dynamic pressure and magnetic reconnection leads to the formation of the tear-drop shaped magnetosphere, and the


19

entry of solar energetic particles into the Earth’s ionosphere”. According Stevancevic’s (2004, 2006), heliocentric hypothesis, electromagnetic waves coming us from the Sun, seize air masses by hydrodynamic pressure (after penetration through magnetosphere) directly causing moving and weather circumstance changes of certain region. If moisture saturation exists in the touching zone of different air masses, and depending also on the solar wind (SW) characteristics, then both clouds and precipitation may appear. The mechanism of the precipitation formation was explained by the principle of electron valence. Thus not only the cloudiness and precipitation phenomena but the phenomenon of hot waves and dry periods are first of all caused by electromagnetic characteristics of SW, location wherefrom it is ejected from the Sun and its chemical structure. Depending on the mentioned parameters, i.e. their combinations, the atmospheric processes of certain regions will also be dependant on. Landschieidt (2000 a) thought similarly: “The strongest contributors to the solar wind intensity are energetic solar eruptions (coronal mass ejections, flares, and eruptive prominences) which create the highest velocities in the solar wind and shock waves that compress and intensify magnetic fields in the solar wind plasma. Coronal holes have a similar effect. So it suggests itself to investigate whether periods of strong plasma ejections on the Sun are connected with temperature on Earth. Not all strong eruptions have an impact on the near - Earth environment. The effect at Earth depends on the heliographic position of the eruptions and conditions in interplanetary space. Indices of geomagnetic disturbances measure the response to those eruptions that actually affect the Earth.” Whether the interactive link exists or not, this is no more the question for Palamara, Bryant (2004): “The crucial question now relates to how solar/geomagnetic activity is coupled to the lower atmosphere.” The findings of Baliunas, Soon (2000) have also confirmed the hypothesis that besides active regions, coronary holes play an extremely important role on the processes in the lower parts of troposphere: “The temperature of the lower troposphere measured by Microwave Sounder Units (MSUs) aboard NOAA-NASA satellites has been recorded since 1979. Along with the MSU temperature curve is plotted the changing area of the Sun covered by the coronal holes the open magnetic field regions, from which high-speed particles flow. The changing flow of high-speed particles from the Sun, represented by the increase and decrease of the Sun's surface area covered by coronal holes, corresponds well with the warming and cooling of the lower troposphere.” On the basis of the recent exchange of opinions with colleagues who treat this problem similarly, the idea on the particle penetration from the Sun (and Cosmos) to the Earth’s surface turned out to be hardly accepted. However, there are sources clearly pointing out this still occurs “When cosmic rays hit Earth's upper atmosphere, they produce a shower of secondary particles that can reach the ground”. (http://science.nasa.gov/headlines/y2005/07oct_afraid.htm). According Hebera: “In other words, the particles were capable of tunneling all the way through Earth’s atmosphere to reach the ground”. (http://science.nasa.gov/headlines/y2007/22feb_nosafeplace.htm). Let us mention one more example: “The most intense burst of solar radiation in five decades accompanied a large solar flare on January 20, 2005 shaking space weather theory and highlighting the need for new forecasting techniques. The solar flare occurred at 2 a.m. ET, tripping radiation monitors all over the planet and scrambling detectors on spacecraft within minutes. It was an extreme example of a flare with radiation storms that arrive too

20


quickly to warn future interplanetary astronauts. …Normally it takes two or more hours for a dangerous proton shower to reach maximum intensity at Earth after a solar flare, but the particles from the January 20 flare peaked about 15 minutes after the first sign. …The event also shakes current theory about the origin of proton storms at Earth. Since about 1990, we've believed that proton storms at Earth are caused by shock waves in the inner solar system as coronal mass ejections plow through interplanetary space. But the protons from this event may have come from the Sun itself, which is very confusing" (http://www.nasa.gov/centers/goddard/earthandsun/solar_fireworks.html#bctop). SW represents in fact the output flux of the solar particles and magnetic fields that are spreading as interplanetary front. “Тhe sun's magnetic field is generated by dynamo action, though the details are still not entirely understood. …The Sun's energy output varies on time scales ...and takes two principal forms: electromagnetic radiation and the emission of charged particles” (http://umbra.nascom.nasa.gov/spd/secr/). Analyzing the case from November 2000 Lockwood et al. (2003) have concluded, on the basis of data from two satellites (ACE and WIND), the similar but not identical variations of interplanetary magnetic field may be observed. At strong eruptions SW also brings highly energetic particles- nucleons, the energy of which is measured in millions of electron volt. The quotation that follows may seem very long, but due to significance of the contents, it has been decided to present it on the whole. “Solar/cosmic ray forcing of global climatic change, as may be inferred from the above records, is controversial among physicists and climatologists. Attempting to explain a physical link on the basis of the relationship ‘solar wind-magnetosphere-ionosphere-atmosphere’ is difficult because of a very large difference of the solar wind energy and the energy of the atmospheric processes (4 orders of magnitude). Thus, it is necessary to develop another approach in the problem solution: the solar irradiance remains the main source of the energy affecting the atmosphere, but some agents controlled by solar activity must act directly on the atmosphere and change the amount of the solar energy reaching the Earth surface. Clearly a positive feedback mechanism is needed, explaining how relatively small variations in solar activity can cause significant climate changes” (van Geel et al., 1999). Landschieidt (2000 a) states: “Willis (1976) has calculated that the solar wind energy flux is less than one millionth of the Sun's electromagnetic power deposited near Earth. However, this estimation is based on the total cross-sectional area of the globe. It does not take into account that the solar wind energy may preferentially penetrate into areas smaller than the total disk where it can dominate other energy sources. Herman and Goldberg (1978) have shown that the solar wind energy concentrates on a narrow circumpolar latitude belt near the auroral zone. Taking additionally into account the slant incidence of the Sun's radiant flux, they calculated that the available power of the solar wind would reach 20% of the Sun's electromagnetic energy flux. If Svensmark could show in detail in his laboratory experiments, planned in cooperation with CERN, how galactic cosmic rays, regulated by the solar wind, affect cloud development, we would even have to concede that the energy of starlight is sufficient to affect climate. Cosmic rays and starlight inject nearly the same amount of energy into the atmosphere.” Disregarding lack of detailed knowledge of the mechanism of interactive connection Ponyavin et al., (2005) emphasize that with usage of certain techniques, connections may be confirmed. “Historical sunspot and climate records were analyzed by means of nonlinear tools to study long-term trends and relationships with the solar activity variations. Cross Wavelet technique and Recurrence Plot analysis were applied to the data (for annual averages


21

of air-surface temperature in Central England, Stockholm and St.Petersburg) to find their similarities and phase coherence at different time and time-scale. ...The second half of 20th century demonstrates unusual response of climatic system to the solar signal.” Russian scientists also noticed the connection of the regional changes regarding some climate elements and forest fires on one side and processes occurring on the Sun on the other side. “This is similar to behavior of cloudiness in Europe depending on solar activity and it explained by displacement of southern and northern paths of western Atlantic cyclones with increase of solar activity to the middle latitudes” (http://www.ans.kiruna.se/meetings/comaar/pdf/V_Solovyev.pdf). According Stevancevic (2004, 2006), the key explanation of the mentioned causativeeffective link is vector circulation of the interplanetary magnetic fields (IMF). If the Bz component of the IMF has negative sign, in relation to Earth’s magnetosphere field, it comes to their linking up i.e. reconnection (in areas above north and south pole). Otherwise, it may come to the rejection and then principally SW does not reach air masses. It is interesting that even regarding SW ejection from the Sun, the magnetic field vector more and more gains on importance. Wang (2005) says: “Without the detailed knowledge about the vector magnetic fields in the photosphere, the coronal heating and activity can not be properly understood.” Nevertheless, it may be concluded the Earth’s magnetic shield does not present such a powerful defensive mechanism of our planet, as it has been believed recently. “The cracks were detected before but researchers now know they can remain open for long periods, rather than opening and closing for just very brief intervals. This new discovery about how the Earth's magnetic shield is breached is expected to help space physicists give better estimates of the effects of severe space weather”18. For the first time, as far as we know, Stevancevic indicated that even forest fires (the causes of which are not officially determined) may directly depend on the mentioned predispositions19. “First larger opening of the magnetic field occurred in February 2002, in Siberia when it came to greater forest ignition. Immediately after that, in the period from 2nd4th of March the Solar Wind reached the borders of our country starting a series of fires in the vicinity of the towns of Bor and Zajecar” (Stevancevic, 2004). In that respect, it seems that a significant step forward was made regarding the notions Auclair (1992) came to, whose results have shown the areas under forest fires are larger (North America) when the Sun is more active.

18 19

(http://www.nasa.gov/centers/goddard/news/topstory/2003/1203image_cluster.html) PhD M. Flannigan suggested that there are similar researches: “Check for Vines (an Australian - think it was Neil but may be wrong on the first name)”. However, all the efforts to come to the researching results of this author were unsuccessful.

Table 1. Total number of forest fires (1) and fire seized surfaces (2) in Europe for period 1991-2001 (according to FAO, 2002)20 year 1 2 (ha)

1991 56490 585774

1992 79058 462100

1993 69588 488236

1994 77771 804814

1995 85107 435517

1996 87580 296510

1997 92526 364824

1998 120742 707920

1999 118263 362704

2000 140316 928416

2001 106692 463186

Table 2. Total number of forest fires for Europe and South European countries for period 1991-201 (according to FAO, 2002)

Europa South Europa

20

1991 56490 45779

1992 79058 57150

1993 69588 56811

1994 77771 61117

1995 85107 72675

1996 87580 66419

1997 92526 71232

1998 120742 86895

1999 118263 70613

Within these data Moldavia, Ukraine, Belarus and Russia are not included while the data for Turkey and Israel are included

2000 140316 95484

2001 106692 65881

Σ 1034133 750057


23

Table 3. Number of forest fires of known (1-3) and unknown (4-6) causes per European countries for period 1999-2002 (according to FAO, 2002)

Country Armenia Belarus Belgium Bulgaria Croatia Cyprus Czech Rep. Denmark Estonia France Germany Greece Kazakhstan Latvia Lithuania Norway Poland Portugal Romania Russian Federation Serbia & Montenegro Slovakia Slovenia Spain Sweden Switzerland The f.Y.R. of Macedonia Turkey Ukraine

1 1999 15 2876 8 93 94 9 921 ... 116 1599 675 ... 96 1196 966 32 8994 ... 81 28300 190 ... 27 14560 ... 30 12 1633 6055

2 2000 35 1705 403 187 205 959 ... 105 1341 681 ... 122 915 619 22 11187 ... 448 16200 115 787 53 20084 ... 53 42 1926 3683

3 2001 ... ... 3 206 ... 210 ... 4 ... 1995 680 660 ... ... 278 ... ... 957 ... ... 149 ... ... 12251 2924 ... ... 2068 3187

4 1999 1083 8 227 129 11 482 ... 14 3353 503 ... 850 56 116 23655 ... 58 3400 74 ... 26 3677 ... 11 48 442 15

5 2000 864 1 1307 519 80 540 ... 53 4401 529 ... 815 35 75 20445 ... 240 2600 224 37 45 4033 ... 140 427 13

6 2001 ... ... 1 619 ... 89 ... 4 ... 2262 352 1998 ... ... 9 ... ... 25943 ... ... 137 ... ... 6846 1850 ... ... 563 18

3. Why Do Forest Fires Appear According to the data of FAO (2000) we may notice the total number of the forest fires in Europe with certain deviations as well as surfaces which they seize is considerably increasing (table 1). Observed in such a way, certain analogy with the sudden air temperature increase is noticed especially in the last decade of the 20th century. From the presented table we can see the largest number of the fires was noted in 2000 (140316) and we can also notice that then

24


the largest fire seized surfaces were in Europe (928416). According to incomplete data of the Global Forest Resources Assessment 200521 the average annual surface of the fire seized forests in 1998-2002 was 1597000 ha in Europe. The data (table 2) are especially interesting pointing the greatest number of the fires appears in the Mediterranean zone. No matter how much it has seemed to us we live in the period of the sudden development of science and technologies, the facts are inexorable and they really show how much we are helpless to perceive clearly what such large number of fires is caused by. Thus, overtaking suitable measures of the protection looks more like “wandering through fog”. Absolute values from the table 3 showed that the greatest number of the forest fires of known cause was noted in Russia in 1999 (28300) and Spain in 2000 (20084), while the fires of unknown cause were the most numerous in Portugal in 2001 (25943) and Poland in 1999 (23655). The data relating to Poland are especially significant. Namely, in 1999 the number of the forest fires of known cause was about 2.5 times less in relation to those of unknown cause. The next year the number of the established causes little increased in relation to unknown ones. It has seemed the situation in forestry drastically improved in Poland the following year so that according to the recent data “unknown causes varied about levels of 7 % to 8 %” for 2005 (http://www.fire.uni-freiburg.de/programmes/eu-comission/EU-ForestFires-in-Europe-2005.pdf). Nevertheless, according to the same source almost incredible 70 455 fires were noted in this country in 2003. It may seem almost impossible to understand any spatial connection, whether it is about occurrences with known or unknown cause; even if we keep in mind all lacks of gathering and data processing. It is noticeable the data for Russia are also missing in the table 4, so the significance of this table considerably lessens. Still, we may notice that as for the surfaces burnt without established cause, Portugal is in the first place (75727 ha in 2001) while Spain bears the first position as for known causes (168163 ha in 2000). Regarding the concrete indexes for Europe, it is important to point out there are little different data: “Since 1985, the average size of burnt surface areas has diminished. However the increase in the number of fires still remains a concern, which shows the importance of an improved struggle against the causes of fires, all the more so in Europe because 53% of the fires remain of an unknown origin.” On one side, we may conclude from the previous source that the fire seized surfaces show decrease during certain temporal period, but on the other one, the domination of the cases of unknown cause is especially fully expressed: 40% in period 1950-1991. (table 5) and 53% from 1985 Let us remember that Nikolov (2006) also stated similar values for the Balkans, i.e. according to this author 37.9% are fires of unknown cause. In lack of the rational explanation we can often find the comments relating to the unclear influence of the weather circumstances: “During the last few years an increase of fire danger and elevated number of fires and area burned have been observed in Poland as a consequence of more frequent occurrence of extreme fire weather conditions during the fire season. These weather conditions that were uncommon in earlier years are accompanied by rapid changes of atmospheric fronts. Moreover, regional climate warming, associated with increasing

21

Chapter 4, Forest health and vitality


25

Table 4. Forest fire seized surfaces (ha) of known (1-3) and unknown (4-6) causes per European countries for period 1999-2001 (according to FAO, 2002)

Country Armenia Belgium Bulgaria Croatia Cyprus Czech Rep. Estonia France Germany Greece Kazakhstan Latvia Lithuania Portugal Romania Serbia & Montenegro Slovenia Spain Sweden Switzerland The FYR. of Macedonia Turkey

1 1999 53 1 6170 3645 1 213 1056 7914 247 ... 7718 1544 480 ... 221 701 192 70682 ... 18 142 4865

2 2000 43 15320 12208 1342 207 683 17456 296 ... 9443 1341 340 ... 2308 2670 219 168163 ... 42 1380 23601

3 2001 ... 1 ... 1891 ... ... 10926 84 4376 ... ... 110 36108 ... 1433 ... 46055 1071 ... ... 5632

4 1999 1 2121 2408 2 123 47 7950 168 ... 18783 14 ... 161 1094 241 11537 ... 4 1687 939

5 2000 0 42086 55958 6693 168 1 3003 285 ... 18044 12 ... 1299 5305 46 18863 ... 24 12289 2752

6 2001 ... 0 ... ... 2939 ... ... 9543 38 13966 ... ... 2 75727 ... 2025 ... 46331 182 ... ... 1762

Table 5. Fire origin in “Landes Forest” from 1950 to 1991 was as following: (http://www.feudeforet.org/english/forets_europe.htm#haut): Unknown Lightning Carelessness Accident Starting up again of fires Others

40 % 29.7 % 11.5% 9.6 % 3% 5.3 %

occurrence of relatively warm and snowless winters have also contributed to prolongation of the fire season. Thus, winter and autumn months are no longer considered free of fire risk. The year 1999 is an example when the maximum of fires (2106) was observed in September. Compared with the period 1990-1998 this number is equivalent to an increase of September fires of more than ten times, contributing to more than a fourth of the total number of yearly fires” (Ubysz, Szczygiel, 2002). Applying HIGRAD/FIRETEC computer model, the numerical simulation has shown that wind, locally, does not always cause fire spreading in the suitable direction. “In all simulations, the magnitude of the convective heat transfer is greater than that of the radiative heat transfer; however, these processes and their relationships to the three-dimensional

26


structure and evolution of the fire are shown to depend both on the ambient wind speed and on the specific location along the fire front (e.g., at the head of the fire where the fire is spreading in the direction of the ambient wind, or on the flank of the fire where the fire is spreading in the direction almost perpendicular to the ambient wind)” (Linn, 2007). The local wind influence certainly plays an important role in the fire spreading. However, it is necessary to point out the question of side spreading of the fire, which advances almost under the right angle in relation to air circulation. Having in mind that satisfying explanation on the influence of any climate element (or a combination) to the initial phase of the fire phenomenon has not been given in 40% of the cases then it is the question of appropriateness of the models, which in the first place base the prediction of the variations of these catastrophes according to global warming. That is why the following statement does not surprise: “Thus, research on fire protection and control is challenging, and predictive tools for fire protection and control are often based substantially on expert opinion and anecdotes, rather than on documented research evidence” (Gorte, 2000). Quoting Boychuk and collaborators (1997), Ryu et al. (2004) have pointed that “The primary approach of landscape management is to maintain states of fuel loading similar to those that existed prior to European settlement to achieve sustainable ecosystem management. However, a substantial gap remains between the principles of fire accommodation and emulation and their application. A clear understanding of the relationships among fire, weather, fuel, and disturbance across scales is essential”. That it is about the impossibility of viewing the key aspects of the whole problem best confirms the quotation pointing the recent activities “only confirmed that the strategy followed until then did not solve the problem” (Gomes, 2006). However, decisive and clear stating of the existing condition is not always present in the scientific papers. Gonzalez et al. (2006) have claimed for example that beyond the fact fires are highly stochastic phenomenon, their model and its parameters are significant and the testing results are consistent, i.e. as such they may be used in practice. In that sense Landscheidt (2003a) is categorical: “Anyway, the correct forecast of the U. S. drought beginning in 1999 and a dozen of further successful climate forecasts, exclusively based on solar activity, show already now that the IPCC’s claim that there has only been a negligible solar effect on climate change in recent decades is not tenable. Ironically, just drought, the greatest threat attributed to alleged man-made global warming, has turned out to be regulated by variations in the sun’s eruptional activity”. Nevertheless, it is useful to mention that even in such circumstances there are certain attempts of the long-term prognosticating. Brown et al. (2004) have done the projection models of the fires for the western USA for periods 2010-2029, 2030-2049, 2050-2069 and 2070-2089. Special significance was given to the temperature increase, especially to relative air humidity. Flannigan claims that forest fires during 2003 were “glimpse of what the future will be like” and that “we can expect more severe fire seasons in the future”. …Continued warming will produce greater seasonal contrasts which, combined with an expected 44 % increase in lightning strikes, is expected to increase the area burned by 78 % in the next 50 years. (http://www.davidsuzuki.org/Forests/Forests_101/FIRE/Climate_Change.asp). Previously mentioned author admits that the connection is not quite clear, but depending on the climate disturbances the fire frequency may also depend: “Although both the number of fires and area burned have increased over the past 40 years, we cannot detect consistent


27

trends in weather indices associated with these large fires. However, we do expect that a changing climate will make fire weather conditions more severe, resulting in an increase in area burned in the future” (Flannigan et al. 2002). On the basis of available literature it is necessary to point out the following: even above all mentioned here, the prevailing opinion both in public and scientific circles is based on: a) the supposition the forest fires are mostly the consequence of the intentional or unintentional man’s activity. Under this it is also meant on direct influence of the greenhouse effect (global warming) to the development of the weather conditions, as well as to accidentally or intentionally caused fires; b) the supposition that lightning is the most frequent cause of fires in the sub polar areas. In distant, unsettled areas, if there was not any lightning the cause of fire has automatically been attributed to irresponsible men’s behavior, because it seemed that simply there has not been other explanation. “The relationship between lightning characteristics and ignition probability is incompletely understood, and not all strikes have characteristics required to initiate a fire …A long continuous current cannot be detected with current technology, and not all lightning strikes are recorded …There was no evidence to suggest the location of lightning detectors …influenced lightning indices …We must consider that initiation patterns (and fire regimes) change over long time scales (e.g. multiple disturbances) and reflect the intrinsic stochasticity of mixedwood boreal stand development …In Alberta, mature pine is considered a “go, no-go” fuel type (assuming ladder fuels such as a spruce understory are not present) where fire behavior is considered low except under strong winds …Initiation was not sensitive to the amount of open (e.g. muskeg) area in a landscape” (Krawchuk et al. 2006). Perhaps it may be useful to mention for the sake of the reading public the typical sub polar climate where Alberta lies, characterizes long cold winters and short cold summers. Besides, Farr et al. (2004) quoting Andison (2003), point out that the forest fires do not have progressive growth in all the regions. Concerning Alberta “Historical records suggest that prior to 1950, fires were more frequent ...burning at least 1 % of the forest per year. It is possible that fire suppression during the past few decades has reduced the incidence of fire in the study area. Alternatively, recent weather and fuel conditions may have been less conducive to fire than several decades ago.” The attempts of modeling the impacts of the electric discharge in the atmosphere on fires left modest also, simply because there are still many unknowns in that field: “Beyond its powerful beauty, lightning presents science with one of its greatest local mysteries: How does it work? It is common knowledge that lightning is generated in electrically charged storm systems, but the method of cloud charging still remains elusive. (http://science.howstuffworks.com/lightning.htm). Anyway, when it is about lightning affecting the vegetation, it is necessary to have in mind already mentioned conclusion it is mostly followed by precipitation (Kourtz, Todd, 1991). It is obvious the precipitation quantity, first of all in such situations defines whether fire would spread over or it would be extinguished. It seems the lack of more detailed studies on this theme does not offer the strong enough support to understand the questions to what extent electric discharges participate in the initial phase of the fire phenomenon.

28


It is founded that: “From 1990 to 1998, over 17000 naturally ignited wildfires were observed in Arizona and New Mexico on US federal land during the fire season of April through October. Lightning strikes associated with these fires accounted for less than 0.35 % of all recorded cloud-to-ground lightning strikes that occurred during the fire season during that time. Natural wildfire ignitions in this region are often attributed to what is referred to as ‘dry’ lightning, or lightning with little or no precipitation” (Hall, 2007). Citing the results of the National Interagency Fire Centre, Rowell, Moore (2000) have pointed out that“ for 1997 for North America three quarters of the land burned – 76 % - was due to lightning.” Beside different temporal intervals of data processing, the ranges of impacts of lightening on forest burning are at least contradictory. An English oak more than hundred years old is one of the tourist attractions of Kuman (northern Banat, Serbia). According to the local residents’ words it is remembered this still alive tree to be struck by lightning for seven times and it has never been burnt. It is clear that such examples cannot be used as proof that lightning is not the frequent cause of the forest fires. However, it is absolutely clear this is not an isolated case and all such examples rather fit into the results Hall (2007) has given.

4. Hypothesis on the Processes on the Sun as the Cause of Large Forest Fires The visual effect of the figure 9, suggests on the significant link between fires in south Europe (13 states-75% of fires) and total number of fires for the whole continent in period from 1991-2001. The estimate of the correlation coefficient (for table 6) has shown it is high 0.91 with the statistically significant level of confidence of over 99%. Disregarding the cases of known or unknown causes are about, the correlation coefficient points to their spatial and time link. However, the correlation link between series of data for south and the rest part of Europe is much lower: 0.64. In other words, the link which evidently does exist is much weaker than it could be concluded on the basis of integrated data. EUROPE Number of fires / Nombre d'incendies

160

Thousands / Milliers

140 120 100 80 60 40 20 0 1991

1992

1993

1994

1995

EUROPE

1996

1997

1998

1999

2000

2001

SOUTHERN EUROPE

SOUTHERN EUROPE / EUROPE MERIDIONALE: Albania, Bulgaria, Croata, Cyprus, France, Greece, Israel, Italy, Portugal, Slovenia, Spain, Serbia & Montenegro and Turkey .

Figure 9. Forest fires registered in Europe (total) and Southern Europe for period 1991-2001. (FAO UN, 2002)

Table 6. Comparative survey of the locations of forest fires in Europe recorded by satellite and the parameters of the highly energetic regions and SW that have immediately preceded them Date of Location recorded fires on Europe 23. 11. 2002

Caspian Lake

02. 03. 2003

Coronary Energetic hole region(s)

Max temperature of particles (°K 000)

Max radial speed of particles (km/s)

Max density of particles (p/cm3) during 3-4 days before the fires

Proton fluence Protons/cm2-day-sr >1 MeV

>10 MeV

>100 MeV

10091

Beta gamma delta

>1 000 000

800

54

2.0e+06

1.1e+04

10296

Gamma delta

600 000

630

20

6.1e+05

1.2e+04

10314

Beta gamma

960 000

870

23

5.5e+06

1.2e+04

2.8e+03

24. 07. 2003

Southwest CH 23 Russia Balkan, east CH 26 Europe Italy CH 49

2.9e+03 and 24. 11. 3.1e+03 2.9e+03

10410

500 000

575

7

1.5e+06

1.2e+04

2.7e+03

28. 07. 2003

France

CH 49

10422

>1 000 000

850

60

1.7e+06

Portugal

CH 55

10456

>1 000 000

770

10

1.7e+06

1.2e+04 and 29. 07. 1.3e+04 1.2e+04

2.7e+03

13. 09. 2003 28. 07. 2004

CH 106

10652

>1 000 000

968

54

2.7e+08

9.5e+06

3.1e+03

23. 08. 2004

Portugal, Spain Volga

CH 110

10661

400 000

550

11

5.8e+05

1.6e+04

3.8e+03

28. 07. 2005

Greece

CH 177

10792

Beta gamma delta Beta gamma delta Beta gamma delta Beta gamma delta Beta gamma delta Beta-gammadelta

500 000

635

23

03. 08. 2005 24. 08. 2005

Portugal Portugal

CH 198 CH 183

10792 S583

500 000 >1 000 000

630 800

56 33

1.2e+07 and rising till 01. 08 5.9e+07 5.9e+07 2.6e+08

2.2e+06, 29. 08 - 6.7e+03 2.8e+06 and 30. 08. - 2.3e+06 1.5e+06 4.9e+03 1.7e+07 1.1e+04

26. 03. 2003

CH NN

Magnetic structure

Beta gamma Beta delta

The data about the forest fires have been taken from Natural Hazards >> Fires >> NN- marking of the coronary holes starts from 2003: The data for coronary holes have been taken from http://www.dxlc.com/solar/index.html The parameters of the energetic regions have been taken from http://www.sel.noaa.gov/ace/ACErtsw_data.html The data for protons have been taken from http://umtof.umd.edu/pm/crn/ Term energetic region means the location on the Sun, containing certain number of spots, having different magnetic structures.

2.7e+03

30


Summing up the data, it was calculated that according the official data between 1999 and 2001. 116352 forest fires occurred in Europe for which the cause was not determined. Proceeding from these facts it was thought that the existing situation could not be explained by ‘classic’ methods, i.e. explanations. At one moment the idea has appeared to check the hypothesis Stevancevic (2004) stated. It was decided the establishing of the eventual time connection, i.e. causality between forest fires and eruptions on the Sun to be the test step. Necessary satellite data were united only for 10 cases, for period from November 2002 to August 2005. Since this as an ‘unusual’ research, it was suggested to check the same way whether similar had been happening with another fire on August 24th 2005 in Portugal. After successful attempt to have the data completed, in this eleventh example the noticed regularity was also confirmed. Further efforts to get to the information whether these 11 fires have any causes found were unsuccessful. At the very beginning it was clear that it would be impossible to make more detailed data base (certainly not large enough for statistically representative samples), but even on this level especially significant results have not been expected. However, it turned out similar situation on the Sun had preceded all the observed fires. Namely, immediately before the destructive power of fires, energetic regions were in geo effective position emitting strong electromagnetic waves toward the Earth, too. In all the cases, without exception, it was the energetic regions with coronary holes co effect about. Having in mind obvious lacks regarding the available data fund, the application of any statistical apparatus has appeared as significant problem. Because of that it has been tried to point out the justification of the approach based on time sequence of the occurrences. The particles’ velocities were of 550 km/s, while in some situations even over 1000 km/s. Presented temperatures are for proton, ion and nucleon SW particles. It is measured on 1.5 million km from the Earth while ACE satellites make the observations (http://www.sel.noaa.gov/ace/ACErtsw_data.html). Particle temperatures reached even over a million of °C in some situations. Under the SW velocities of e.g. about 800 km/s, we can estimate that highly energetic particles, having also high thermal temperature, arrived to Earth for about 45 minutes from the moment when the instruments had registered them. Suspicion the fires in northern piedmont area of Caucasus (figure 10) may be the possible consequence of the eventual terrorist actions, was eliminated by noticing several locations burning also on the southern slopes of the mountain. Let us mention that in the very same region many fires also occurred on March 2nd and March 31st 2003 (http://earthobservatory.nasa.gov/NaturalHazards/archive). This practically means the meteorological conditions in all three cases, in accordance with suitable part of the year, cannot cause the initial phase of fire. Persistent searching for the information whether the local population was preparing the terrain for working in the fields on both sides of the mountain by burning vegetation just at the end of November and at the beginning of February i.e., at the end of March, also left without results. It has been noticed that wider area around Caspian Lake has been fire seized relatively frequently in the last few years. With this example, as well as with all the rest examples from the previous table, a sudden proton energy rise in all ranges has always been registered immediately (mostly about 2 days) before fire breaking out (Figures 11 and 12). It is not possible to show recordings for all the cases due to limited scope of this monograph, but they certainly may be checked in corresponding sources.


31

Figure 10. Satellite recording of the fires at the utmost southeast of Europe on 23.11.2002. (http://earthobservatory.nasa.gov/NaturalHazards/Archive/Nov2002/SERussia.AMOA2002325_lrg.jpg)

Figure 11. Sudden proton energy rise at the beginning of 21. 11. 2002. (http://www.sel.noaa.gov/ace/ace_rtsw_data.html)

32


Figure 12. SW parameters were characterized by extremely high particle density, high velocity and temperature in the area of Caspian Lake immediately before fires (http://www.sel.noaa.gov/ace/ace_rtsw_data.html)

Reconsidering our own results, an idea occurred that perhaps certain geographic i.e. geophysical specification exists in Europe, which is not present on other continents or it is less prevailed. However, while surveying superficially, it has turned out that in other parts of our planet similar phenomena also exist as well as on Old Continent (figures 13 and 14).

Figure 13. The strongest flare on the Sun in the history of the satellite observations belonged to X28 class (http://sohowww.nascom.nasa.gov/hotshots/2003_11_04/c2.gif)


33

It is interesting that in period from October 18th to November 4th 2003. a series of extremely strong flares occurred on the Sun, unprecedented in the history of satellite measuring. Here is how media described occurrences in the USA those days: “The fires that blackened 775,000 acres and 2,400 homes in Southern California this October. ...The state has never seen a loss of this magnitude” (http://www.hcn.org/servlets/hcn.Article?article_id=14457). Eruption which occurred on November 4th that year belonged to X28 class and as such it was an absolute recorder according its strength (figure 13). It seems that our planet had luck since disregarding that ranges of electromagnetic waves were very high, the main emitting directions were directed out of earth’s orbit. We ask is the fire in India, in the foothill of the Himalaya (recorded on November 6th 2003, figure 14) in time coincidence with the strongest flare or is it something else about?

Figure 14. Tens of the locations were fire seized in the foothill of Himalaya two days after the strongest X28 flare (http://earthobservatory.nasa.gov/NaturalHazards/Archive/Oct2003/India.AMOA2003296_lrg.jp)

Citing D. Beker, Bond (2004) notices: ”We have never seen such a powerful enhancement and distortion of the radiation belts. From 1 to 10 November the outer belt had its centre only about 9 600 km from Earth’s equatorial surface. ...This is a place where ordinarily there are almost no energetic electrons at all.” Let us remind that on November 3rd 2003 many fires in New Guinea were detected, while on November 10th 2003 fires in Northern Brazil as well as in West Africa were also detected. Analyzing satellite recordings it follows that at the same time when X28 occurred, several energetic regions were in geo effective position (with 10467, 10495, S299 signs), as well as the coronary hole bearing CH 0065 sign (figure 15). In other words, it is similar as in all 11 cases. And again it comes to a sudden flux of electromagnetic waves (figure 16).

34


Figure 15. Recording of the coronary hole and energetic regions on the Sun day after Х28 (http://www.dxlc.com/solar/)

Figure 16. Sudden rise in proton energy at the end of October and the beginning of November 2003 was directed toward Earth in two waves (http://sec.noaa.gov/ace/SWEPAM_7d.html)

Fires in Australia, recorded in January 2005 also characterized similar analogy. “Firefighters tentatively contained a large wildfire in the mountains east of Perth on Jan. 20, 2005. This image shows the burned areas as well as still-burning portions of the fire.” (http://earthobservatory.nasa.gov/NaturalHazards/Archive/Jan2005/Australia4.AMOA200502 0_lrg.jpg). Those days, proton velocities exceeded measuring abilities of the instruments several times (figure 17).


35

Figure 17. From 12th-23rd of January values of proton’s velocities were several times above measuring abilities of instruments (http://umtof.umd.edu/pm/crn/)

It is important to emphasize the forest fires are not always preceded by the phenomenon of coronary holes and energetic regions which emit exclusively strong electromagnetic waves. There are some cases when danger from plant mass ignition still exists even under relatively weaker sources. The example could be the series of forest fires in Serbia in the period from March 13th-19th. The public was then informed that 18 fires were burning between Rudnik and Takovo, 10 ha (66 localities) fire seized in the vicinity of the town of Kragujevac (central Serbia), while in the surroundings of Leskovac (southeastern Serbia) fire seized 300 ha of forest. In the nearby of Svrljig (eastern Serbia) 16 fires were registered, while around 50 in the District of Rasina (five municipalities south from Krusevac toward Kosovo and Metohia). In Podgorina (surroundings of Valjevo), in the village of Vragocanica –small village of Stojkovic, according local residents’ words forest burned being ignited by a shining red ball which landed from the sky! D. Simic, a local resident, described the event: “It was about 18.00 hours when I saw fire burning in the forest, like a road cut through for about 100 meters long. It only burned by one side and the fire did not spread over. Above flame, there was one red firing band in the sky such as the depth of an arm is, resembling the white aerial trail. Nobody was passing by the forest, neither anybody do anything. I do not know what was it, but I am sure that the fire did not occur just like that.” In this case firemen rejected the possibility that eventually a meteor caused the ignition, because there was not crater from the fall of the meteor, although it was not possible to notice it at night. N. Bozic who is an astronomer in Petnica Researching Center near Valjevo said that it was possible the fall of the meteor had caused fire in Vregocanica, but only under certain circumstances. “While burning out in the atmosphere, meteor leaves a track in a shape of a tail. Theoretically, it may burn out

36


even one meter above land not making a crater, but causing the ignition. However, since it is a great velocity about, a sound effect must have been heard such as missile flying is and striking wave that would break treetops. If it had not happened, then meteor fall was not the fire cause.” S. Stojkovic, a local resident, does not also believe the clearing of the forest with fire may be the cause of the mentioned disaster. As he says, on Sundays (when mentioned fire occurred near Valjevo) no one worked in the village. (http://arhiva.glas-javnosti.co.yu/arhiva/2007/03/21/srpski/T07032002.shtml).

Figure 18. A day before the fires in Serbia, 10946 energetic region was recorded in the east of the Sun (in geo effective position), while at the same time electromagnetic waves from CH260 coronary hole were emitted toward Earth (http://www.dxlc.com/solar/)

Figure 19. Sudden flux of the SW highly energetic particles was especially registered in ranges of 1.83.3 and 3.3-6.4 MeV/n from 12th-16th of March 2007


37

Figure 20. Proton velocities were reaching the values of mostly over 600 km/s from 11th-16th of March 2007

Fires in Tasmania Fires triggered by lightning in February 2007 continued to burn in March. This image shows the fires on March 21. Event Date: 2007-03-21 00:00:00 Number of Images: 1 Topic: Fires Fires in the Southern United States Numerous fires were burning across the southern United States in early March 2007. This image shows the area on March 20, 2007. Event Date: 2007-03-07 00:00:00 Number of Images: 2 Topic: Fires Fires in Myanmar Hundreds of fires were burning in Myanmar and surrounding countries in March and April 2007. Event Date: 2007-03-02 00:00:00 Number of Images: 6 Topic: Fires

Figure 21. Fires in different parts of our planet at the time when relatively small fires occurred in Serbia

38


As it has already been mentioned the figures 18 to 20 as well as all cases cited before point to similar situations on the Sun before braking out of the forest fires. In relation to some previously mentioned cases, in this example it is relatively smaller fire about. However, by the inspection into available data, it turned out that during that period fire did not just seize the area of Serbia. The disaster was more expressed in the southern part of the USA and Myanmaris, while in Tasmania fires burned on relatively smaller number of the locations, but they lasted more than 20 days (figure 21). Notions on possible extreme values of SW parameters were probably insufficient in the time when satellite instruments had been constructed. How else explain the situations when instruments cannot record e.g. proton flux (figure 22) even during several days in a row. Let us remind that fires appeared in France (coastal area of the Mediterranean Sea) on July 28th 2003. Many cases, especially those after 2000., point to the necessity of expanding the measuring range of the instruments i.e. the possibility of measuring greater values of SW parameters than recently. Satellites detecting particle flux, measure in essence electric convection current which flows from the Sun and towards the Earth. Picturesque description of the cosmic radiation under extremely strong emissions Cowen (2001) presented: “2005 has been a surprisingly active year on the sun... Since January, astronomers have counted 14 powerful X-class solar flares and an even greater number of CMEs". (http://science.nasa.gov/headlines/y2005/07oct_afraid.htm).”

Figure 22. Values of proton velocities were exceeding measuring abilities of instruments at the beginning of 27. 07. 2003 in all days to 03. 08. 2003. An exception is 28. 07. (http://umtof.umd.edu/pm/crn/).


39

It is similar with the satellite data of the observation lasting of proton, electron, neutron flow, chemical structure, speed, temperature, intensity of convectional current, their vector direction, but which are being observed out of Earth’s magnetosphere. Many instruments, positioned for those purposes, stopped working just because of damage or complete destruction. The reason: -‘close encounter’ with electromagnetic waves of the cosmic (and/or solar) origin, of so high energies, the instruments of which obviously had not been adequately protected (Iucci et al., 2006). Strong flares also indicatively suggest the intensified solar activity may be brought into connection with increased number of fires in the last few years, as shown in Table 7. It is necessary to emphasize that according other sources five strongest flares relate the period after 2000 (http://umtof.umd.edu/pm/flare/5flares.gif). On the other side, not all strong flares were directed toward Earth. Table 7. Five strongest flares since 1976. (According http://www.spaceweather.com/solarflares/topflares.html) Ranking 1 2 2 3 4

Day/Month/Year 04/11/03 02/04/01 16/08/89 28/10/03 07/09/05

X-Ray Class X28 X20.0 X20.0 X17.2 X17

The hypothesis on the certain processes on the Sun, as possible causes of plant mass ignition, is based on the supposition that highly energetic particles, in certain conditions, penetrate to vegetation combustion material and by burning through, on the molecular level, they cause the initial phase of fire. If there are clouds, the particles of large energetic load have reduced possibilities of penetration to the topographic surface in places of the penetration in the atmosphere of our planet. By itself, in such circumstances, according mentioned hypothesis, danger from the destructive power of fires is reduced. Simply said, vapor contained in developed cloudy systems, as an integral part of the atmosphere, absorbs particles arrived from cosmos. According Stevancevic’s views, it does not mean the fires may appear by chance, but penetrations above poles and equators cause them. Further particle circulation contained in the SW toward Earth depends on several parameters and their combinations, which greatly makes harder the exact prediction of the potential centers. It is clear the SW suffers considerable losses in temperature and speed on its way to Earth. By recent inspection of the SW penetration through magnetosphere has shown they can be classified into two main groups: penetrations above approximately 65º of the magnetosphere latitude and penetrations in the area of 5º northern and southern from magnetosphere equator near geomagnetic anomalies (Radovanovic et al., 2003 b). Tinsley, Yu (2004) came to similar (indirect) results, what may be seen from figure 23.

40


Figure 23. Percentage changes in Jz and near-surface Ez for a Forbush decrease of 35% (polar) to 12% (equatorial) for longitude 72.5° E. The departures from symmetry about the equator are due to the variations in surface altitude, that have greatest effect on the near-surface Ez. Adapted from Sapkota 1 and Varshneya (1990) (Tinsley, Yu, 2004)

Values ΔЕz about 65º, as well as ΔJz about 5º of the northern geographic latitude are particularly noticeable. According the author: “The treatment of this effect by Sapkota and Varshneya ...for a relatively large decrease of GCR flux, of 35 % at high latitudes and 12 % at equatorial latitudes. The values of ΔJz and ΔEz, the changes in Jz and Ez from values before the GCR flux change, are plotted against latitude for longitude 72.5° E. The effect of changes in surface altitude (orography) and thus in nearsurface resistivity with latitude and longitude cause the departures from symmetry about the equator. The effects are especially important for Ez that is proportional to the altitude dependent near-surface resistivity. ...The effects of aerosols on chemistry and climate are sensitive to particle size and concentration, which are influenced significantly by nucleation processes that are not well understood” (Tinsley, Yu, 2004). According Stevancevic (2004), SW penetrations prevail above belt of 65º magnetosphere latitude, characterized by highly energetic protons but also the particles of relatively heavier chemical elements. According this author, the process of reconnection is not any rarity, to what relatively small deviation point of both vertical profile of current density and vertical electric field. “Perhaps most surprising is that 8 May 2004 was just relatively a normal day for the Earth’s magnetic field. There were no large magnetic storms on Earth, or spectacular aurorae to fill the night sky. However, Cluster and Double Star revealed that energetic particles from the Sun were blasting their way through the Earth’s magnetic shield and penetrating the Earth’s environment”. (http://www.esa.int/esaSC/SEM5ZTKKKSE_index_0.html). Contrary to the pole itself, as it may be seen from the previous figure, deviations to 65º reduce. In the area around geographic, that is magnetosphere equator, SW penetrations are mainly connected with particles of less weight, but higher velocity, which first of all may be seen through relatively stable values of the vertical current density. 1

Jz = vertical current density, Ez = vertical electric fields


41

Time will certainly tell how much the hypothesis of the previously mentioned author is correct. However, it is evident that at certain moments the hypothesis offers possible explanations making a step forward far ahead of the current suppositions in science. “Previous satellite observations have found that, during this late stage, the flows of plasma (a gas of charged particles populating Earth’s magnetosphere) in the magnetotail exhibit a reversal in direction. In recent years it was generally thought that a flow reversal region is where magnetic reconnection takes place, that is where the energy of the magnetic field is converted into particle energy (dissipation effect), resulting in high-speed plasma flows that hurl towards Earth, like space tsunamis” (http://www.esa.int/esaSC/SEMZMD7DWZE_index_0.html).

5. Case Analysis-Fires in Portugal on 24.08.2005 During July and August of 2005, more than 270, 000 ha of forest burned in Portugal. In these two months fires burned in 81% (273216 ha) of the total burned area from that year (http://www.fire.uni-freiburg.de/programmes/eu-comission/EU-Forest-Fires-in-Europe2005.pdf). Assuming that in tropical zone, due to geomagnetic anomaly i.e. weak geomagnetic field over the Atlantic (as well as over the Pacific and Indian Ocean), reconnection does not have to exist but under the strong SW it comes to a direct penetration of the SW into lower layers of atmosphere (figure 24).

Figure 24. Map of region where the UOSAT spacecraft showed memory upsets, superimposed on a magnetic field strength map. The projection is not the same, but is comparable in the South Atlantic region, where the intensity of the energetic particles is high and the field strength is low (http://space.rice.edu/IMAGE/livefrom/sunearth.html)

In the context of strengthening the Solar activity Lockwood (1999) talked about, parallel comes the weakening of the Earth’s magnetic field for about 10% in the last 150 years. “Over the southern Atlantic Ocean, a continued weakening of the magnetic field has diminished the shielding effect it has locally in protecting the Earth from the natural radiation that bombards our planet from space”


42

(http://www.space.com/scienceastronomy/earth_magnetic_031212.html)2. This problem certainly deserves more space, but for this occasion it will be prepared in the context of the SW penetration through geomagnetic anomaly (figure 25). Let us assume that penetration of the SW is followed by air mass influence in tropical zone due to kinetic energy effect. Clearly defined parameterization for proving such assumption was not established, although it seems that vast quantity of energy necessary for breaking through magnetosphere still exists, not only in the extreme conditions, enabling the particles breaking through the surface. “The magnetic field in the solar wind near Earth is about 5 nT, or 5 x 10-5 Gauss. The magnetic field on the surface of the Earth is about 0.5 Gauss”. (http://helios.gsfc.nasa.gov/physicist.html). If such assumptions do exist during ‘weaker’ interplanetary magnetic fronts, we may ask why not they also occur during stronger ones. “Solar flares are known to contain as much as 1029 joules of energy and can accelerate electrons and protons to energies of many MeV and even hundreds of MeV at times. …These coronal mass ejection ...events, as they propagate away from the sun, are also capable of accelerating interplanetary particles to higher energies - perhaps many tens of MeV. The relationship of these CME events to solar phenomena such as sunspots and flares is not yet well understood. However, CMEs are now known to be important sources of disturbances of the interplanetary medium and of the space environment of Earth, even during years of low sunspot conditions. …Space weather influence on the Earth's weather and climate is still a developing topic” (Marhavilas et al. 2004). +Bz – of interplanetary magnetic field -Bz - of interplanetary magnetic field Location of the strongest defense Location of the weakest magnetic field

Figure 25. The schematic review of the SW particle penetration into the Earth’s magnetosphere (Stevancevic, 2006)

2

Andrew Bridges, 2003


43

Therefore, the idea on the magnetic Earth’s shield penetration is not new. Absence of model that could explain this does not mean something similar is really occurring. “However, space storms, which can dump 1,000 billion watts - more than America's total electric generating capacity - into the Earth's magnetic field, indicated that the shield was not impenetrable” (http://www.nasa.gov/centers/goddard/news/topstory/2003/1203image_cluster.html). Since the beginning of this century the papers written on this theme have at least been considered as insignificant. "Like the first meteorologists with a small number of measuring stations, we had an incomplete and at times misleading view of the magnetosphere before IMAGE, because we couldn't see the big picture.32 The night-side region of the magnetosphere, which is stretched out by the solar wind, sometimes snaps back and shoots plasma violently toward Earth. The plasma becomes heated to several hundred million degrees and whirls around Earth in multi-million-amp currents. IMAGE discovered that such plasma occasionally is most dense on the Earth's day side, which was unexpected. Researchers are currently studying the phenomenon”. (http://science.nasa.gov/headlines/y2001/ast25jan_1.htm). The initial parameters for determining the quantitative values of electric convectional current of the SW particles, getting into the upper layers of troposphere (approximately 150mb) relate to the fact that the SW structure consists of particles of different electric load, different density per volume unit and different velocity and temperature. Total density of the convectional current of the SW particles may be defined by relation: J = N1e1v1 + N2e2v2 + …Nn en vn N is the number of the SW particles which bear free electric loads per volume unit, esingle electric load of particles, and V- velocity of SW. Kinetic energy of the SW and altitude of the penetration through magnetosphere define to what magnetosphere i.e. geographic latitude SW particles will get through. By declining of the kinetic energy and due to effect of gravitational force, the SW moves spirally towards the Earth’s surface. In case when the speed of SW v is perpendicular (at the right angle) to the vector of induction B of Earth’s magnetic field, then electromagnetic force acting upon particles of SW is: F=qvxB q refers to free electric loads. The relation shows the electromagnetic force is trying to bend the trajectory of the particles. If r is momentary radius of the bend trajectory of the particles, we see that: mv2/r = qvB

32

Thomas Moore


44

The circle motion of the SW particles is possible only in tropical region where the magnetic field is weak and when the vector of the speed is perpendicular to the lines of the geomagnetic field. However, on locations of the weakest magnetic field, as the central zone of geomagnetic anomaly is (and its direct closeness) the conditions for the formation of the cyclogenesis should not exist. The reason lies in the opposite directions of the magnetic field’s vector circulation in north and south hemisphere (figure 26).

+ 5° north magnetosperic latitude В Geomagnetic equator В 5° south magnetospheric latitude

Figure 26. Schematic review of the magnetic field’s vector circulation around geomagnetic equator (Stevancevic, 2006)

Other scientists have also noticed there are unclear details on the mechanism of the SW penetration as well as the parameterization of losses in speed, temperature and chemical structure of the particles. “The associated changes in the Brewer–Dobson circulation have a non-local effect on the thermal structure in the lower tropical stratosphere leading to significant solar signals in e.g. temperature, cloud cover, precipitation in the tropical troposphere. …It must however be noted that many questions concerning the impact of solar variability on the atmosphere are still open. E.g. the observed solar signal in stratospheric ozone can so far not be reproduced by models. The contribution of energetic particles to the solar signal is not yet well understood” (Langematz et al., 2005). Most frequently occurs that the vector of the speed v of the SW particles makes some angle θ with the vector of induction B. When we separate the speed v of the SW particles into one component which is in the direction of the field, v cos θ and the component perpendicular to the direction of the magnetic field of Earth, v sin θ, the result will be that the trajectory of the SW particles is helix (spiral), where the radius r is: r = mv sin θ/qB while the step of the helix (spiral) is: d = 2π r/vsinθ x vcosθ = 2πm vcosθ/qB The speed of the SW particles is: v = rqB/m sin θ


45

while the speed of wind in atmosphere, namely, air masses influenced by the SW particles is: v = (rqB/m sin θ)ή where ή refers to the degree of sliding (Radovanovic, Stevancevic et al., 2003 a, Radovanovic, Stevancevic et al., 2003 b, Stevancevic et al., 2006). Due to simultaneous effect of the gravitational force and magnetic field, the air mass trajectory, as we already mentioned, should be getting a form of the spiral. With deeper penetration in atmosphere, the speed of the particles v reduces because of friction, and thus the radius of the spiral r also reduces. When SW enters the atmosphere, ionized atoms which are in the structure of the SW are being carried in. Due to mutual effect between electronic shell and newly formed ions the electrostatic pressure increases, having direction opposite the gravitational force. Electrostatic pressure pulls air masses and reduces the total atmospheric pressure (figure 27). Then the total pressure in A point is: PА = P + Pe + Msv where P is the mass of air, Pe is electrostatic pressure in point A, while Msv is the mass of the SW particles. With deeper and deeper penetration into atmosphere the number of ionized atoms increases, electrostatic pressure increases, while atmospheric pressure decreases in point B. Thus, Pa > Pb, while the angle of the SW penetration determines the gradient of pressure i.e. higher angle- larger gradient. Distribution of air mass velocities under the SW jet points that the highest velocities are near jet. It means that in such conditions the speed of wind does not depend from the air pressure, but from friction between air masses and SW. If air pressure in such situation caused the speed of motion, than the speed of wind would be the highest at the surface of Earth, because it was the place of the largest gradient. The mentioned motion is the consequence of hydrodynamic effect of the SW. According Stevancevic (2006), the SW particles are moving through jet (tube) which is limited by magnetic walls (figure 29). If we assume the current of the SW particles is homogeneous in the jet of radius a, then the lines of the magnetic field lie at surfaces which are perpendicular to the axis of the jet. Within the jet, the intensity of the magnetic induction B increases linear with the distance from the axis of the jet and it is equal to current J which penetrates through the observed contour when r ‹ a, where

B = µo

Ir 2

µo refers to porosity of the vacuum (1.2566 x 10-6 Hm-1), I - current intensity, a- the radius of the tube, r- an arbitrary distance from the center of the tube.


46

Electronic belt Pe (A)

Pe (B)

Vertical streams

SW jet

Pa (A) Pa (B)

Earth’s wind

Point А

Point В

Earth

Figure 41. Schematic penetration of the solar wind (SW) jet into the atmosphere, entering in point A and proceeding to Point B. Pe refers to the electrons flow current and Pa to the particles flow current (Stevancevic, 2006)

Magnetic wall of tube a

Direction of the vector circulation of the magnetic field tube

Figure 29. Schematic review of the SW jet (tube) which penetrates through atmosphere (Stevancevic, 2006)

By the circulation of the vector of magnetic induction the magnetic wall is being formed around the jet not allowing dispersion. Applying the Ampere’s law on the circle contour, the diameter of which is r › a, the result will be:

∫ c

d = B 2πr = µoI


where B = µo

47

I

2πr On the basis of the above, the intensity of the magnetic induction B out of jet is inversely proportional to the distance of the radius of the circle contour from the axis of the jet. We may see from the previous figure that the low wind was carrying smoke towards west, i.e. towards the Atlantic. The linear cluster of fires suggests the connection of air mass motions in the figure 33. Therefore, it is important to emphasize two moments. The first moment relates the fire spreading in the south-north direction, i.e. in the direction of air mass blowing, from above to downward. The second one, which is also important, is that the low winds (according smoky plumes) blew in the east-west direction. According the hypothesis Stevancevic has given, the SW jet which penetrates through atmosphere is always characterized by spiral circulation of the magnetic fields around main axis of the penetration (similar to the motion of a drill).

Figure 30. Satellite recording of fires in Portugal on 24. 08. 2005 (http://earthobservatory.nasa.gov/NaturalHazards/Archive/Aug2005/Portugal_fires.TMOA2005234_lrg .jpg)

48


In other words, air masses, attacked by the hydrodynamic pressure of the SW, are moving from above to downward, from the south to north direction. Due to vortex sinking, in lower layers also comes to air motion approximately in the east-west direction. It would have been logical to expect the wind was blowing the flame around from Spain, namely from Portugal if regionally dominant direction of air flow had been from east to west, or vice versa, what did not happen in this case. As in other cases from the table 11, this time also the energetic region was in the geo effective position on the Sun, as well as coronary hole (figure 31). At that time over the north western bank of Africa, in the upper layers of troposphere, winds were blowing having the speed of over 50 m/s (figure 32). The isolines clearly show the motion of air masses of the highest speeds is directed toward the Pyrenees Peninsula (Gomes, Radovanovic, 2008). Spiral motion proofs the direction of penetration toward lower layers by the principle of the left spiral (figure 33).

Figure 31. Image of the Sun a few days before fires started to ignite in Portugal (http://www.dxlc.com/solar/index.html)


Figure 32. Wind Shear in the 150-300 mb layer mean minus 700-925 mb layer mean (http://cimss.ssec.wisc.edu/tropic/real-time/europe/winds/wm7shr.html)

Figure 33. Satellite recording of the air masses breakthrough over West Europe on 24. 08. 2005 (http://www.sat.dundee.ac.uk/pdus.html)

49

50


Figure 34. Sudden rises in protons in all energetic ranges at the beginning of 22nd.08.2005 (http://umtof.umd.edu/pm/crn/CRN_1996.GIF)

Table 8. The number of protons of certain energies a few days before and after the fires phenomena in Portugal (http://umtof.umd.edu/pm/crn/) 2

Date 2005 08 20 2005 08 21 2005 08 22 2005 08 23 2005 08 24 2005 08 25 2005 08 26 2005 08 27

(protons/cm -day-sr) >1 MeV >10 MeV >100 MeV 1.1e+06 1.6e+04 4.0e+03 1.1e+06 1.6e+04 4.3e+03 1.0e+07 7.2e+05 4.8e+03 1.4e+08 1.7e+07 1.1e+04 2.6e+08 5.1e+06 4.8e+03 3.2e+07 2.9e+05 3.2e+03 2.7e+06 4.6e+04 3.6e+03 2.3e+06 2.2e+04 3.3e+03

After decrease of the kinetic energy the jet stream of the SW particles descends towards the Earth’s surface under the effect of the gravitational force and the laws of the magnetic fields. The spiral in a form of funnel is the trajectory of the descending, the wider end of which is turned upward. Two days before forest fires in Portugal it had come to a sudden influx of the highly energetic particles from the Sun (figure 34). On the basis of the table 8 we may see the number of the highly energetic particles per volume unit has increased in all energetic ranges to 23rd. i.e. 24th.08. After that, the values were declining, but they still have had higher values than before the fires. Such data are in keeping with the information of Natural Hazards >> Fires >>: “Drought-ravaged forests in Portugal continued to burn in the fourth week of August 2005. Wildfires were burning out of


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control in several locations, and the government had declared a state of emergency in the central part of the country.” Analysis of synoptic situation and meteorological parameters showed that before 24th. 08 was a relatively longer period of dry, sunny and very warm weather. During the warmest days maximum temperatures were exceeding 40 degrees (www.weatheronline.com). The Iberian Peninsula was influenced by Azorean anticyclone of clear weather (http://wetterzentrale.de/ topkarten). The last breakthrough of fresh and cold air with clouds and precipitation was recorded in the period from 08th to 10th August, while considerably weaker breakthrough without precipitation was around 18th August. From 20th-24th August the relative humidity was very low (about 30%), while satellite recordings (figure 33) have shown there were no clouds, i.e. little humid content was in the troposphere over Portugal. From 23rd-25th August in the area over Iceland, the existing cyclone circulation intensified, what was most probably the indication of the proton particle penetration into lower layers of troposphere. The Iberian Peninsula was on the southern side of the cyclone, in warm sector with dominant western and southwestern flow. The cyclone was intensifying and cold atmospheric front were coming closer the Iberian Peninsula. We get a conviction that under those conditions the SW also penetrated the atmospheric layers deficient in moisture into lower layers of atmosphere from southwest, while a part of highly energetic particles just ‘dispersed’ over Portugal. Lucio (2005) pointed to the connection between interplanetary magnetic fields and development of weather conditions in Portugal: „Hence, in this work we evaluate the existence of empirical evidence to support the hypothesis that solar variability is linked to the Earth’s climate through regional-scale temperature and precipitation stochastic processes. One possible linkage to climate change is the sun’s influence over the local flux of galactic cosmic rays via the fact that as the solar magnetic field gets stronger; fewer cosmic rays are able to penetrate to the inner solar system and Earth. Because the galactic cosmic rays contribute for ionizer air molecules in the lower atmosphere, they might play a role in processes like cloud formation.” However, on September 15th the same year the proton’s velocities again exceeded the measuring abilities of instruments (http://umtof.umd.edu/pm/crn/CRN_2034.GIF). Fires were seizing again the northern part of Portugal (figures 35 to 37).

Figure 35. Forest fires in the village of Agua de Alto, near Agueda, northern Portugal, 18.09.2005 (http://www.sltrib.com/utah/ci_4096129#top)

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Researching the links between processes on the Sun and physical-geographic processes on Earth, on the basis of available literature, seems more and more to be directed toward synchronized phenomenon of the SW and geomagnetic disturbances. Palamara and Bryant (2004) have concluded similarly: “Therefore, we conclude that geomagnetic activity plays an important role in recent climate change, but that the mechanism behind this relationship needs further clarification.”

Figure 36. As in other analyzed cases, geomagnetic disturbances had preceded fires (small red columns in the lower part of the figure). Just at the end of 15.09. the values of proton flux has descended on the level of normal state (upper part of the figure) (http://www.sec.noaa.gov/rt_plots/satenv.html)

Figure 37. Sudden rise in proton energy of all ranges was arriving toward Earth at the end of 13.09.2005 (http://umtof.umd.edu/pm/crn/CRN_1996.GIF)


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6. Fires in Central and South Europe from 24th-26th03.2003: Case Analysis The development of the idea on the SW penetration over geographic poles will be briefly presented. “In 1961, J. Dungey predicted that cracks might form in the magnetic shield when the SW contained a magnetic field that was oriented in the opposite direction to a portion of the Earth's field. In these regions, the two magnetic fields would interconnect through a process known as "magnetic reconnection," forming a crack in the shield through which the electrically charged particles of the SW could flow. In 1979, G. Paschmann detected the cracks using the ISEE spacecraft. However, since this spacecraft only briefly passed through the cracks during its orbit, it was unknown if the cracks were temporary features or if they were stable for long periods. In the new observations, the IMAGE satellite revealed an area almost the size of California in the arctic upper atmosphere (ionosphere) where a 75megawatt "proton" aurora flared for hours (figure 38). This aurora, energetic enough to power 75000 homes, was different from the visible aurora known as the Northern and Southern lights. It was generated by heavy particles (ions) hitting the upper atmosphere and causing it to emit ultraviolet light, which is invisible to the human eye but detectable by the Far Ultraviolet Imager on IMAGE” (http://www.nasa.gov/centers/goddard/news/topstory/2003/1203image_cluster.html).

Figure 38. Sudden hit of SW into upper layers of atmosphere may cause the phenomenon of shining ring (http://www.nasa.gov/centers/goddard/news/topstory/2003/1203 image_cluster.html)

The following results confirm Stevancevic’s assumption (2004, 2006) that after the SW penetration through magnetosphere, the particles may seize air masses by their spiral motion: “A dynamical link between the solar irradiance and the stratospheric polar vortex has been attributed to an interaction between ultraviolet radiation and the ozone in the stratosphere” (Balachandran et al., 1999). According Black (2002) the results are in keeping with the view where potential anomalies of vortex in the lower part of the stratosphere, associated with changes in strength of stratospheric polar whirlpool (vortex), are causing zonal symmetric wind disturbances, spreading down toward the surface.

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Figure 39. Continuing reconnection occurred on 17/18.09.2000. Aurora was observed in the period from 01:00-10:00 on 18.09.2000 when instruments registered the disturbance (Frey et al., 2003)

Thoughts on the SW penetration into Earth’s magnetosphere have been considered as unfounded recently. But the views have definitely changed since 2003. “Relying on observations collected by NASA's Polar spacecraft and Japan's Geotail spacecraft, scientists associated with the International Solar-Terrestrial Physics (ISTP) program have gathered the first direct evidence that a process known as magnetic reconnection occurs naturally in the Sun-Earth system. Until now, reconnection had only been observed under contrived conditions in a few physics laboratories. During reconnection, magnetic fields that are heading in opposite directions - having opposite north or south polarities - break and connect to each other. …Reconnection is the fundamental process for transferring and exchanging energy in the Sun-Earth system3” (www.nassa.gov 2003). Therefore, not only the described process is contested, but it gains more on its importance. “Magnetic reconnection – a phenomenon by which magnetic fields lines get interconnected and reconfigure themselves - is a universal process in space that plays a key role in various astrophysical phenomena such as star formation, solar explosions or the entry of solar material within the Earth's environment” (http://www.esa.int/esaCP/SEMDI3T4LZE_index_0.html). In extreme cases, as showed in the previous two figures, almost the whole ring of about 65° represents input, through which electromagnetic waves penetrate (Radovanovic et al., 2003 a, Radovanovic et al., 2003 b, Stevancevic, 2004). Polar light phenomenon usually follows such manifestations. "We've observed high-altitude auroras during all of the coronal 3

A. Nishida


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mass ejection events that engulfed Earth since the instrument became operational ...But we still don't understand the process that is causing them" (ucsdnews.ucsd.edu/newsrel/science/mcsun.htm). Lilensten and Bornel (2006) emphasize certain unknowns in a domain of parameterization of the origin of the polar light mechanism: “From space, satellites can see a luminous oval that is brighter on the night side since the particles are accelerated when they pass through the neutral layer (in what way is still not known) and produce more brutal collisions. Mechanism that would explain the penetrations of highly energetic particles through atmosphere in polar areas was also the research subject of Galand (2001). “Using a coupled electron/proton transport code to analyze the data they show that the unusual low-altitude peak of thе red emission observed from ground is produced entirely by proton precipitation, the major particle energy source around the time period and in the region of the strong red aurora. ...In addition, Patterson et al. еxplain how such observations can be used to infer the effective ion-electron recombination coefficients in the ionosphere, coefficients whose values are subject to large uncertainties. ...Our abiltiy to accurately model the proton aurora is now mainly limited by the uncertainties in the input data (Basu et al.): cross sections, phase function, atmospheric neutral model, and characteristics of the incident proton flux. As consequence, proton modeling relies strongly on future laboratory experiment and in situ observations.“ Chisham (2005) states similar views: “The measurement of magnetic reconnection requires: a) detecting regions of different magnetic connectivity and b) measuring the transport of magnetic flux between them. ...However, methods of detection of this spectral width boundary (SWB) and an understanding of how the boundary relates to the open-close boundary have a history of confusion with conflicting conclusions drawn in different studies.” As from the case of Portugal, the hypothesis bases on the view that by penetration into lower layers the SW moves air masses by hydrodynamic pressure and thus it may cause the disturbances in the lower layers of troposphere. The recent researches show that in case when Bz component of IMF has direction opposite to the geomagnetic field, namely, when it has got a negative sign, the magnetosphere opens (magnetic reconnection). Then the SW particles enter the Earth’s atmosphere (magnetospheric door) in the form of a jet stream and advance along geomagnetic lines to the magnetosphere equator. Therefore, the process is occurring in the area where Earth’s magnetic field is the strongest (figure 40). Otherwise, the SW does not penetrate through Earth’s magnetosphere but passes i.e., it rejects from it. “We found that the events occurring during closed geomagnetic conditions do not show common peaks at all the high latitude stations and tend to be coherent only among Antarctic stations, while there is a lack of coherence between high latitude opposite hemispheres. Conversely, during open geomagnetic conditions the pulsation events are characterized by discrete frequencies, the same at all stations, and are generally highly coherent between high and low latitudes and between opposite hemispheres” (Lepidi et al., 2005). The strongest and weakest magnetic fields of Earth may be seen in the figure. The areas of the reconnection even under weaker SW penetrations are over Canada and Siberia, while under the influence of the kinetic energy of the SW the penetrations occur over the western Atlantic, central parts of the Pacific and south from Australia.

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Figure 40. Earth’s magnetic field intensity (Mc Lean et al., 2004)

The position of the opening of the magnetospheric door greatly depends on the moving of the geomagnetic poles, for it is clear the magnetosphere coordinates (including also geomagnetic anomalies) link magnetic poles, and not geographic ones (figure 41). This is an essential factor about, the studying of which should represent the integral part of the prognostic models. Kinetic energy of the SW determines to which geomagnetic latitude the particles will arrive. The input angle also plays an important role under such motions, so that under certain conditions polar light may appear (although much rarely) in lower geographic latitudes (figure 42). When the strongest flares on the Sun ab. 12) appeared, the polar light also appeared over south part of the USA. “During the past two weeks, number 486 and two other large sunspots set off nine other major flares. It was one of the stormiest periods of activity ever witnessed, all experts agree. The number of intense flares, some shooting out within a day of another, was unprecedented. Auroras were seen as far south as Texas and Florida. The second strongest flare in this historic two-week series was an X17 event on Oct. 28. It was aimed at Earth and generated severe geomagnetic storming when it blew past the planet less than 24 hours later”. (http://www.space.com/scienceastronomy/xtreme_flare_031105.html). Connection of the SW penetrations in lower layers of troposphere and change in the development of the synoptic situation was also noticed in the area of Antarctica. “One can see that increase in the ground temperature is determined by power of the negative BZ action: the longer BZS field exposure (and the higher electric field intensity) the more is the temperature


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deviation and shorter is time delay between the key moment and the temperature change: at stations Vostok and Dome C the 15-hours exposure affects the effective warming (up to DT= +20) after >>12 hours at level of statistical significance 0.99” (Troshichev et al., 2005).

Figure 41. North magnetic pole from 1900-2005 (http://www.mrinbetween.com/thirdparty/pdf/N_magpl.PDF)

4

Figure 42. Recording of aurora over Athens (http://www.the-eggs.org/articles.php?issueSel=18)

4

A. Ayiomamitis

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Van Geel et al. (1999) also pointed to the link of highly energetic particles and ozone: “Shumilov et al. (1992, 1995), Stephenson and Scourfield (1992) and Kodama et al. (1992) showed that solar proton events (known as SPE), which generate the solar cosmic rays, may produce ozone ‘mini-holes’ at the high latitudes (the decrease of the total ozone content is about 10-15%) and these are accompanied by a decrease of the temperature in the stratosphere of 2.4°C.” However, contrary to the previous quotation there is an opinion that under certain conditions, the SW, by entering the upper layers of the atmosphere, extrudes electrons from atoms of air due to high speed and makes large electric charges, which increase ozone concentration. Thus, the highest ozone density determines the place of the SW input into upper layers of the atmosphere (Stevancevic, 2004) (figure 43). One of the basic conclusions from the 20th Quadrennial Ozone Symposium, held from 01st-08th June 2004 in Greece was: “We have still a long way to go to understand the complex system of interactions between ozone and a globally changing environment and the best tools we have at present are the continuation of global quality observations both from ground and from space” (http://www.the-eggs.org/articles.php?id=54#). In any case, figure 43 also points to time sequence of occurrences. Therefore, similar situation on the Sun had preceded the increased concentration of ozone over North Pole. Before the reconnection occurred, a sudden proton rise had been noticed in all energetic ranges. Three days after that (24.03.2003) many fires occurred in the area of south Baltic and Poland (figure 44). In Southeastern Europe, two days later, forest fires were recorded in about ten states, also including the south of Italy (figure 45). Chronologically viewed, the wildfire was moving from north to south, namely, toward the Balkans and south of Italy.

Figure 43. Opening of magnetospheric door on 21.03.2003 three days before fires in the southern part of the Baltic coast (http://www.cpc.ncep.noaa.gov/products/stratosphere/sbuv2to/gif_files/sbuv16_nh_latest.gif)


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The analysis of the synoptic situation and meteorological parameters from March 2003., has shown that to 15th March cyclone circulation of the frequent cold and wet air breakthrough was prevailing, causing cloudiness and precipitation in the area of the Baltic and Poland. Maximum air temperature was from 0 to 10 degrees (www.weatheronline.com). After that, the cyclone circulation was getting weaker and in lower layers from the Central Europe toward that area the anticyclone was spreading and strengthening (http://wetterzentrale.de/topkarten). Such synoptic situation caused stable and clear weather from 20th March. Then it comes to the influence of strong circulation from the northern Atlantic. From 22 to 24.03 in the area of the Baltic and Poland the breakthrough of warm air is starting and warm sector of cyclones with clear weather is being formed. Relative humidity was the lowest those days (45%), while the sky was without clouds. It is possible the part of the highly energetic particles penetrated to the surface in the area of clearness in warm sector of the cyclone under simultaneous regeneration and development of the cyclone in the north of the Atlantic, what may be explained by the SW penetration to the lower layers of atmosphere. Veretenenko, Thejll (2004) wrote on the similar developments of the weather conditions: “The most pronounced effects of energetic solar proton events were observed near the south-eastern Grenland coast which is the North Atlantic part of the arctic front and a cyclogenetic area. The energetic solar proton events are accompanied by the intensification of re-deepening (regeneration) of well-developed cold cyclones in this region.”

Figure 44. Satellite recording of numerous fires on the south banks of the Baltic Sea on 24.03.2003. http://earthobservatory.nasa.gov/NaturalHazards/Archive/Mar2003/NEEurope.AMOA2003083_lrg.jpg

We call readers’ attention to the previous figure, where it may seem the number of burning localities is relatively small. Those are small red spots (hot spot), which are really far


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more than it may seem at first sight. The visual effect will certainly be much larger if the recording is additionally enlarged. We get an impression the most sensitive part of the hypothesis is exactly the part on the contact of the highly energetic particles on the molecular level with plant mass. The particle distribution is in the direct dependence from the characteristics of the SW which is moving to the surface. In Stevancevic’s (2006) opinion, in every concrete situation under penetration through atmosphere, the SW jet is dispersing in several smaller sheaves, due to increase of the geomagnetic induction B and the reduction of the radius of circulation of the SW particles in keeping with relation r = mV/qB The radius of the SW movement is proportional to mass m and velocity V, and inversely proportional to electric charge of particles q and the value of magnetic induction B. We unavoidably need experimental laboratory researches that would confirm or refute the assumption that e.g. protons or neutrons, under certain conditions, may burn through plant mass. Table 9. Number of protons of certain energies a few days before and after fires in Eastern and Southern Europe (http://umtof.umd.edu/pm/crn/) 2

Date 2003 03 19 2003 03 20 2003 03 21 2003 03 22 2003 03 23 2003 03 24 2003 03 25 2003 03 26 2003 03 27 2003 03 28

(protons/cm -day-sr) >1 MeV >10 MeV 2.8e+06 1.5e+04 3.4e+06 1.2e+04 7.0e+06 1.1e+04 8.4e+05 1.2e+04 5.5e+06 1.2e+04 8.0e+05 1.2e+04 1.4e+06 1.2e+04 9.7e+05 1.2e+04 4.2e+05 1.1e+04 4.5e+05 1.1e+04

>100 MeV 2.4e+03 2.1e+03 2.4e+03 2.7e+03 2.7e+03 2.8e+03 2.7e+03 2.6e+03 2.6e+03 2.6e+03

According to table 4 the density of the highly energetic particles of the SW had very high values on days when many fires were noted (namely, one day earlier), after what their number per unit surface gradually decreases. Contrary to extreme situations, in this case the proton velocity was not exceeding the measuring abilities of instruments (figure 46). However, the limit considered as ‘normal value’ i.e. 500 km/s (a broken line in the upper part of the figure) was surpassed on days when fires burned. In order not to make any confusion, figure 46 was recorded on 26.03, when the proton velocity had been declining. As already mentioned the satellite recordings may be taken only when fire is in its developed phase, and the moment of the ignition, by the rule occurs one day earlier.


Figure 45. Many fires on 26.03.2003. were spreading from Italy over the Balkans, Hungary, Romania, Ukraine, Slovakia and Poland (http://earthobservatory.nasa.gov/NaturalHazards/natural_hazards_v2.php3?img_id=8620)

Figure 46. Proton velocities were exceeding values of 500 km/s from 20th to 24th03.2003. (http://umtof.umd.edu/pm/crn/)

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7. The Possibility of Prognostic Modeling Respecting recent results in the research field of the interactive Sun-Earth link, the contemporary science seem to be burdened by many questions. No matter how much the period we live in seem progressive and successful in many areas of the scientific creativity, it is necessary to emphasize that according official data the causes of about 40% of the fires in Europe were not determined. The initial base for considering this question is the possible influence of the processes on the Sun upon Earth’s biosphere. However, renowned scientists such as Lilensten and Bornarel (2006) have emphasized that: “For instance, we are partly capable of describing the solar magnetic field but quite incapable of predicting it, with its various irregularities and, in particular, the triggering of coronal mass ejections. The same can be said of the photon flux and of life on the Earth, in particular in the ultraviolet and X-rays. In the interplanetary medium, we cannot quantify the dynamic pressure of the solar wind or the frozen interplanetary magnetic field found there. Consequently, it is as yet impossible to determine in advance the position of the magnetic shield formed by the magnetopause: is it on this side or the other of the orbit of geostationary satellites? The characteristics of the radiation belts are not yet well known either. Furthermore, they also depend on the cosmic radiation of all the other stars that also have to be kept under surveillance. The phenomena which enable solar particles to enter the magnetosphere are still not understood: the aperture on the day side when the solar magnetic field reverses is only a model, a theory which stands up better then others to the facts. Our knowledge concerning the porosity of the magnetospheric wall of or the collisions in the reconnection zone on the night side is relatively poor, for lack of observations.” The problem is also the stochastic phenomenon of energetic regions on the Sun, as well as extremely strong flares, what is impossible to predict for now. “It is still unclear which of the various possible nonlinear quenching mechanisms is of primary importance to the solar dynamo” (Bushby, Mason, 2004). Veselovsky (2005) thought similarly: “At present, with no diagnostics of subphotospheric processes and very poor knowledge of the solar interior dynamics, one can say that SEEs5 are practically not predictable.” Let us mention Eredelyi (2004): “What is the source of plasma heating in the solar (and stellar) atmosphere? How do perturbations dissipate efficiently, resulting in hot plasmas? The latest results of theoretical and observational studies provide some answers, but there remains much to be learned.” The confusions from this domain may be seen from many statements. “Even after more than a decade of spacecraft observations of magnetospheric plasma waves, we understand very little about how they are generated” (http://ssdoo.gsfc.nasa.gov/education/lectures/magnetosphere/index.html). But as in the case of determining the link between solar activity and meteorological conditions, the cosmic radiation additionally complicates such sort of the research. “Cosmic rays are different—and worse. Cosmic rays are super-charged subatomic particles coming mainly from outside our solar system. Sources include exploding stars, black holes and other characters that dwarf the sun in violence. Unlike solar protons, which are relatively easy to stop with materials such as aluminum or plastic, cosmic rays cannot be completely stopped by any known shielding technology” (http://science.nasa.gov/headlines/y2005/07oct_afraid.htm).


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On the basis of available literature, we get an impression that cosmic radiation has also its pulsations, namely, it is not constant. It is noticed that when the Sun is more active, the electromagnetic waves coming out of the solar system penetrate harder towards Earth and vice versa. However, sometimes in spite of intensified solar activity, at certain moments the striking fronts of the cosmic particles still arrive to us. The penetrations of such radiation may be the significant problem for the operation of the satellite instruments, but also for the estimate of the SW entering into atmosphere. Energies from the Space are traveling in a form of cloud of particles of high electric charges that may reach 450 million electron volts. Electric charge of the SW particles rarely reaches 100 million of electron volts. It seems unnecessary to emphasize that in this segment we are not even closer to the representative enough data base upon which statistics could show any trends on the global level. Except noticing the signals on the connection of the forest fires and processes on the Sun, the crucial importance of the acquired results relates to the basic directives with an aim to make prognostic models. Following the rotation speeds of the coronary holes and active regions on the Sun, by the estimate of appearing in geo effective position and on the basis of data on the magnetic field, structure and strength of the ejected energy which is coming toward Earth in the form of IMF (Figure 60), it is possible to prognosticate place and time of the jet stream enter into magnetosphere, its approximate moving toward atmosphere and influence on meteorological phenomena (atmospheric fronts, cyclones, cloudiness etc.) (Radovanovic, Stevancevic et al., 2005). Having in mind that according heliocentric hypothesis, the SW jet when in contact with Earth’s magnetosphere splits into several smaller sheaves, great problem is the positioning of the locations on Earth whereto they are going to influence. “The solar electromagnetic radiation varies the least at visible wavelengths (the regime that most directly affects weather and climate) …The charged particles that carry a portion of the Sun's energy include both the relatively low-energy plasma of the solar wind and high-energy particles, such as solar energetic protons, which have been accelerated to velocities near the speed of light. The solar wind varies both recurrently, as a function of the Sun's 27-day rotational period, and sporadically, in response to violent eruptive events in the corona, which also accelerate energetic particles to near-relativistic velocities” (http://umbra.nascom.nasa.gov/spd/secr/). From the previous figure we clearly see that electromagnetic waves from the Sun do not spread linearly, but their path is twisted. Nevertheless, mathematical parameterization of the IMF movements is caused by moss, meaning that any calculation is possible only after observed preliminary elements on the Sun. In that sense Neugebauer et al. (2000) have given some indications: “It might be explained as evidence for some sort of internal structure (such as an irregularity on the core-mantle boundary) or an aspect of the internal dynamo that allows it to "remember" some longitudinal feature in spite of the reversals. Since the interiors of the Sun and stars are so different from the interior of a planet like the Earth, the correspondence is even more puzzling.”

5

Solar extreme events

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Figure 47. Twisted line of the magnetic field in certain situations ‘leads’ the jet of the SW particles to Earth’s magnetosphere (http://www.windows.ucar.edu/tour/link=/sparc/images/imf_big_jpg_image.html)

The recent following of the processes on the Sun has shown there are several sectors of the magnetic fields (Figure 48). Belonging of some energetic regions to a certain sector points to the character of the magnetic fields (alpha, beta, gamma, delta) which, when in geo effective position, direct electromagnetic energy of a ‘certain type’ towards Earth.

Figure 48. Sector distribution of the magnetic fields on the Sun. Black small square at the bottom of the recording represents the Earth, while the circumference in the middle represents the Sun (http://www.lmsal.com/forecast/modelEIT/index.html)


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A scenario that should especially be considered relates to the SW penetrations into areas above geomagnetic equator under the dominant effect of kinetic energy first of all. According Litensten, Bornel (2006) the kinetic pressure of the SW may be: Pc = ½ n m v 2 = n kB T n refers to the number of particles per volume unit, m-mass of particles, V-their velocity, Kb Boltzmann’s constant (1.38 x 10-23 JK-1), and T- absolute temperature of the SW. If the estimate includes Archimedes’ spiral, i.e. angle θ between the SW and Earth-Sun axis, then Pe may be:

pSW =

1 2 cos θ nSW v SW2 2

According previously mentioned authors the magnetic pressure is:

pm =

B2 2μ 0

The synoptic situation development depends on the whole series of circumstances. Following the energetic regions and coronary holes, as the first step it is necessary to define geo effective position which is not static (Melony et al., 2005). According Naitamor (2005): “From all identified events (from January 1997 to September 2004) the geo effective CMEs scattered in latitude (S40, N40) and in longitude (E50, W60). These results also show that 62% events occurred on the west and 38% events in the east. Therefore CMEs which occur in the west part of the sun disk can affect the earth geo magnetosphere.” Width of the ejected jet that is emitted from mentioned sources directly determines whether they are directed towards Earth. The direction of Bz component, velocity, density, temperature, chemical structure, the input angle of the SW into magnetosphere as well as the size of the opening of the magnetospheric door are the initial elements necessary for making the prognostic models. However, it is clear that there is large number of possible combinations, so that at this moment, the defining of the resultant penetration is an extremely complex task. Baliunas, Soon (2000) emphasized the importance of not only 11 years long but 20 years long magnetic cycle of the closest star to us: “The Sun's changing magnetism has several consequences, some only recently learned. For example, the surprise of the last 20 years is the observed fact that the total light, or brightness, of the Sun also changes in step with the magnetic cycle.” It seems that among others, Stevancevic and collaborators gave in the papers ‘more courageous’ elements to what direction the research methodology should be developed. We assume the new solar cycle is about to start on April 2008 so that soon we should get into a period of calmer activities on the Sun. In other words, we should expect a little lower temperatures and also smaller number of forest fires on Earth. According Cranmer (2002): “At solar minimum, the high-speed wind dominates at high latitudes (greater than ±20–30°) and the low-speed wind coexists at lower latitudes with occasional high-speed streams.” If the link between large forest fires (it is meant on most fires of unknown cause) and strong

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eruptions (also including strong corpuscular radiation from the coronary holes) directed towards Earth proves, the scenarios predicting further increasing of forest fires won’t have basis. Mentioned conclusion relates the period of the first half of the cycle that is in front of us, i.e. approximately to April 2013. Quassim and Attia (2005) have concluded similarly: “According to our prediction, the Gleissberg Cycle have been started its declining phase and it seems to be slower than the increasing phase, i.e. the firing of solar activity is going to its end and it is expected to return to the average level detected through the far cycles 13, 14 and 15. A relative reduction in heating rate is predicted; it will reach its minimum in 2012, next increasing with slow rate, but lesser than the previous rate, is expected. Because of the large contribution of the artificial influence we are still in the critical stage.” Studying Sun’s spots, Hathaway and Wilson (2006) have come to similar results. According them, entering the second phase of the solar cycle, it is possible to expect an extremely strong solar activity (figure 49). Investigating the link between geomagnetic disturbances and Sun’s spots, it is noticed that: “Cross correlating sunspot number vs. Interhour Variability Index (IHV), they found that the IHV predicts the amplitude of the solar cycle 6-plus years in advance with a 94% correlation coefficient. "We don't know why this works"6 …The underlying physics is a mystery. But it does work" (http://science.nasa.gov/headlines/y2006/21dec_cycle24.htm?list53210).

Figure 49. Prediction of the amplitude of the Solar cycle 24 (Hathaway, Wilson, 2006)

However, the importance of the heliocentric hypothesis among others is that, it in the foreground emphasizes only those coronary holes which direct their energy towards us. 6

Hathaway


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Landschiedt (2000 c) has thought similarly: “Moreover, it is quite clear now that all models that back cast the Sun's effect on climate on the basis of sunspot numbers yield misleading results. The number of eruptions does not depend proportionally on the intensity of 11-year sunspot maxima. Cycle 20 with the highest monthly sunspot number R=106 was much weaker than cycle 21 (R=165) and cycle 22 (R=158), but it produced nearly as much flares as cycle 21 and considerably more than cycle 22. You would expect that current cycle 23, which is at the same level as cycle 20 should produce a similar number of flares. Not so. The flare activity is weaker than at any time after the beginning of observations in the thirties. Those who do not take this into account draw conclusions that do not conform to reality.” Regarding establishing the link with climate interactive connections, the recent researches are in keeping with the results Komitov (2005) has given: “The generalized conclusions about the solar 10-11 and 20-22 year cycles effects over Earth climate are: 1. Quasi 11-year oscillations are observed in many climatic parameters, but mainly in temperatures. They can to track in climatic data series of separated stations as well as in planetary scale. These cycles are relatively better expressed in winter as in summer and mainly on middle and high geographic latitudes. 2. For the atmospheric circulation the quasy-20-22 year oscillations are typical. As a result from 20-22 year cycle influence over Iceland baric minimum position and activity, the same cyclity in rains and pressure over South –East Europe and particularly –over Bulgaria is observed.” One of also important segments that should be taken into consideration when making the prognostic models relates to the weakening of Earth’s magnetic field. “Previous studies have shown that the strength of the Earth's magnetic shield has decreased 10 percent over the past 150 years. During the same period, the north magnetic pole wandered about 685 miles out into the Arctic, according to a new analysis by Stoner. …A major uncertainty, however, has remained regarding how long this process takes” (http://www.space.com/scienceastronomy/earth_poles_040407.html)7. Studying storms in Britain, Wheeler (2001) relied on general aspects of the procedure Corbyn had used. Those aspects are based on the variations in the Sun’s behavior, its magnetic field, coronary eruptions and fluctuating character of the SW. Therefore, that is the methodology which, as observed on the whole, does not have anything in common with most contemporary prognostic models in use. The result was that in the period from October 1995. to September 1997., four out of five strong storms were correctly prognosticated. The fifth one had the mistake of 48 hours, while such mistake (from the aspect of the methods just about to develop) may be considered as marginal one, simply because the prognosis had been done months earlier. As far as we know, Corbyn did not publish his methods anywhere, because they have been used in commercial purposes. In that context Landscheidt (2003 a) also made, we may say, significant step forward: “I have shown that ENSO events, the North Atlantic Oscillation (NAO), the Pacific Decadal Oscillation (PDO), extreme in global temperature anomalies, drought in Africa, and European floods are linked to cycles in the sun’s orbital motion around the center of mass of the solar 7

Robert Roy Britt, 2003

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system. So the next extended wet period should begin around 2007 and last about 7 to 8 years …A draught peak, indicated by LPTC …is to be expected from 2025 on and should last about five years.” The same source enclosed the proof the prognosis was done several years in advance: “Dr Theodor Landscheidt claimed several times in the above paper that he had successfully predicted key climatic events (such as the current El Niño) years before the actual events, making reference to papers currently archived on this website and to other papers he has published elsewhere. I can certify that the papers he refers to were indeed published on this site on the dates indicated and that his forward predictions made on this website to events that have now already happened were indeed made well ahead of their time, just as he says they were. In particular, he predicted the current El Niño 3½ years in advance, in a paper published in January 1999. I can therefore fully confirm the authenticity of that prediction, as can the many expert reviewers who participated in the subsequent open review in 19998.” Radovanovic, Lukic et al. (2005), Stevancevic, Radovanovic et al. (2006) have also pointed that by working out the heliocentric hypothesis the long-term forecasts can be done, with a special review on the possibility of the practical application. On the basis of the experience, Stevancevic, Radovanovic et al. (2004, 2006) have pointed to the positive sides but also the mistakes appearing by using such approach. Todorovic, Stevancevic et al. (2005) have also given some indications the processes on the Sun may cause forest fires.

8. Conclusions We may conclude that the number of forest fires as well as surfaces they occupy has increased from year to year. Difficult which has existed during the research relates to modest database. Unsuccessful was the attempt to unite necessary satellite data with data on fires for period 1991-2001. That is why it was decided to add FAO UN results to establish whether there is a signal of the eventual causality. Observation Wang (2005) gave seems interesting: “Following E. N. Parker, when the mathematics becomes too much complicated in the study, is seems the time to stop to find new physics, while when the observations get into too many details, it seems the time to stop to think what physics we are working on“. Proceeding from the official data, the cause for about 43% of the forest fires was not established. The monograph points out the hypothetic possibility that certain processes on the Sun could be the explanation. As mentioned in the Introduction, certain segments of basic idea need detailed research in order to confirm or refute the heliocentric approach. On basis of the recent researches, it is certain that destructive power of fires, not only rages vegetation throughout the world from year to year, but also endangers the environment. With all accomplishments of modern age, as well as with undertaken measures (on general level), we can conclude the society was caught with fire phenomenon. In such circumstances “guilt” imputes to intentional or unintentional burning by man or by electric discharges from the atmosphere. We have seen that in some parts of the USA lightning practically represents minor cause of the initial phase. According to previous estimation, even over 50% of “responsibility” was attributed to lightning. On the other side, we have clearly seen that 8

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modern science is not able to explain an extremely large quantity of electric power in clouds. Rain that should follow thunder is also in a domain of sporadic interests. Thus, we have come to global warming, that is, climatic disturbances for which man bears most responsibility. On basis of such arguments, some officials claim men guilty for even over 95% of the cases. This “trend” in science is dominating so much that at the beginning of the research there was a worry into the coherence of developing at any other different approach. However, there are more and more scientists stating their own arguments for opposite view from different aspects. In accordance to estimation that the hypothesis may be contested, especially on delicate places which objectively do exist, the monograph gives a great number of quotations just because of possible reproaching for selective choice and arbitrary interpretation of some scientific papers. In any case, there is a strong belief the successful measures of prevention may only realize on bases of better notion of what is happening on the Sun, of processes happening in the magnetosphere and atmosphere, as well as manifestations that charged particles make in the contact with biomass. Generally, the situation we are in now characterizes the impossibility of making both successful prognostic models and prevention: “purely analytical system“ (Hardy, Hardy, 2007). According to hypothesis Stevancevic developed, depending on solar wind parameters, the differences concerning the regional development of the weather conditions seem to give a universal approach in the only possible way for now. “One hypothesis for these clustered dates (Agee 1993) is that these were times of sunspot minima associated with periods of lower than normal solar activity (Stuiver and Quay 1980). These global cooling periods may be linked to changes in the factors associated with large fire events in more recent times in the wetter portions of the Pacific Northwest: drought, lightning activity, the occurrence of east winds, or less summer onshore flow of moist air. We do not understand these linkages well, or linkages between fires and other episodic but potentially catastrophic disturbances“ (Agee, Krusemark, 2001). Moore et al. (2002) thought similarly: “Many aspects of fires in the landscape remain obscure and more reliable data on fire causes, impacts and research on fire behavior is required to effectively understand and then address the fire issue“ If we only rely the data from the table 11, we could say the connection is direct and the observed fires are in temporal accordance with mentioned process on the Sun. “Obviously we need to understand first what happens in the Sun's convection zone when perturbations in the torque cycle occur. …I think that these problems can only be solved by a joint interdisciplinary effort of openminded scientists“ (Landschieidt, 2000 b). Viewing from presented perspective, Lynch et al. (2004) for example, understood the domain of the key question, but obviously without clear vision how further to develop the measures of prevention: “Our results therefore support other recent studies demonstrating that warmer/drier climatic conditions do not necessarily induce greater fire importance. …These results contradict the current understanding of modern fire–climate relationships. It is also inconsistent with model predictions that a drier and warmer climate, as a result of glasshouse warming, will lead to increased fire activity in boreal systems“ Gorte, (2006) is categorical: “Research information on causative factors and on the complex circumstances surrounding wildfire is limited. The value of wildfires as case studies for building predictive models is confined, because the a priori situation (e.g., fuel loads and distribution) and burning conditions (e.g., wind and moisture levels, patterns, and variations) are often unknown“. On basis of the researches showed in this study, we may conclude the following:


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in all cases the data were gathered for, up to several days earlier the coronary holes and energetic regions in geoeffective position on the Sun had preceded forest fires in Europe. In every concrete situation, the emission of strong electromagnetic and thermal corpuscular energy from these sources had preceded fires; basic ways of solar wind penetration into the magnetosphere are a) reconnection (in the area of geomagnetic poles) and b) direct solar wind penetration under the dominant effect of the kinetic energy (near geomagnetic anomalies); solar wind directed towards the Earth gets weaker with deeper and deeper penetration towards the topographic surface. The modifications happening above the Atlantic anomaly and over magnetosphere tropics also represent the border area modern science has come to. air masses seized by power stream of the solar wind particles, are subject to the magnetic field laws and their moving is on the account of particles’ energy of the power stream; geomagnetic coordinates can represent the base for mathematical equation usage, which describe the trajectories of air mass movements; direction of air mass movements is determined by the polarization of the solar wind charged particles. In the northern hemisphere, the movement of winds made on the account of the proton solar wind energetic particles has the left direction. Wind speed increases with the height increase and it is directly proportional to the kinetic energy of the solar wind particles’ increase; cloudiness represents one of the most important factors, determining whether charged particles will be deposited to the topographic surface; on the basis of the preliminary results, there are indications that the cosmic radiation (especially in period of reduced solar activity) may also cause fire phenomenon. As already said, the cosmic radiation in certain situations may be characterized by far higher temperatures, speeds, particle density, that is, by far stronger electromagnetic waves than ever measured for the solar wind. “However, the physical mechanism of solar activity effects on weather phenomena remains unclear. It is suggested that a significant part in the transfer of the solar variability to the lower atmosphere may be played by charged particles of solar and galactic origin, mainly protons, with energies from ~100 MeV to several GeV“ (Veretenenko, Thejll, 2004). research at what conditions the charged particle dispersion on vegetation may cause the initial phase of burning require experimental testing. Due to impossibility of precise prognosticating at which locations it may concretely happen, necessary simulation of the similar conditions in laboratory is considered as the first step.

It is well known that a minimum of 300 °C is necessary for the mentioned initial phase. It is not necessary to point that so high air temperature has never been measured on the Earth by standard meteorological measures, even when we talk about soil temperature. Brief notes on the recent experiences of meteorologists and climatologists are certainly related to the ingratitude of the long-term forecasting. What could be concluded, when it is about the processes on the Sun, is that in the following several years the Sun should come into relatively calmer phase, so we should expect the reduction in the number of fires. It certainly does not mean that we won’t have them (it is first of all meant on those fires with “unknown” cause). However, for now we cannot conclude with certainty how it will effect


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the cosmic radiation and what, in fact, it will bring us in future. “Magnetic reconnection, turbulence and shocks are three fundamental ingredients of the plasma Universe. The detailed understanding of these key processes and their associated multi-scale physics is a challenge for the future of space physics. One of the lessons learned from Cluster is the need for new space missions equipped with instruments of higher sensitivity and better time resolution together with a larger number of satellites“

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Chapter 2

STATISTICAL CHARACTERISTICS OF THE HELIOSPHERIC PLASMA AND MAGNETIC FIELD AT THE EARTH'S ORBIT DURING FOUR SOLAR CYCLES 20-23 A.V. Dmitriev1, 2, A.V. Suvorova2 and I.S. Veselovsky2, 3 1

Institute of Space Science, National Central University, Taiwan Skobeltsyn Institute of Nuclear Physics, Moscow State University, Russian Federation 3 Space Research Institute (IKI), Russian Academy of Sciences, Moscow, Russian Federation

2

Abstract The review presents analysis and physical interpretation of available statistical data about solar wind plasma and interplanetary magnetic field (IMF) properties as measured in-situ at 1 A.U. by numerous space experiments during time period from 1964 to 2007. The experimental information have been collected in the OMNI Web/NSSDC data set of hourly averaged heliospheric parameters for last four solar cycles from 20th to 23rd. We studied statistical characteristics of such key heliospheric parameters as solar wind proton number density, temperature, bulk velocity, and IMF vector as well as dimensionless parameters. From harmonic analysis of the variations of key parameters we found basic periods of 13.5 days, 27 days, 1 year, and ~11 years, which correspond to rotation of the Sun, Earth and to the solar cycle. We also revealed other periodicities such as specific five-year plasma density and temperature variations, which origin is a subject of discussion. We have found that the distribution of solar wind proton density, temperature and IMF is very close to a log-normal function, while the solar wind velocity is characterized by a very broad statistical distribution. Detailed study of the variability of statistical distributions with solar activity was performed using a method of running histograms. In general, the distributions of heliospheric parameters are wider during maximum and declining phase of the solar cycle. More complicated behavior was revealed for the solar wind velocity and temperature, which distribution is characterized by two- or even tree-peak structure in dependence on the phase of solar cycle. Our findings support the concepts of solar wind sources in the open, closed and intermittent magnetic regions on the Sun.

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A.V. Dmitriev, A.V. Suvorova and I.S. Veselovsky

1. Introduction Solar wind (SW) plasma and interplanetary magnetic field (IMF) parameters are measured in situ during space era nearly continuously onboard many spacecraft and satellites. The physical processes on the Sun and in the heliosphere leading to observed SW and IMF parameters and their variations are now rather well investigated and understood, though some unsolved problems still remaining [Schwenn and Marsch, 1990; Burlaga, 2005]. Namely, heating of the solar corona and generation of the solar wind and heliospheric magnetic field are still unresolved subjects of very intense investigations during last decades. The SW and IMF data are processed and compiled in data bases, which contain hundreds of thousand hourly averages of the solar wind plasma and IMF parameters measured near Earth’s orbit in 1964-2007 by the IMP, HEOS, VELA, OGO, ISEE, Prognoz, Wind and ACE satellites [King, 1981, King and Papitashvili, 2005]. The estimation of errors in those data is difficult because direct measurements were made with different instruments on different satellites and at different orbits. The data obtained are rather nonuniform in both spacing and relative and absolute accuracy. The procedure of relative intercalibration of detectors and introduction of correction is not complete [King, 1977; Couzens and King, 1986; Freeman et at al., 1993; Russell and Petrinec, 1993; Zwickl, 1993; Dmitriev et al., 2005a; King and Papitashvili, 2005]. Detailed description of the data intercalibrations and corrections are presented at web site http://omniweb.gsfc.nasa.gov/html/omni2_doc.html. The average values of SW and IMF parameters at the Earth orbit were calculated in a number of papers based on the analysis of these growing data sets [Veselovsky et al., 1998a; 1999; 2000a, 2001]. In mentioned papers, long-term variations of the averaged density and other parameters of the solar wind and interplanetary magnetic field were analyzed using the data obtained from direct measurements at the Earth orbit from 1964 to 1996. A general trend was revealed for the entire period along with quite pronounced but comparatively small variations during solar cycles 20, 21, and 22. The results obtained highlighted the important role of different sources of the solar wind. At different phases of the solar cycle, open, closed, and intermittent magnetic-field configurations are typical of these sources [Veselovsky et al., 1998a]. The variability and the periodicity of heliospheric parameters are of interest from the point of view of plasma dynamics on the Sun and in the interplanetary space as well as for the solar-terrestrial physics. The long-term and large-scale variations are described in numerous studies [e.g. Crooker, 1983; Veselovsky, 1984; Schwenn, 1990; Zhang and Xu, 1993; Gazis, 1996; El-Borie et аl., 1997]. The variability of the Sun as a star was traced in its integrated solar-wind mass and energy fluxes [Veselovsky et al., 1999]. Direct plasma measurements in the heliosphere over more than the last thirty years indicated that these quantities have experienced relative variations by factors of 1.5-2, approximately in antiphase with the last three eleven-year solar cycles. A rising trend was noted over this time, with a similar relativevariation scale. This trend may be a manifestation of a "secular" cycle with duration of 60-70 years or longer. The methods of the Fourier transform, spectrum-time analysis, and wavelet analysis were used to study the structure and dynamics of rhythmic and non-rythmic variations of the main SW and IMF parameters at time scales from days to tens of years. A large variety of the observed regular and irregular variations in the near-Earth heliosphere is explained by a

Statistical Characteristics of the Heliospheric Plasma and Magnetic Field…

83

number of reasons: (1) the variability of unstable processes in the region of solar wind formation, (2) the rotation of Sun and the associated inhomogeneities in its corona, (3) and the Earth's orbital motion. Irregular, a-periodic variations are present for all parameters and at all time scales. The most prominent regular variations are related to cyclic processes on the Sun and its rotation [Veselovsky et al., 2000b; Dmitriev et al., 2000]. The time-epoch analysis and hysteresis curves of the heliospheric parameters show some general and specific properties of the cycles [Veselovsky et al., 2000b; 2001; Dmitriev et al., 2002a; 2002b; 2005b]. Based on these results and using measured heliospheric parameters during the rising phase of the 23-rd solar cycle we were able to present some semiquantitative estimations of the expected solar wind energy flux and the induced electric field for the time period after the solar maximum. The similarity between the rising phases of the 23-rd and 20-th solar cycles presented additional grounds for correct expectations of the lower maximum of the 23-rd solar cycle and the geomagnetic activity as compared with the 21-st and 22-nd solar cycles [Dmitriev et al., 2002b]. The purpose of this paper is an extension of our statistical studies of SW and IMF parameters based on growing amount of direct in-situ measurements near the Earth orbit during space era. Common statistical properties are considered in a form of statistical distributions in Section 2. “Basic Statistical Properties”. Some characteristic periods in variations of heliospheric parameters derived by a method of Fourier transform for unequallyspaced data are discussed in Section 3. “Characteristic periodicities”. Variations of the parameters with solar cycle are studied by a method of running histograms in Section 4. “Solar cycle variations”. Section 5. is “Summary and Conclusions”.

2. Basic Statistical Properties Sunspot Number In the first turn we consider sunspot numbers represented by the Wolf number (W) as a key heliospheric parameter related to the variations of solar activity. The Wolf number is measured continuously with 1-day step for many decades. It is a simple and robust parameter for comparisons and ordering of data in its regular and irregular behavior. Figure 1 shows 27day running annual Wolf number for the time interval from 1963 to 2007. The smoothed time profile has four prominent maxima of solar cycles 20th to 23rd, respectively, in 1969, 1980, 1989 and 2000. We can also indicate five solar minima in 1964, 1976, 1986, 1996 and about 2007, which allow easy estimation of the cycle duration: 12 years for the 20th cycle, 10 years for the cycles 21st and 22nd, and ~11 to 12 years for the 23rd cycle. Those time intervals are in good agreement with empirical fact that large solar cycles (21st and 22nd) have shorter duration of ~10 years than small cycles (20th and 23rd) having duration of ~12 years. It is a manifestation of the well-known Waldmeier’s rule [Veselovsky and Tarsina, 2002a]. Hence the last four solar cycles exhibit two periods of 10 years and of 12 years, i.e. around 11-year cycle.


84

Sunspot Number W

150

100

50

20th

22nd

21st

23rd

0 1965 1970 1975 1980 1985 1990 1995 2000 2005

Year Figure 1. Time profile of the 27-day running annual Wolf number W from 1963 to 2007.

Further analysis of the dynamics of sunspot number requires a study of its statistical properties. Statistical distributions of the W are presented in Figure 2. The daily value of sunspot number varies in very wide range from 0 to 302. In the linear scale, the distribution is smooth and decreases fast from maximum at W=0. There is a little plateau at W of ~100. Hence in the linear representation the dominant contribution to the distribution function is produced by relatively small sunspot number of W, the number of independent measurements in calculation of the RMSD becomes N-1 as represented in the denominator. The RMSD of normal distribution is equal to one standard deviation σ. That is another important property of the normal PDF. The third moment of a statistical distribution is skewness:

1 N ⎛x − X k3 = ∑ ⎜⎜ i N i =1 ⎝ RMSD

3

⎞ ⎟⎟ . ⎠

(4)

The skewness is a measure of the lack of symmetry of the distribution. A positive (negative) number indicates a higher number of large (small) values of the parameter than would be expected for the normal PDF, which has zero skewness. The fourth statistical moment, kurtosis, is defined as follow:

1 N ⎛x − X k 4 = ∑ ⎜⎜ i N i =1 ⎝ RMSD

4

⎞ ⎟⎟ − 3 ⎠

(5)

The kurtosis is a measure of the flatness (negative value of k4) or peakedness (positive value of k4) of the distribution relative to the normal PDF with the same mean and dispersion. Note that normal distribution has zero kurtosis. Thus, under the assumption of normal distribution the determination of mode and standard deviation can be simply substituted by calculation of mean and RMSD. Actually those moments can be calculated for any variable, which statistical distribution might differ from the normal, i.e. have non-zero skeweness and/or kurtosis. However in such a case the first two statistical moment have lost their important statistical sense. Namely, the mean might be different from the mode, i.e. we lost information about the most probable value of measured parameter. The RMSD is not equal to the standard deviation σ, i.e. the variation of parameter can not be determined in standard manner. In this case it might be possible to find such a represnetation of the parameter that allows approaching its statistical distribution to the normal PDF. The logarithmic scale is one of very useful representations. Here we can introduce a lognormal PDF as follow [e.g. Hartlep et al., 2000]:

⎡ 1 ⎛ ln( x / X ) ⎞ 2 ⎤ ⎡ 1 ⎛ ln( x) − ln( X ) ⎞ 2 ⎤ 0 0 ⎟⎟ ⎥ ⎟⎟ ⎥ ≡ A exp⎢− ⎜⎜ P( x) = A exp⎢− ⎜⎜ 2 ln( σ ) 2 ln( σ ) ⎠ ⎦⎥ ⎠ ⎦⎥ ⎣⎢ ⎝ ⎣⎢ ⎝

(6)

The lognormal PDF has the same properties as normal distribution but in logarithmic scale. Indeed, replacing ln(x) by z, ln(X0) by Z0 and ln(σ) by δ we can rewrite Equation 4 as:


90

⎡ 1 ⎛ z − Z0 ⎞2 ⎤ P( z ) = A exp⎢− ⎜ ⎟ ⎥ ⎢⎣ 2 ⎝ δ ⎠ ⎥⎦

(6a)

This Equation is exactly the same as Equation 1. Taking the exponent we can simply convert numbers from logarithm to linear scale. The exponent of most probable of lognormal distribution is equal to mode X0. In other words, the lognormal distribution reaches the maximum at X0. However, the dispersion of lognormal PDF has a different meaning such that the hwmh should be redefined as a ratio of x/X0 at middle height (rmh), which is equal to

rmh = σ

. Therefore, the standard deviation σ in the logarithmic scale has a meaning of standard relative deviation, i.e. a standard ratio relative to mode. In the lognormal distribution the parameter σ is dimensionless. In linear scale, the lognormal distribution is asymmetric and its dispersion is characterized by upper SDup and lower SDlo standard deviations: 2 ln( 2 )

SDup= X0σ - X0 = X0(σ-1)

(7a)

SDlo= X0 - X0/σ= X0(1-1/σ)

(7b),

which are not equal, because of σ is always more than 1. Indeed, the logarithmic dispersion δ=ln(σ) should be always positive. In the logarithmic scale we can also introduce the first four statistical moments of the distribution of random variable. Namely, the mean value <X>ln can be defined as follow:

X

ln

= exp( ln( x) )

(8)

where

ln( x) =

1 N ∑ ln( xi ) N i =1

(8a)

It is very easy to show that the mean in logarithmic scale is equal to the geometric mean: 1

X

ln

⎛ N ⎞N = ⎜⎜ ∏ xi ⎟⎟ ⎝ i =1 ⎠

(8b)

The lognormal distribution has the same achievement as the normal one: mean <X>ln is equal to mode X0 and to median of logarithms. The second moment RMSDln is introduced as follow:


⎧⎪ 1 N RMSDln = exp⎨ ∑ (ln( xi ) − ln X ⎪⎩ N − 1 i =1

⎫ 2⎪ ) ⎬ ln ⎪⎭

91

(9)

For large number of independent measurements N the RMSDln approaches to the standard deviation σ of lognormal PDF. Note that the RMSDln is also dimensionless and has a meaning of relative deviation from the mean <X>ln. Hence in linear scale, the upper and lower deviations from the mean are calculated as <X>ln RMSDln and <X>ln/RMSDln, respectively. The third and fourth statistical parameters can be defined in logarithmic scale as follows:

1 N ⎛⎜ ln( xi ) − ln X ln ⎞ ⎟ skewness k3 = ∑ N i =1 ⎜⎝ ln( RMSDln ) ⎟⎠

3

(10)

and 4

1 N ⎛⎜ ln( xi ) − ln X ln ⎞⎟ kurtosis k 4 = −3 ∑ N i =1 ⎜⎝ ln( RMSDln ) ⎟⎠

(11)

The skewness and kurtosis calculated in the logarithmic scale have the same properties as those in the linear scale. Hence they can be used as a measure of similarity of the statistical distribution to lognormal PDF. For a log-normally distributed parameter the skewness and kurtosis are equal to zero, and the most probable and standard deviation can be easily calculated, respectively, as mean <X>ln and RMSDln. In practice however, the number N is not infinitely large and statistical distributions may have various shapes, which in general differ from the normal PDF. The mode, i.e. most probable value, is different from mean and median, and may be very different for strongly skewed distributions. As an example we demonstrate the statistical distribution of sunspot number (see Figure 2). Direct determination of the most probable of statistical distribution is not very accurate because of the following circumstances. The statistical distribution of empirical parameter is discrete with finite size of bins, because of limited number of measurements N. Very small size of the bins leads to appearance of many subsidiary peaks with low statistical significance, such that the most probable is hidden by noise. Hence the size of bins is selected in such a way as to provide a smooth shape of statistical distribution. As a result the accuracy of mode and dispersion are limited by the width of bin, which might be pretty wide and, thus, the accuracy becomes very poor. Another way of fitting the statistical distribution by standard, say normal, PDF is also unreliable, because in general the distributions are different from the normal. In such situation, as a first step we compare the mode, mean and median in order to verify the normality of distribution. As a second step, the statistical distribution is approached, if possible, to the normal shape. Namely we choose such a representation (linear or logarithmic), which provides minimal difference between the mode, median and mean. Hence in the new representation the statistical distribution becomes more symmetric and its most probable is close to average. Our choice is based on a very important property of median: it is invariant in transformations between the linear and logarithmic scales. The quality of our approach is expressed numerically by the skewness and kurtosis.


92

In the following sections we will show that the logarithmic representation allows symmetrization of the statistical distributions for many heliospheric parameters. The number of bins is chosen to achieve a smooth shape of statistical distribution. For most of parameters that number is about 30. Using the statistical distribution, we estimate the most probable value of parameter. The median, mean and RMSD are calculated in the most appropriate scale, where the distribution is mostly close to the normal PDF. The distribution is fitted by normal or lognormal PDF in the following way. The mode X0 of PDF is supposed to be equal to median. The standard deviation SD is calculated by fitting the shape of statistical distribution by a PDF. The results are presented in Table 1. There we also indicate a type of PDF and percentage of data covered by that PDF. Table 1. Main statistical numbers of key heliospheric parameters at the Earth orbit during 1963-2007.

W V, km/s T, 103 K n, cm-3 He/p Pd, nPa Sk, erg/cm2⋅s B, nT Bxy, nT Bx, nT By, nT Bz, nT Ey, mV/m Ma Ms

statistics 16437* 265699 227883 244625 163052 244625 244625

min 0 156 2.9 0.1 0.001 0.01 .0015

271938 0.4 271938 0.14 271938 -40.1 271938 -38.8 271938 -46.3 242155 -34 228053 1.1 227171 2.6 212221 0.001 β * Number of days

max median mean mode RMSD SD k3 k4 PDF % 302 62 51 97~117 4.66 1.88 two-peak 1200 420 430 370~390 1.25 1.26 .42 -.32 flatten 7000 85 83 72~94 2.3 2.43 -.14 -.31 lognormal 94 118. 5.3 5.4 4.3~5.3 2.0 2.0 .008 .59 lognormal 95 0.4 0.037 0.034 0.03~0.05 2.0 1.7 -.79 1.4 skewed 79 2. 2. 1.8~2.25 1.86 1.74 -.01 1.7 lognormal 95 30 0.43 0.44 0.37~0.49 2.0 1.92 .08 1.3 lognormal 98 55.8 52. 29.4 46.1 36.8 30 93. 72. 87.

5.9 4.6 0. 0. 0. 0 8.4 12.7 0.48

6.0 5.5~6.5 4.5 4.3~4.7 0. ±3 0. ±3 0. -0.6~1.5 0 -0.4~0.2 8.4 8.~9.4 13. 11.~13.8 0.43 0.44~0.65

1.55 1.74 3.90 4.30 3.1 1.55 1.54 1.35 2.61

1.48 .12 .85 lognormal 1.55 -.78 2.8 lognormal two-peak two-peak 2.09 -.01 9.1 normal 1.0 -0.1 23. normal 1.44 .025 1.7 lognormal 1.30 0.57 1.3 lognormal 2.12 -.92 2.5 lognormal

95 82 88 88 95 92 89

Solar Wind Plasma There are many indications that SW parameters have lognormal distribution. Veselovsky et al. [1998b] revealed that statistical distributions of hourly averages of SW proton density and temperature during three solar cycles from 20 to 22 are well fitted by the lognormal PDF. Statistical analysis of SW data acquired from the Wind satellite in 1995 to 1998 also reveal that hourly averages of solar wind velocity, density and temperature have lognormal distribution [Burlaga and Szabo, 1999, Burlaga and Lazarus, 2000]. King and Papitashvili [2005] studying the hourly averaged SW plasma data during the 23rd solar cycle, use also logarithmic representation of the proton density and temperature and mention that the distribution of density is close to the lognormal. Statistical distributions of the SW parameters are shown in Figure 5. All the parameters are represented in the logarithmic scale. In Figures 5a and 5b we find that the distributions of


93

proton density n and temperature T are very close to lognormal PDF with the mode, respectively, 5.3 cm-3 and 85103 K and standard relative deviation, respectively, 2 and 2.43. They have pretty small skewness and kurtosis. In contrast, the distributions of SW velocity and He/p ratio are different from lognormal (Figure 5c and 5d). The statistical distributions of n and T are fitted very well by the lognormal PDF within 2-σ interval that corresponds to ~95% of the total statistics, which contain 244625 and 227883 hourly averaged measurements, respectively, of the density and temperature.

Occurrence number

1E+5

1E+4 median = 5.3 mean = 5.4 mode = 4.3~5.3 RMSD = 2. SD = 2. skewness = 0.008 kurtosis = 0.59

1E+3

1E+2

+2σ

−2σ 1E+1 1E-1

1E+0

1E+1

1E+2

SWP Density, 1/cc

a)

Occurrence number

1E+5 1E+4 median = 85000 mean = 83000 mode = 72000 ~ 94000 RMSD = 2.3 SD = 2.43 skewness = -0.14 kurtosis = -0.31

1E+3 1E+2 1E+1

+2σ

−2σ 1E+0 1E+3

1E+4

1E+5

SWP Temperature, K

b) Figure 5. (Continued)

1E+6

1E+7


94

Occurrence number

1E+4

1E+3

median = 420 mean = 430 mode = 370 ~ 390 RMSD = 1.25 SD = 1.26 skewness = 0.42 kurtosis = -0.32

1E+2

1E+1

1E+0 100

1000

SWP Velocity, km/s

c)

Occurrence number

1E+4

1E+3

1E+2

1E+1 1E-3

median = 0.037 mean = 0.034 mode = 0.03 ~ 0.05 RMSD = 1.97 SD = 1.72 skewness = -0.8 kurtosis = 1.4

1E-2

1E-1

He/p ratio

d) Figure 5. (Continued)

1E+0


95

Occurrence number

1E+4

median = 2. mean = 2. mode = 1.8~2.2 RMSD = 1.85 SD = 1.74 skewness = -0.01 kurtosis = 1.7

1E+3

1E+2

1E+1

1E+0 1E-2

−2σ 1E-1

+2σ

1E+0

1E+1

Pd, nPa

e)

Occurrence number

1E+4

median = 0.43 mean = 0.44 mode = 0.37~0.49 RMSD = 2.0 SD = 1.92 skewness = 0.08 kurtosis = 1.3 −3σ +3σ

1E+3

1E+2

1E+1

1E+0 1E-3

1E-2

1E-1

1E+0

1E+1

2 Sk, erg/cm s

f) Figure 5. Statistical distributions of the solar wind parameters represented in logarithmic scale for time interval from 1963 to 2007: (a) proton density, (b) proton temperature, (c) SW velocity, (d) He/p ratio, (e) dynamic pressure Pd, and (f) kinetic energy flux density Sk. Fitting by lognormal distribution function is shown by dashed line for good fit or by dotted line for poor fit. Vertical thin dashed lines restrict the best-fit intervals.

96


A characteristic feature of the solar wind density within the 2-σ interval is an anticorrelation with the SW velocity such that fast streams originating mainly in coronal holes in average have lower density than dense slow SW originating around coronal streamers [Ipavich et al., 1998]. Beyond of the 2-σ interval, the proton density distribution deviates from the lognormal PDF such that the wings of distribution become less steep. At small values, the 2-σ level restricts densities smaller than 1 cm-3. Interplanetary structures with very small proton density are associated with transient SW structures, in particular, expanding ejecta and post-shock flows [Richardson et al., 2000]. Most prominent deviation from the lognormal PDF is revealed at extremely small densities of n2106 K. Such high temperatures are observed downstream of very strong interplanetary shocks [Skoug et al., 2004]. They are far exceed those predicted from empirical relationship between the temperature and speed [Lopez and Freeman, 1986]. The extremely high temperature is a result of conversion of the kinetic energy of the interplanetary disturbance into thermal energy of the shocked gas. Hence they are generated by such extremely fast SW transients as ICMEs. From the above we can see that the thermodynamic properties of SW plasma are related with the SW velocity V. The statistical distribution of the SW velocity is different from the lognormal PDFs (see Figure 5c). The distribution has a relatively large positive skewness. The most probable of ~380 km/s is shifted toward lower velocities relative to the median of 420 km/s. In the linear scale (not shown), the distribution is even far from the normal PDF, because in that representation the mean value of 443 km/s differs very much from the median of 420 km/s and from the most probable of 360 ~ 380 km/s. In the range from 300 km/s to ~700 km/s the statistical distribution has a very wide peak, which contains more than 95% of the total statistics of 265699 hourly averages. That wide peak is formed by various kinds of the solar wind from slow plasma streams in the heliospheric current sheet to fast streams from the coronal holes [e.g. Smith, 2001; McComas et al., 2003]. Note that the speed of fast streams correlates well with the size of coronal holes located near the central solar meridian [Veselovsky et al., 2006; Vrsnak et al., 2007]. It is interesting that the distribution extends smoothly from the peak of most probable to very high speeds of >800 km/s. Those fast SW streams are related to fast interplanetary transients, such as ICME and other eruptive events. Note that the highest SW speed of more than 2000 km/s was observed in the interplanetary sheath region leading by extremely fast ICME [Skoug et al., 2004]. The number of events with slow SW decreases abruptly at velocities below 300 km/s. That deficiency of very slow SW might be due the “sweep-away” effect, which was discussed above in regard to deficiency of very low SW temperatures. It is difficult to interpret the extremely slow SW speeds of ~200 km/s. Some of those events correspond to intervals of extremely low SW density. Others might be due to unaccounted encounters to the magnetosheath or comet tails [Baker et al., 1986; Oyama et al., 1986]. Further studies of that subject are required.


98

Table 2. Average values of the fluxes for the solar wind at the Earth orbit during 1963-2007.

Physical quantity

Formula

Mean value

Mass flux density

J = m p DV

4.0⋅10-16 g/cm2⋅s

Momentum flux density (dynamic pressure)

Pd = m p DV 2

2.0⋅10-8 erg/cm3 (nPa)

Kinetic energy flux density

Sk =

1 m p DV 3 2

Sp =

1 2 m pV g DV , 2

where

Vg = 618 km / s

Enthalpy flux density for protons

St =

5 nTV 2

Magnetic energy flux density

B2 Sm = V 8π

Potential energy flux density

0.44 erg/cm2⋅s

1.7 erg/cm2⋅s

6.8⋅10-1 erg/cm2⋅s

6.1⋅10-3 erg/cm2⋅s

Based on the key plasma parameters, we calculate average physical numbers characterizing the SW plasma flow at the Earth orbit (see Table 2). As we have found, most of the SW parameters have better representation in logarithmic scale, where their statistical distributions are very close to the lognormal PDF. The average values of physical numbers from the Table 2 have been also calculated in the logarithmic scale, i.e. those are geometric mean. In calculation we take into account that the SW density D is contributed by both protons with atom mass A=1 and helium ions with atom mass A=4.

D = n(1 + 4 ⋅ He / p) ,

(12)

where n is concentration of protons per cubic centimeter and He/p is a ratio of helium content to proton concentration. Here we suppose that the speed of helium ions is equal to the speed


99

of protons. That assumption is reasonable because the average difference between the He and proton speeds was found in the SW observations of only about 10 km/s [Ogilvie et al., 1982]. Statistical distribution of the He to proton ratio is presented in Figure 5d. The shape of distribution is different from both lognormal and normal PDF. The skewness and kurtosis are relatively large. Helium to proton ratio is averaged about 0.04 and varies from 10-3 to ~0.3. In Figure 3c we can see that the data coverage for the He/p is poor. There are no data before 1970. More-less regular measurements started only in 1998. As a result, the He/p is known only for less than 50% of measurements in 1963 to 2007 and, thus, the statistics is not very representative. Usually the data gaps are filled by the average value of 0.04. This assumption is very rough. The statistical distribution of He/p ratio has a long tail toward very small values of ~10-3. Note that the ratio can be even smaller but in the OMNI dataset, only three positions after decimal point were used to record that value. In average, the He/p ratio correlates with the SW velocity [Aellig et al., 2001]. Smaller He/p ratio is characteristic of the slow SW in the heliospheric current sheet and the ratio of >0.04 corresponds to fast streams from coronal holes [Borrini et al., 1981; McComas et al., 2003]. Very high ratios of >0.1 occur within the ICMEs and eruptive filaments [Borrini et al., 1982b; Burlaga et al., 1998; Skoug et al., 2004]. Interaction of the SW plasma with planetary atmospheres and magnetospheres as well as with interstellar gas is controlled mainly by such important parameter as SW dynamic pressure Pd. The dynamic pressure is contributed by both proton and helium ion population, and, hence it is calculated as follow

Pd = 1.67 ⋅ 10−5 DV 2

(13),

The pressure Pd and velocity V are expressed, respectively, in nPa and km/s. Figure 5e shows the statistical distribution of SW dynamic pressure. The distribution is fitted very well by the lognormal PDF within 2-σ vicinity of the median of 2 nPa, i.e. about 95% of statistics satisfy to lognormal distribution. The same properties of the dynamic pressure were revealed in previous studies of ~1 min averages of SW parameters measured by the ACE and Wind satellites, and of hourly averages from the OMNI data base [Dmitriev et al., 2002a; 2004; 2005c]. The distribution of Pd has zero skewness. However, pretty large positive kurtosis indicates to excess peakedness due to long tails of the distribution at small and high pressures. The tail at low pressures of 7 nPa is mostly associated with fast SW transient events, which are often accompanied with dense regions of plasma compression. We should emphasize that SW structures with very low and very high dynamic pressure occupy only less than 5% of total statistics. Statistical distribution of the kinetic energy flux density Sk presented in Figure 5f is very similar to the distribution of dynamic pressure. The distribution is fitted by the lognormal PDF within 3-σ vicinity of the median of 0.43 erg/cm2s, i.e. more than 98% of statistics are distributed lognormally. The skewness of distribution is zero and the kurtosis is relatively small. The moderate peakedness is due to excess of statistics at very small and very large magnitudes, which contribute only to less than 2% of statistics.

100


Interplanetary Magnetic Field Numerous studies are devoted to statistical properties of the IMF at various heliocentric distances and in various time scales. Most of studies note that statistical distribution of IMF intensity B is different from the normal PDF. Some authors consider the lognormal PDF as the best fit for the distribution of B [Burlaga and King, 1979; Burlaga and Ness, 1998; Veselovsky et al., 1998b; 2000a; Burlaga, 2001b; Dmitriev et al., 2005c]. However, Feynman and Ruzmaikin [1994] considering 3-hour averages, found that the statistical distribution of B is different from the log-normal, because of non-zero skewness toward the small values, and relatively large positive kurtosis, corresponding to larger peakedness relative to a normal distribution. Hartlep et al. [2000] propose another approach of the IMF distribution in a form of fixed mean and normally distributed components. In particular, they reveal very good correspondence with the observed IMF statistical distribution when the normal component magnitude distribution is axisymmetric about the mean field (which is mainly aligned with the Archimedean spiral) but admits a high degree of variance anisotropy, with parallel variance much less than perpendicular variance. On the other hand, Bieber et al. [1993] revealed that the amplitudes of the spectra of variations are comparable for the IMF components, respectively, in the north-south direction, perpendicular to the Archimedean spiral in the ecliptic plane, and parallel to the Archimede spiral. Figure 6a shows statistical distribution of the IMF intensity B represented in logarithmic scale. The distribution is very close to lognormal PDF within 2-σ and 1.5-σ deviations, respectively, toward low and high intensities relative to the average of 6 nT. So more than 95% of the statistics satisfy to the lognormal distribution. There are no any well-defined correlations of the magnetic field with other heliospheric parameters in that range. The skewness of distribution is relatively small. The positive non-zero kurtosis is due to pretty prominent wings, which exceed the lognormal PDF at very low and very high magnitudes and contribute less than 5% of total statistics. The range of very weak IMF intensities of 13 nT is observed in 4% of cases, which are characterized by wide variability of the SW parameters from very small to very large values. An excess of strong fields relative to the lognormal distribution was reported in several studies [e.g. Burlaga and Szabo, 1999]. There are various physical processes contributing to the long tail at large IMF magnitudes. It is well known that the magnetic field can be enhanced significantly inside the ICMEs [Burlaga et al., 1987; 2001; Owens et al., 2005]. It was found that the IMF intensity correlates well with the speed of ICME [Owens and Cargill, 2002]. The IMF is also enforced in the interplanetary sheath and other compressed regions formed due to interaction of high speed structures with the ambient SW [Burlaga and King, 1979; Borrini et al., 1982a; Bothmer and Schwenn, 1995; Dal Lago et al., 2001; Owens et al., 2005].


101

Occurrence number

1E+5 1E+4 1E+3 1E+2

−2σ

1E+1

median = 5.9 mean = 6.0 mode = 5.5~6.6 RMSD = 1.55 SD = 1.48 skewness = 0.12 kurtosis = 0.85 +1.5σ

1E+0 1

10

IMF B, nT

a)

Occurrence number

1E+4

median = 4.6 mean = 4.5 mode = 4.3~4.7 RMSD = 1.74 SD = 1.55 skewness = -0.78 kurtosis = 2.8

1E+3

1E+2

1E+1

−1.2σ

+1.4σ

1E+0 1

10

IMF Bxy, nT

b) Figure 6. Statistical distributions of the IMF for time interval from 1963 to 2007 in logarithmic scale: (a) strength B, (b) projection of the IMF vector onto the ecliptic plane Bxy. Dashed curves depict the best fit of the B and Bxy by the lognormal PDF. Vertical thin dashed lines restrict the best-fit intervals.

102


The vector of IMF can be presented as a sum of three orthogonal components Bx, By, and Bz. In the GSE coordinate system, X-axis is pointed to the Sun, Y-axis lies in the ecliptic plane and directed duskward, and Z-axis is perpendicular to the ecliptic plane and directed northward. Projection of the IMF vector to the ecliptic plane Bxy is simply presented as the r r r vector sum of Bx and By components: Bxy = Bx + B y , and the magnitude of Bxy is equal to

r Bxy = Bx2 + By2 . Statistical distribution of the Bxy magnitude is presented in Figure 6b. It is close to the lognormal PDF with average of 4.6 nT within a narrow interval from –1.2 to 1.4 standard deviations, i.e. ~80% of the total statistics of Bxy satisfy to lognormal distribution. The distribution is slightly skewed toward small values. That skewness is mainly due to very prominent tail extending to small magnitudes. The tail together with excess of large values of Bxy leads to a pretty large positive kurtosis and large RMSD=1.74 relative to the standard deviation of 1.55. The tail at large magnitudes of Bxy (>10 nT) has apparently the same nature as the tail of high IMF intensities. The abundant statistics at small values of Bxy (500 counts (red). The top and right histograms represent statistical distributions of the Bx and By component, respectively. The distributions of Bx and By components correspond to predominant orientation of the IMF vector along the Archimedean spiral, which has an angle of ~135° relative to the sunward direction (pointed by positive Bx).

The two-dimensional distribution of the components Bx and By has a long ridge corresponding to a predominant orientation of the Bxy vector along a line, which is inclined on ~-45° relative the X-axis. The same predominant orientation of the IMF was reported earlier [e.g. Luhmann et al., 1993; Veselovsky and Tarsina, 2001]. This orientation is very close to the Archimedean spiral. In the solar equatorial plane the angle α between the Archimedean spiral and the X-axis is calculated as follow:

⎛ 2πr ⎞ ⎟⎟ , ⎝ τ sV ⎠

α = tan −1 ⎜⎜

(14)

104


where r is heliocentric distance, V is the SW velocity and τs=25.4 days is the sidereal rotation period of the Sun at the equator. Taking distance r=1.5 108 km and median SW velocity of 420 km/s directed antiparallel to the X-axis, we obtain α=-45° at the Earth orbit. We should emphasize that the predominant orientation along the Archimedean spiral is revealed even at very large Bxy magnitudes of >15 nT. Such strong magnetic field in the ecliptic plane can not be only the result of field line stretching. The ecliptic magnetic field described by the ideal Parker spiral model is given by

Bxy = B0 a 2 r −1 r −2 + Ω 2 /V 2

(15)

were a is the radius of the solar source surface. Using this equation we simply estimate that variations of the solar wind velocity with average of 420 km/s and dispersion of ~1.25 (see Table 1) cause the relative variation of ~1.24 in the Bxy magnitude. That variation is apparently smaller than logarithmic RMSD of 1.74 and standard deviation of 1.55, which we find from the statistical distribution of the Bxy (Figure 6b). Hence it is rather possible that significant part of the Bxy variations is originated from solar sources. Variations of the Archimedean spiral angle from α~-55° in slow SW (V=300 km/s) to α~-31° in the fast SW (V=700 km/s) also contribute to a pretty large dispersion of the ridge of most probable values in the two-dimensional distribution P(Bx,By) presented in Figure 7. Another important heliospheric phenomenon contributing to the dispersion of magnetic field components is large-amplitude Alfvén waves propagating outward from the Sun [Belcher and Davis, 1971; Tsurutani and Gonzalez, 1987; Tsurutani et al., 1995]. They have a broad wavelength range up to 5106 km and beyond, which corresponds to period of hours. Most Alfvén waves in the interplanetary medium are likely the undamped remnants of waves generated at the Sun. They occur mainly in high-speed SW streams and on their trailing edges where the velocity slowly decreases. In the Alfvén waves, the magnetic field orientation varies such that one IMF component increases and another decreases. As a result, those variations can contribute a lot to the statistics at both very small and large values of Bxand By. The largest amplitude Alfvénic fluctuations of ~10 nT in the IMF component are observed in the compression regions at the leading edges of high-velocity streams, i.e. in the CIR region. The Alfvén waves are one of the sources of IMF fluctuations perpendicular to the ecliptic plane, i.e. variations of the Bz component, which statistical distribution is presented in Figure 8a. The distribution has a zero skewness and can be fitted well by a normal PDF within 2-σ interval (i.e. ±4.18 nT) around the average of 0 nT. However the RMSD of 3.1 nT is much larger than the standard deviation SD of 2.1 nT, because of presence of very prominent tails, which contain about 13% of the total statistics. Because of those tails the kurtosis is positive and very large. The large peakedness of the Bz distribution is also reported by [Feynman and Ruzmaikin, 1994]. The excess of large Bz magnitudes can be explained by the Alfvén waves only partially. Large Bz is generated due to compression in the CIR regions and in the interplanetary sheaths. In the latter case the Bz can achieve extremely high values but for a short time. The long-duration large and extremely large Bz occurs in the ICME and as a result of interaction between the ICME and other SW structures [Bothmer and Schwenn, 1995; Dal Lago et al., 2001].


Occurrence number

1E+4

1E+3

105

median = 0. mean = 0. mode = -0.6~1.5 RMSD = 3.10 SD = 2.09 skewness = -0.01 kurtosis = 9.1

1E+2

1E+1

−2σ

+2σ

1E+0 -40

-20

0

20

IMF Bz, nT

a)

Occurrence number

1E+5 1E+4 1E+3

median = 0. mean = 0. mode = -0.4~0.2 RMSD = 1.6 SD = 1.0 skewness = -0.1 kurtosis = 23

1E+2 1E+1

+2σ

−2σ 1E+0 -30

-20

-10

0

10

20

Ey, mV/m

b) Figure 8. Statistical distributions of (a) IMF Bz component and (b) Y-component of induced interplanetary electric field Ey for time interval 1963 to 2007. Dashed curve depicts the fitting by normal PDF. Vertical thin dashed lines restrict the best-fit intervals.

30


106

The IMF Bz and induced interplanetary electric field V×B play a key role in transmission of the SW energy into the Earth’s magnetosphere and hence control the system of magnetospheric currents [Burton et al., 1975; Akasofu, 1979; Iijima and Potemra, 1982; Tsyganenko, 2002a,b; Tsurutani et al., 2004]. Geoeffective Ey component of the induced electric field is defined as follow:

E y = 10−3Vx ⋅ Bz

(16)

Here the radial component of the velocity V is negative and expressed in km/s, Bz in nT and Ey in mV/m. Note that in this case the IMF component Bz is represented in the GSM coordinate system, which is related to the orientation of the Earth dipole axis projection to YZ plane. In the GSM system the Z component is contributed mainly by the IMF Bz and partially by the By components represented in the GSE coordinate system. Statistical distribution of the induced electric field Ey is presented in Figure 8b. The distribution is similar to one of the Bz (Figure 8a). It is well fitted by the normal PDF within 2-σ interval from –2 to 2 mV/m around the zero average. The distribution is symmetrical relative to the mode (skewness k3=0). The kurtosis is large because of great excess of large Ey magnitudes, which form prominent wings extending up to extremely high values of ~30 mV/m. As a result only 88% of the statistics at relatively low Ey magnitudes are distributed normally. The wings are contributed by both the excess of large intensities of the IMF Bz (see Figure 8a) and the abundant statistics of the fast SW streams (see Figure 5c). Note that the strongest magnitudes of Ey occur in extremely fast interplanetary transients (ICME and related sheath regions), which often contain very strong IMF Bz. Burton et al. [1975] found a criterion for the onset of geomagnetic storms: a storm starts when the Ey is larger than 0.5 mV/m. Using the statistical distribution of Ey we can find that the criterion is satisfied in 30% of cases. So about one third of time the magnetosphere stays under magnetic storm conditions.

Relevant Physical Quantities Using the measured parameters of SW and IMF, we calculated various quantities characterizing average physical properties of the interplanetary medium at the Earth orbit and listed them in Tables 2, 3 and 4. In the previous sections we found that statistical distributions of all measured parameters of the solar wind and IMF intensity are very close to lognormal PDF. It is easy to show that the lognormal distribution is multiplicative, i.e. multiplication/division of two random variables distributed log-normally has also lognormal distribution. As an example we can indicate the log-normally distributed SW dynamic pressure Pd. Hence physical quantities being a multiplication of log-normally distributed measured parameters should be represented in the logarithm scale. So we calculate average logarithms of the physical quantities (Equation 8).


107

Table 3. Mean heliospheric plasma conditions at the Earth orbit during 1963-2007. Physical quantity

Formula

Mean value

VA =

B 4π nm p

56.8 km/s

cS =

5T 3m p

33.7 km/s

Alfvèn-Mach number

MA =

V VA

7.7

Sonic Mach number for protons

MS =

V cS

13.

Gas-kinetic proton pressure (Thermal proton pressure)

Pt = nT

Alfvèn velocity

Sonic velocity for protons

.62⋅10-10 erg/cm3 (10-2 nPa)

Magnetic pressure

Pm =

B2 8π

1.4⋅10-10 erg/cm3 (10-2 nPa)

Proton gas-kinetic to magnetic pressure ratio

βp =

8π nT B2

0.43

Coulomb collision time for electrons

τ e ≅ 10 −2 Te3 / 2 n −1

~9.9⋅104 s

Coulomb collision time for protons

τ p ≅ 0.6Tp 3 / 2 n −1

~2.9⋅106 s


108

Table 4. Main plasma characteristics calculated for mean heliospheric parameters at the Earth orbit during 1963-2007. Physical quantity

Formula

Mean value

1.30⋅105 s-1

Plasma frequency

4π ne 2 ω0 = me

Electron cyclotron frequency

ω ce =

eB me c

1.04⋅103 s-1

Proton cyclotron frequency

ω cp =

eB mpc

0.56 s-1

Upper hybrid frequency

ω h1 = ω 0 2 + ω ce 2

Lower hybrid frequency

ω h 2 = ω cpω ce 1 / 2

Mean thermal speed of protons

3T Vp = mp

Larmor radius for protons

(

(

rp =

Vp

)

)

1/ 2

≈ ω0

1.30⋅105 s-1

24.1 s-1

45.8 km/s

81.8 km

ω cp

Average values of the energy, momentum and mass fluxes for the SW are shown in Table 2. Note that here we consider SW density D which accounts the helium contribution (Equation 12). One can see that the largest energy flux density is carried in the shape of potential and kinetic energies of the solar wind. The density of enthalpy (thermal) and magnetic energy fluxes are smaller on about 2 orders of magnitude. The total energy flux density of ~2.3 erg cm-2 s-1 amounts only a small portion of the total energy flux density emitted by the Sun in the form of electromagnetic radiation [Veselovsky et al., 1999]. Mean heliospheric plasma and IMF quantities are listed in Table 3. In the present case we use only proton concentration n and temperature T in the solar wind. The neglect of helium contribution leads to ~10% overestimation of the Alfvèn speed, while the Alfvèn Mach number is underestimated on ~10%. Other plasma quantities such as the sonic speed cs, sonic Mach number Ms, gas-kinetic pressure Pt and plasma β depend strongly on electron temperature, which is not available in most cases.


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The electron temperature Te varies in very wide range from ~5104 to ~106 K, and it has only very weak correlation with the proton temperature [Newbury et al., 1998; Salem et al., 2003]. It was found that in average the electron to proton ratio Te/T varies from 0.5 in the fast wind with velocities of ~700 km/s to ~4 in the slow solar wind. The average electron temperature is ~1.4105 K, i.e. almost two-time higher than the average proton temperature of 8.5104 K (see Table 1). Hence neglect of the electron temperature may lead to ~50% underestimation of the sonic speed cs and 50% overestimation of the sonic Mach number Ms. The magnitudes of gas-kinetic pressure Pt and plasma β might be about two-time underestimated. That is only rough estimation, because of the absence of electron temperature data. From Table 3 we can conclude that in average the SW flow at the Earth orbit is supersonic (Ms>1) and superalfvènic (Ma>1). Interaction of such SW with the magnetosphere obstacle causes generation of fast magnetosonic wave enveloping the magnetosphere, or socalled bow shock [e.g. Spreiter et al., 1966]. The Alfvènic and sonic Mach numbers and plasma β are the key parameters controlling the bow shock formation, i.e. conditions for SW flow about the magnetosphere [e.g. Dmitriev et al., 2003]. Statistical distributions of dimensionless quantities Ma, Ms and β are presented in Figure 9. As one can see, those distributions can be well fitted by a lognormal PDF as reported before by Dmitriev et al. [2003]. Similar behavior was found with 1 min data [Mullan and Smith, 2006].

Occurrence number

1E+5 1E+4

median = 8.4 mean = 8.4 mode = 8.~9.4 RMSD = 1.54 SD = 1.44 skewness = 0.03 kurtosis = 1.7

1E+3 1E+2 1E+1

−1.7σ

+1.7σ

1E+0 1E+0

1E+1

Ma

a) Figure 9. (Continued)

1E+2


110

Occurrence number

1E+4

median = 12.7 mean = 13. mode = 11.~13.8 RMSD = 1.35 SD = 1.3 skewness = 0.57 kurtosis = 1.3

1E+3

1E+2

1E+1

+1.2σ

−2σ 1E+0 1E+1

Ms

b)

Occurrence number

1E+4

1E+3

median = 0.48 mean = 0.43 mode = 0.44~0.65 RMSD = 2.61 SD = 2.12 skewness = -0.92 kurtosis = 2.5

1E+2

1E+1

+4 σ

−1.75 σ 1E+0 1E-3

1E-2

1E-1

1E+0

1E+1

beta

c) Figure 9. Statistical distributions of the dimensionless quantities in logarithmic scale for time interval 1963 to 2007: (a) Alfvén-Mach number Ma, (b) Sonic Mach number Ms, and (c) thermal to magnetic pressure ratio β. The distributions are fitted well by the lognormal PDF shown by dashed line. Vertical thin dashed lines restrict the best-fit intervals.


111

The distribution of Alfvèn Mach number (Figure 9a) is very close to the lognormal PDF within 1.7-σ interval around the average of 8.4 that contains ~95% of total statistics. The distribution has zero skewness and relatively large positive kurtosis, which is caused by abundant statistics at small and large Ma values. From analysis of statistical distributions of the SW velocity, density and IMF intensity, we can find that the tail of relatively small values of Ma can be contributed by relatively small SW densities and/or strong IMF. Such conditions often occur inside ICMEs. It is important to note the excess of extremely small values of Ma, which can be sometimes less than 1. Correction to the He abundance helps a little. Hence in some very rare cases the SW can be subalfvènic. Usmanov et al. [2005] have studied this problem and find that events of very low Alfvèn Mach number at the Earth orbit are associated mainly with extremely low SW density (10 nT. On the other hand, the extremely high Ma can occur inside the magnetic holes [Zurbuchen et al., 2001]. Contrary to the Ma, the sonic Mach number Ms is always larger than 1, as we can see from its statistical distribution in Figure 9b. About 92% of the Ms statistics is fitted well by the lognormal PDF in the range from 5 to 20 with average of ~13. The events with very low Ms of 2 years. In contrast to the Bx and By, there are no 27.3-day and 13.5-day periodicities in Bz component and only harmonics of 9.25 days and 5.75 days are presented [Mursula and Zieger, 1996]. That is a manifestation of very high variability of the IMF Bz within even half of the solar rotation. The dominant periodicities of IMF Bz are 268 days (0.73 year) and 1.2 years. A broad peak near 250-285 days was revealed from power spectral analysis of cosmic-ray intensity during the period 1964-1995 [El-Borie and Al-Thoyaib, 2002]. The origin of 0.73-year periodicity is still unclear and hence that should be a subject of future investigations. The period of 1.2~1.4 years was revealed in the dynamics of Bz by different spectral methods [Paularena et al., 1995; Szabo et al., 1995]. This variable period was discussed above in the context of the solar wind velocity variations. The Ey component is characterized mainly by periods of ~14 days, 28 days, 1 year 1.2 years, and 1.4 years, which inherit partially from the periodicities in solar wind velocity and IMF Bz. The dominant periodicity of Ey is characterized by a broad peak at ~28-day period, which is apparently associated with the solar synodic period. The solar cycle periodicities of >2 years vanish in the Ey variations because of high variability of the Bz.

Periodicities of Dimensionless Parameters Periodograms of the plasma β, sonic and Alfvén Mach numbers are shown in Figure 13. The parameters β and Ms have very similar periods: solar synodic period with harmonics (27 days, 13.5 days and 9 days), annual and semiannual variations inherit from the dynamics of solar wind velocity and temperature (see Figure 11a). However the solar cycle variations (>2 years) in plasma β and Ms are slightly different. Comparing with Figure 11 we can find that the periodicities in the sonic Mach number are mostly related to the solar wind plasma variations with periods of 5-years and ~9.8 years. The periodicity of 2.5 years might be a harmonic of the 5-year period. The variations in plasma β are rather related to the dynamics of IMF intensity B (see Figure 12a) with periods of ~5.1 years and 10.3 years. It is interesting that the periodicities of Alfvén Mach number Ma (see Figure 13b) are practically same as the characteristic periods of sunspot numbers (see Figure 10), excepting the period of 131 days. From Table 3 we can see that the number Ma is a complex parameter of solar wind velocity, proton density and IMF B. Comparing Figures 11a, 11b and 12a, we can see that those parameters have pretty different periodograms. Perhaps interference of different periodicities leads to degeneration of the variations into the basic harmonics of three main periodicities: solar synodic period, annual period of the Earth orbital rotation, and sunspot cycle.

122


4. Solar Cycle Variations Solar cycle variation of heliospheric parameters is a manifestation of various solar sources of the solar wind and IMF operating at different phases of the solar cycle [e.g. McComas et al., 2003]. It is widely accepted that the solar coronal holes is a main source of the solar wind during declining phases [e.g. Tsurutani et al., 1995]. Transient events form the solar wind at solar maximum [e.g. Cane and Richardson, 2003]. Slow and dense solar wind streams of heliospheric current sheet dominant in the ecliptic plane during solar minimum [e.g. Smith, 2001]. As a result, statistical properties of the heliospheric parameters vary within the cycle such that not only the average and dispersion but also the shape of statistical distributions can change [e.g. Dmitriev et al., 2000; 2005c]. We study solar-cycle variations using a method of running histogram [Dmitriev et al., 2002a; 2005c]. In this method a histogram of statistical distribution is accumulated within a relatively narrow time window, which is consequently shifted with a short time step. As result, a long time interval of measurements is represented by a sequence of running statistical distributions of the measured parameter. For each distribution we calculate running mode, mean and dispersion (RMSD). The choice of running time window and step depends mainly on data sampling. The variations of statistical distribution can be represented more brightly when we take into account the characteristic periodicities of analyzing parameter. In the previous section we find that practically all heliospheric parameters have prominent variation with solar synodic period of 27.3 and annual variation. We choose the step of 27 days and time window of 189 days. The time interval of 189 days is approximately equal to 7 solar synodic periods and also corresponds to the half-year period. By this way we eliminate shorttime variations associated with solar rotation, but the annual and longer variations can be analyzed. Figure 14 shows the running histogram of sunspot number. This parameter demonstrates very high variability during the four last solar cycles (Figure 14). The running mean varies in a wide range and during solar maxima and minima exceeds 1-σ deviation from the 40-year average of ~50. Large statistically significant variations during the cycle have been also found for the radio emission flux of the Sun at the wave length 10.7 cm and for the total solar irradiance [Dmitriev et al., 2005c]. The dispersion of sunspot number is lowest during solar maximum. A short-time enhancement of the dispersion coincides with decrease of sunspot number in the Gnevyshev gap, which corresponds to polarity reversal of the solar magnetic field in 1969, 1980, 1990 and 2001. The running dispersion is highest during rising and declining phases, while the solar cycle minima are characterized by moderate dispersion.

Solar Cycle in Plasma Parameters Solar-cycle dynamics of the statistical distributions of SW plasma parameters is presented in Figure 15. All cyclic variations in the running mean are not very large and lie inside 1-σ corridor around the averages. Specific cyclic patterns of the variations can be discernible for all plasma parameters. Dmitriev et al. [2002b] demonstrate that the dynamics of solar wind plasma during rising and declining phases are systematically different such that the cycle variation in solar wind parameters represents hysteresis behavior in dependence on the sunspot number.


123

RMSD

2.5 2.0 1.5 1.0

Figure 14. Running histogram of statistical distribution of sunspot number W for time interval from 1963 to 2007. Occurrence number in the running histograms is indicated in rainbow palette from violet (minimum) to red (maximum). Top panel shows the running dispersion of distribution. Running mean and running 1-σ deviation are indicated, respectively, by thick and thin black curves. The average is indicated by horizontal black solid line. The 1-σ corridor is restricted by horizontal black dotted line.

Most prominent variations with pretty well organized pattern are revealed in the SW velocity (Figure 15a). Note that the statistical distribution of velocity is deviated from the lognormal PDF and hence the running averages can be different from running modes. One can clearly see that the variations in running average represent solar-cycle very roughly, because of very wide statistical distribution with long tails. Moreover, the running averages lose informative meaning because the running histogram often has two or even three peaks. The running mode of solar wind velocity is more representative. In Figure 15a we can distinguish a clear pattern of the both 11-year and 22-year cycles. The 22nd cycle in velocity resembles the 20th cycle as reported before [e.g. Cliver et al., 1996]. Declining phases of both cycles contain long-duration intervals of fast solar wind with very high dispersion. Detailed comparison reveals that the cycles 21st and 23rd do not have so prominent velocity enhancements as the cycles 20th and 22nd. However, the common pattern of velocity variations repeats from cycle to cycle. The slow solar wind streams with velocity > s0, the maximum apparatus speed is

Vmax = 2a0 s0 .

(5)

Alexander Bolonkin

362

The proposed solar sail without a load reaches a maximum speed of 295 km/s ≈ 300 km/s whereas the conventional sail without a load reaches only 55 km/s. With a load of 100 kg the new sail reaches a speed of 116 km/s. If the apparatus makes a maneuver and starts at s0 = 30 million km from the Sun (a = 25a0) the maximum speed reaches 660 km/s. We can find the tangent speed of the petals (aluminum plates) around the charged ball from the following equations:

F =k

qQ mv 2 Q ρSd k = , q= , m= , v=Q , 2 r r N N ρSrd

(6)

where F – the electrostatic force between the central ball and the petal [N], k = 9×109 – electrostatic coefficient, q – charge of a petal [C], Q – charge of the ball [C], r – distance between the petal and the center of ball [m], m – mass of a petal [kg], v – tangent speed of a petal (around the ball) [m/s], N – number of petals. If ρ = 2700 kg/m3 (for aluminum), S = 106 m2 , r = 600 m, d = 10–8 m, then v = 745Q. For Q = 0.01 C the speed v = 7.45 m/s.

Figure 10. Possible form of Solar Sail. Credit NASA/JPL, 63K

2. Estimation of the Initial Expenditure of Electrical Energy to Charge of the Ball The ball has to be charged with electrical energy of high voltage (millions of volts). Let us estimate the minimum energy, when the charged device has 100% efficiency. This energy

Electrostatic Solar Light-Wind Sail

363

equals the work done to move of the ball charge to infinity. It can be computed using the equation

Wb =

Q2 a2E a a3E 2 , Q= , C = , Wb = , k k 2C 2k

(7)

where Wb – ball charge energy [J]; C – ball capacitance [F]; Q – ball charge [C]; a – radius of ball [m]; E – electric intensity [V/m]. For our charge Q = 0.01C and electrical intensity (safe for a vacuum) E = 108 V/m the required ball radius is a = 0.95 m ≈1 m [equation (7)], the required charge energy is Wb = 0.154 kWh [equation (7)]. This energy is not great, and it may be returned when the ball discharged by emitting the charge into space using a sharp edge.

3. Estimation of the Ball Stress, Cover Thickness and Ball Mass The ball has tensile stress from the like electric charge. We can find the ball stress and the necessary thickness of the ball cover. If the ball is in a vacuum and the ball charge, Q, is constant, the internal force within the ball is

f =

∂Wb Q2 a kQ 2 1 = 9 × 109 , Wb = , Wb = , C= , k= , ∂a k 2C 4πε 0 2a

kQ 2 a2E , f =− 2 , Q= k 2a

f

(aE )2 , =−

(8)–(9)

2k

where f is the ball’s internal tensile force [N]; Wb is the charge energy [J]; C is the capacity of the ball as a spherical capacitor [F]; E is electric intensity [V/m]. The internal pressure of the ball is then

p=

f , Sb = 4πa 2 , Sb

p=

E2 , 8πk

(10)

where p is internal pressure [N/m2], Sb is ball surface area [m2]. The thickness of a ball cover is

π a 2 p = 2π aδσ , δ =

ap aE 2 , δ= , 2σ 16π kσ

(11)

where δ is the cover thickness [m]; σ is the safe cover stress [N/m2]. The ball mass is then

M s = S bδγ , S b = 4πa 2 , M s =

a 3 E 2γ , 4kσ

(12)

364

Alexander Bolonkin

where Ms – ball (sail) mass [kg]; γ – ball cover density [kg/m3]; σ – safe stress level of the ball cover [N/m2]. For our case where a = 1 m, E = 108 V/m, γ = 1800 kg/m3, σ = 109 N/m2, the mass of the ball is Ms = 0.5 kg [equation (12)].

4. Technology of the thin plate-petals The thin plate-petals can be produced by electrolytic or vapor precipitation.

5. Design of Artificial Moon The proposed idea may be used to construct on artificial Moon when the light pressure equals the Earth’s gravity and a gigantic electrostatic mirror illuminates the Earth’s surface.

6. Estimation of the Trust May be computed by [5] or [1] Ch.13. Other electrostatic applications are offered in the References [1–9].

Possible Form of Solar Sail

Figure11. NASA Solar Sail

Electrostatic Solar Light-Wind Sail

365

Figure 12. Flying away on a wing and a prayer: The Canadian Solar Sail Project for a proposed race to the moon in 1992 in honor of the 500 year anniversary of Columbus coming to America.

References (Reader can find part of these articles at the author’s website: http://Bolonkin.narod.ru/p65.htm, http://arxiv.org, search term: “Bolonkin”, in the book "Non-Rocket Space Launch and Flight", Elsevier, London, 2006,488 pgs., and book “New Concepts, Ideas, Innovations in Aerospace, Technology and Human Sciences”, NOVA, 2008, 502 pgs.; “Macro-Projects: Environment and Technology”, NOVA, 2009, 536 pgs.) [1] [2]

Bolonkin A.A., “Non-Rocket Space Launch and Flight”, Elsevier, 2006, 488 pgs. Bolonkin A.A., “New Concepts, Ideas, and Innovation in Aerospace, Technology and Human Science”, NOVA, 2008, 400 pgs. [3] Bolonkin, A.A., Method of Stretching of Thin Film. Russian patent application #3646689/10 138085. 28 September 1983 (in Russian), Russian PTO. [4] Bolonkin, A.A., “Electrostatic Utilization of Asteroids for Space Flight”, 41 Propulsion conference, 10–12 July, 2005, Tucson, Arizona, USA, AIAA-2005-3857. [5] Bolonkin, A.A., Electrostatic Solar Wind Propulsion, 41 Propulsion conference, 10–12 July, 2005, Tucson, Arizona, USA, AIAA-2005-3653. [6] Bolonkin, A.A., “Guided Solar Sail and Electric Generator”, 41 Propulsion conference, 10–12 July, 2005, Tucson, Arizona, USA, AIAA-2005-3857. [7] Bolonkin A.A., “Electrostatic Levitation and Artificial Gravity”, 41 Propulsion conference, 10-12 July, 2005, Tucson, Arizona, USA, AIAA-2005-3365. [8] Bolonkin, A.A., “Radioisotope Space Sail and Electric Generator”, 41 Propulsion conference, 10-12 July, 2005, Tucson, Arizona, USA, AIAA-2005-3653. [9] Bolonkin A.A., “Macro-Projects: Environment and Technology”, NOVA, 2008, 420 pgs. [10] “Dispersion of light”, Big Soviet Encyclopedia Moscow (in Russian). [11] Kikoin I.K., Tables of physical values (directory). Moscow, 1975 (in Russian).



Short Communication C

SOLAR AND SOLAR WIND AB-SAIL

1

Alexander Bolonkin2 C & R, Brooklyn, NY, USA

Abstract The Solar and Solar Wind sail is a large thin film used to collect solar light and solar wind pressure for the moving of space apparatus. Any solar sail simultaneously is the solar wind sail because the light and solar wind have a same direction. The light (photons) and solar wind (protons and electrons) are adsorbed by a sail material. Unfortunately, the solar radiation pressure is very small, about 9 μN/m2 at Earth's orbit. The solar wind pressure is much less. However, the light and wind forces significantly increases up to 0.2 - 0.35 N/m2 near the Sun. The author offers his research on a new revolutionary highly reflective solar sail which performs a flyby (after a special maneuver) near Sun and attains a velocity up to 400 km/sec enabling reaching far planets of the Solar system in short time, and enabling escape flights out of the solar system. New, highly reflective sail-mirror allows avoiding overheating of the solar sail. It may be useful for probes close to the Sun as well as probes to Mercury and Venus.

Keywords: AB-solar sail, highly reflective solar sail, high-speed propulsion.

1. Introduction A solar and solar wind sail is a thin film reflector that uses solar energy for propulsion. The spacecraft deploys a large, lightweight sail which reflects light from the Sun (or some other source). The radiation pressure on the sail provides thrust by reflecting photons and braked solar wind. The solar radiation pressure is very small 6.7 Newtons per gigawatt. That equals 9.12×10-6 N/m2 at Earth's orbit (1 AU - Astronomical Unit = 150 million km) and decreases 1

This work was presented as Bolonkin’s paper AIAA-2006-4806 for 42 Joint Propulsion Conference, Sacramento, USA, 9-12 July, 2006. 2 Correspondence to: C&R, A.Bolonkin, 1310 Avenue R, #F-6, Brooklyn, NY 11229, USA, T/F 718-339-4563, [email protected], or [email protected], http://Bolonkin.narod.ru

368

Alexander Bolonkin

by the square of the distance from the sun. However, the solar light and solar wind pressure significently increases near the sun and not far above it can reach 0.2 - 0.35 (up to 0.4 on Solar surfice) N/m2.

Brief History of Solar Sail The conventional solar sail concept was first proposed by Friedrich Zander in 1924 [1] and gradually refined over the decades. The author proposed innovations and a new design of Solar sail in 1965 [2, 3], and theory was developed in [3] - [6]. The author offers a new revolutionary solar AB-sail. Its main distinction is very high reflectivity which allows the AB-sail to come very close to the Sun without great heating and to attain high light and wind forces and high speed. This innovation allows (main advantages only): 1) to achieve very high speed up 400 km/s; 2) an easily controlled amount and direction of thrust without need to turn a gigantic sail; 3) to utilize the solar sail as a power generator (for example, electricity generator); 4) to use the solar sail for long-distance communication systems.

Information about the Sun Radiation The pressure of light equals P = 2E/c (where E is energy of radiation, c is light speed (c = 3×108 m/s)). The solar light energy at Earth's orbit equals 1.4 kW/m2, but near a solar surface it reaches up to 64×103 kW/m2 (it increases 47 thousand times!). As the result the light pressure jumps up to 0.4 N/m2. The space apparatus can get significant acceleration (up to 80 m/s2) and high speed up to 400 - 500 km/s. Spectrum of Sun is presented in Figure 1. Note, the space mirror (sail) will not heat only if it reflects all solar spectrum (λ = 0.2 ÷ 3μm).

Figure 1. Spectrum of solar radiation. λ is the wavelength [0.25–2.5 μm, 250 – 2500 nm].

AB-Solar and Solar Wind Sail.

369

Brief Information about Solar Wind The Sun emits plasma which is a continuous outward flow (solar Wind) of ionized solar gas through out our solar system. The solar wind contains about 90% protons and electrons and some quantities of ionized α-particles and gases. It attains speeds in the range of 300–750 km/s and has a flow density of 5×107 – 5×108 protons/ electrons/cm2s. The observed speed rises systematically from low values a 300–400 km/s to high values of 650–700 km/s in 1 or 2 days and then returns to low values during the next 3 to 5 days (Figure 1, Ch.9). Each of these high-speed streams tends to appeal at approximately 27-day intervals or to recur with the rotation period of the Sun. On days of high Sun activity the solar wind speed reaches 1000 (and more) km/s and its flow density 109 – 1010 protons/electrons/ cm2s, 8–70 particles in cm3. The Sun has high activity periods some days each year. The pressure of the solar wind is very small. For full braking it is in the interval 2.5×10– 10 ÷ 6.3×10–9 N/m2. This value is double when the particles have full reflection. The interstellar medium also has high energy particles. Their density is about 1 particle/cm3.

2. Description and Innovations of Suggested Solar Sail Description of the offered light-magnetic sail The suggested AB space sail is presented in Figure 2. It consists of: A thin high reflection film (solar sail) supported by an inflatable ring (or other method), space apparatus connected to solar sail,; a heat screen defends the apparatus from solar radiation.

Figure 2. High reflective space AB-sail. (a) Side view of AB-sail; (b) Front view; (c) cross-section of sail surface; (d) case of non-perpendicular solar beam; (e) triangle reflective sail. Notation: 1 - thin film high reflective AB-mirror, 2 - space apparatus, 3 - high reflective heat screen (shield) of space apparatus, 4- inflatable support thin film ring, 5 - inflatable strain ring, 6 - solar light, 9 - solar beam, 10 - reflective sell, 11 - substrate, 12 - gap.

The thin film includes millions of very small prisms (angle 45o, side 3 - 30 μm). The solar light is totally reflected back into the incident medium. This effect is called total internal reflection. Total internal reflection is used in the proposed reflector. As it is shown in [5]

370

Alexander Bolonkin

Ch.12 the light absorption is very small (10 -5 ÷10 -7) and radiation heating is small (see computation section). Another possible design for the suggested solar sail is presented in Figure 3a. Here, the solar sail has concave form (or that plate is made like a Fresnel mirror). The sail concentrates solar light on a small control mirror 4. That mirror allows a redirected (reflected) solar beam to change value and direction of the sail thrust without turning the large solar sail. Between thin films 1, 8 there is a small gas pressure, which supports the concave form of reflector 1. Concentration of energy can reach 103 ÷ 104 times, temperature greater than 5000 oK. This energy may be very large. For the sail of 200×200 m, at Earth orbit the energy is 5.6×104 kW. This energy may be used for apparatus propulsion or other possibilities (see [5]), for example, to generate electricity, or even to flash a signal to greet amateur astronomers. The concave reflector may be also utilized for long-distance radio communication. The current conventional NASA design of solar sail is shown in Figure 3b. The trajectory of the high speed solar AB-sail is shown in Figure 4. The sail starts from Earth orbit. Then it is accelerated by solar light to up 11 km/s in opposed direction of Earth moving around Sun and leaves Earth gravitational field. The Earth has a speed about 29 km/s in its around Sun orbit. The sail will be subtracting additional 11 km/s from this to achieve a net velocity of 18 km/s. That braking slows it down and gravity then speeds it up; the sail moves Sunward. (trajectory 4). Near the Sun the reflector is turned for acceleration to get a high speed (up to 400 km/s) from a powerful solar radiation. The solar escape velocity is about 619 km/s. If AB sail makes revolutions around Sun, it can then reach speed of a 1000 km/s and leaves the Solar system with a residual speed of about 400 km/s. The suggested highly reflective screen protects the apparatus from excessive solar heating. Note, the offered AB sail allows us also to brake an apparatus very efficiently from high speed to low speed. If we send an AB sail to another star, it can brake at that star and became a satellite of the star, free to move around the local system on local ‘solar’ power, with no reaction mass required.

Figure 3a. Highly reflective solar AB-sail with concentrator. (a) side view; (b) front view. Notation: 1 highly reflective AB mirror (it may have a Fresnel form), 2 - space apparatus, 3 - highly reflective heat screen, 4 - control mirror, 5 - reflected solar beam, 6 - inflatable support thin film ring, 7 - inflatable strain ring, 8 - thin transparent film, 9 - solar beam.

AB-Solar and Solar Wind Sail.

371

Figure 3b. NASA solar sail. 94K. Credit NASA.

Figure 4. Maneuvers of AB solar sail for reaching a high speed: braking for flyby near Sun, great acceleration from strong solar radiation and flight away to far planets or out of our Solar system. Notation: 1 - Sun, 2 - Earth, 3 - Solar AB-sail, 4 - trajectory of solar sail to Sun, 5 - other planets, 6, 7 speed of solar sail.

3. Estimation and Computation 1. Light Pressure Is Calculated by Equation p = (1 + ρ )

E , for c

ρ = 1,

p=2

E c

(1)

where p is light pressure, N/m2; E is energy, J/m2; c = 3×108 m/s is light speed; ρ is reflective coefficient (ρ = 0 ÷ 1). At solar surface E = 64×103 kW/m2 and p = 0.4 N/m2. At Earth's orbit the E = 1,4 kW/m2 and p = 9 μN/m2.

Alexander Bolonkin

372

2. Temperature of Sail. The temperature of sail equals T = 100

4

γE cS (ε 1 + ε 2 )

(2)

where T is temperature, oK; E is heat flow, W/m2; γ is absorption coefficient of light energy, cS = 5.67 is coefficient, 0 < ε > H1) than the ring magnetic intensity of MagSail! It is correct for any charged beam that interacts with the MagSail. That means all research and computation (without taking into account the influence the solar wind or charged beam into MagSail) is wrong and basically worthless for all practical space exploration and exploitation applications. How can it happen that hundreds of researchers, professors at famous universities, audiences of specialists, members of scientific Conferences and Congresses, editors of scientific journals: "Journal of Propulsion and Power", (Editor V. Yang); Journal "Spacecraft and Rockets", (Editor V. Zoby), paid so little attention to student-level mistakes in many scientific publications and public presentations to scientific conferences? More over, the director NASA Institute for Advanced Concepts (NIAC) Mr. R. Cassanova awarded (totaling more than $1 million dollars!) to his close associate, professor R.M. Winglee (University of Washington) for pseudo-scientific work about MagSail.[1] # It is still happening because popular textbook authors continue to use as a reference frame the interaction between the strong magnetic field of particle accelerators and small amount of charged particles where we can neglect the influence of charged particles in the magnetic field of the accelerator. With MagSails, we have the opposite situation: The weak ring magnetic field and strong magnetic field of solar wind or charged beam. The influence of charged particles on the magnetic field is then paramount and can hardly be ignored!

Figure 4a. Sun magnetic field. 48K. #

Mr. Cassanova invented a new method of legal larceny of government money. He personally awarded taxpayerfunded money grants to his friends, protégés and other useful persons for mere promises of great discoveries and revolutionary developments in future in space sciences. In eight years of NIAC’s existence under him, Mr. Cassanova spent in excess of fifty millions dollars of taxpayer money in pseudo-scientific works, but has not presented to the public even one new researched scientific concept. The Scientific Committee of a famous organization, the CAGW (Citizen against Government Waste), awarded NIAC and Mr. Cassanova pseudoNobel prize-2005 and 2006[42]-[47].

Electrostatic MagSail

383

Theory of MagSail Below, the author suggests the correct theory of MagSail operation, which takes into consideration the influence of the solar wind flow into the ring magnetic field and allows an estimation of the drag of a MagSail like device (Figure 4). Let us to take the equations (2) in form: H1 =

I , R1

H2 =

V i , r= , ( q / me ) B 2r

R2 =

V

(q / m ) B ,

i = π R32 qN V ,

B = μ0 ( H1 − H 2 )

(3)

p

where mp is mass of positive particle, for proton mp=1.67×10-27, kg; R2 is rotate radius of positive particles (protons for Solar Wind), m; R3 is capture radius of positive particles, m.

Figure 4b. Magnetic field of ring. 9K.

Notice particularly the last equation (3). In this equation, the active term is summary magnetic intensity B! For getting the maximum solar wind drag the turn radius of heavy particles must be 90 degrees. Assume R = R1 = R2 = R3. We have 6 equations (3) and 6 unknown values. From set equations (3) we receive the estimation of the radius efficiency R: R2 =

me π q2 N

⎛ Iq 2 ⎞ ⎜ − ⎟ ⎜m V μ ⎟ 0 ⎠ ⎝ p

(4)

From (4) we get minimal ring electric currency I≥

2m pV

μ0q

(5)

Alexander Bolonkin

384

For average solar wind speed V = 400 km/s the minimal ring electric currency is I = 6.65×103 A. The solar wing drag, D, equals approximately

D = π R2mp N V 2

(6)

Results of computation are presented in figures 5 - 6. Look you attention: for receiving good drag we need in high electric current. For typical current I = 104 A (I = 10 kA) the efficiency radius R and drag D are small.

Figure 5. Radius efficiency of MagSail via ring electric current.

Figure 6. Drag of MagSail via ring electric current at distance from Sun equals 1 Astronomical Unit.


385

Offered Electrostatic MagSail (EMS) The conventional MagSail with super-conductive ring has big drawbacks: 1. It is currently difficult to place or build a gigantic (tens of km radius) ring in outer space. 2. It is difficult to insert and, maintain, unquenched, large amounts of energy into a superconductive ring. 3. A super-conductive ring needs a low temperature to function at all. The Sun heats all bodies in the Solar System to a temperature higher than the transition temperature of super-conductive materials. 4. The super-conductive ring explodes if the temperature is increased over critical value. 5. It is difficult to control the value of MagSail thrust and the thrust direction. The author offers new Electrostatic MagSail (EMS). The innovation includes the central positive charged small ball and a negative electronic equal density ring rotated around the ball (Figure 7).

Figure 7. Electrostatic MagSail. Notations: 1-Spaceship; 2-Positive charged ball; 3–electrical ring; 4solar wind; 5-EMS drag.

The suggested EMS has the following significant advantages in comparison with conventional MagSail: (1) (2) (3) (4)

No heavy super-conductive large ring. No cooling system for ring is required. Electronic ring is safe. The thrust (ring radius) easily changes by varying of the ball charge.

Alexander Bolonkin

386

Electrostatic Offered MagSail Theory Let us consider a method of estimation of electronic ring magnetic intensity in the electronic ring’s center [2]. We will take into consideration a repulsion of electrons from the electron ring (blocking the ball charge by the electronic ring) and relativistic speed of electrons. We will not take into consideration the diamagnetic property of the solar wind or charged beam because our purpose here is only to find the magnetic intensity from the electronic ring. The blocking the MagSail magnetic field by the particles flow the reader find in previous section (above). We also neglect the radiation of the rotary electronic ring because the ring is a symmetrical circle, has constant density and that does not emit synchronous radiation (this assumption needs further research. Synchronous radiation appears when electrons rotate in an outer magnetic field, the electron ring is unclosed or has non-constant density. In our case, the ring electric and magnetic fields are constant and do not emit energy in outer space). From equilibrium of the centrifugal and attraction forces we have MVe2 (Q − Q )Q Q = k 1 2 2 2 , M = me 2 , Q1 > Q2 , R R q

(7)

where M is mass of electron ring, kg; Ve is speed of electrons, m/s; R is ring radius, m; k = 9×109 is electrostatic constant; Q1 is positive charge of the central ball, C; Q2 is negative charge of the electron ring, C; me is mass of electron, kg; q = 1.6×10-19 is electron charge, C. The best relation between Q1 and Q2 is Q1 = 2Q2. Substituting this value into (7) we receive

⎛ q ⎞Q RVe2 I QV Ve2 = k ⎜⎜ ⎟⎟ 2 , Q2 = , H= , I = 2 e , B = μ0 H ( ) m R k q / m 2 R 2π R e ⎝ e⎠

(8)

where I is ring electric currency, A; H is magnetic intensity, A/m; B is magnetic intensity, T; μ0 = 4π10-7 is magnetic constant. Substitute the previous Eqs. (8) in the last equation (8) for B and use the formula for relativistic electron mass

B=

μ0 Ve3 V me0 μ c 3 (me0 / q ) β 3 , β = e , me = , B= 0 4π R k (q / me ) c 4π R k 1− β 2 1− β 2

(9)

where c = 3×108 m/s is light speed; me0 = 9.11×10-31 kg is electron mass at Ve = 0. Let us to add formula for estimation charge and radius of ball and substitute the known values into last equation (9). We received the final equations for estimation of MagSail size: B = 1.7 ⋅ 10 −3

β2 1 β3 B 1 β3 c2R 2kQ2 (10) = 1.36 ⋅ 103 , H= , Q2 = , a2 = 2 2 μ0 R 1− β R 1− β k (q / me 0 ) 1 − β 2 E0

where a is radius of ball, m; E0 is safety electric intensity at ball surface, V/m.


387

If the magnetic intensity into ring is constant, we can estimate the energy needed for starting of ring: I I S πR LI2 (11) , Φ = μ0 , W= H= S = IL, L = μ 0 = μ0 2R

2R

2R

2

2

where Φ is magnetic flux, Wb: L is ring inductance, Henry; S is ring area, m2; final equation in (11) W is energy, J. For conventional ring of MagSail having R = 50 km and I = 104 A the W = 5×106 J. The Eqs. (7) - (11) allow us to find the magnetic intensity of a MagSail for a given ring radius and electron speed (without the presence of solar wind or plasma beam), charge and radius of ball for a given electrostatic ball intensity, energy of a rotating ring, but they do not permit us to estimate a MagSail’s drag. We can estimate the drag of a conventional MagSail (see section above), to compute the drag of the electrostatic sail offered by author in [3] Chapter 18, but unfortunately we cannot do an estimate for the drag EMS at the present time. The trajectory of charged particles into both fields (magnetic and electric) are very complex.

Possible forms of MagSail, Space Ships and apparatus. (Credit NASA)

388

Alexander Bolonkin

References (Reader can find part of these articles at the web pages: http://Bolonkin.narod.ru/p65.htm, http://arxiv.org, search term: "Bolonkin", in the book "Non-Rocket Space Launch and Flight", Elsevier, London, 2006, 488 pgs., book “New Concepts, Ideas, Innovations in Aerospace, Technology and Human Science”, NOVA, 2008, 502 pgs., and book “Macro Projects: Environment and Technology”, NOVA, 2009, 536 pgs.)


389

[1-39] (Respectively). Some Manuscripts about MagSail published or presented to AIAA Conferences: (1) Winglee R.,M., at al. (4 co-authors), "Mini-Magnetospheric Plasma Propulsion. Tapping the Energy of the Solar Wing for Spacecraft Propulsion", Journal of Geophysical Reserach. Vol. 105, No. 6., 2000. (2) AIAA-2006-5257, (3) AIAA2006-769 (4 coauthors). (4) JSP 2006, Vol. 43, no. 3, (667-672). (5) AIC-05-C4.6.07. (6) AIAA-2005-4463 (6 coauthors). (7) AIAA-2005-4791. (8) AIAA-2005-4461. (9) AIAA-2004-3502 (7 co-authors). (10) AIAA-2003-4292 (8 co-authors). (11) IAC-035.6.06. (12) AIAA-2003-4886. (13) AIAA-2003-4292. (14) AIAA-2003-6201. (15) AIAA-2003-5226. (16) AIAA-2003-5227. (17) "Journal Propulsion and Power (JPP)" 2003, Vol.19, no 6 (1129-1134). (18) JPP, vol.20, No 4 (763-764). (19) JPP, vol.21, No. 5, 2005 (853-861)(4 co-authors). (20) AIAA-2004-3706. (21) AIAA-2001-840. (22) AIAA-2001-3517. (23) AIAA-1998-3403. (24) AIAA-1997-3072. (25) AIAA1997-3208. (26) AIAA-1997-2792 (3 co-authors). (27) Journal "Spacecraft and Rockets". 1994, Vol. 31, No. 2 (342 - 344). (28) AiAA-1992-3862. (29) AIAA-19912538. (30) AIAA-1991-3352. (31) AIAA-1990-2367. (32) AIAA-1990-1997 (6 coauthors). (33) AIAA-1990-3799. (34) AIAA-1989-2861, (35) JSR 1991, Vol. 28, no.2, (197-203). (36) AIAA-1990-1997. (37) AIAA-1990-2367. (39) AIAA-1990-3799. (39) AIAA-1989-2941. [40] Bolonkin A.A., "A Space Motor Using Solar Wind Energy (Magnetic Particle Sail)", IAF-0615. The World Space Congress, 28 August - 5 September 1992, Washington DC, USA. [41] Bolonkin A.A., Non-Rocket Space Launch and Flight, Elsevier, London, 2006, 488 pgs. [42] GO TO: http://auditing-science.narod.ru or http://www.geocities.com/auditing.science/ [43] GO TO: http://NASA-NIAC.narod.ru. [44] Johnson A., Space Research: Organizing for Economical Efficiency. Presented as paper AIAA-2006-7224 in Conference "Space-2006", 19-21 September 2006, San Diego, California, USA. [45] Johnson A., Space research: problems of efficiency. Journal "Actual Problems of Aviation and Aerospace System", No.1, 2007. http://www.kcn.ru/tat_en/science/ans/journals/rasj_cnt/07_1_10.html [46] Bolonkin A.A., “New Concepts, Ideas, Innovations in Aerospace, Technology and Human Science”, NOVA, 2008, 502 pgs., Appendix 1, pp. 445 – 458. [47] Bolonkin A.A., Cathcart R.B., “Macro Projects: Environment and Technology”, NOVA, 2009, 536 pgs.). Part III, pp. 465 - 479.



Short Communication E

THE 27-DAY PERIODICITY IN GEOMAGNETIC ACTIVITY AND SOLAR WIND PARAMETERS OVER SOLAR CYCLE 23 Ana G. Elias1,2, Virginia M. Silbergleit1,3, Ana Curcio3 and Patricia A. Larocca3 1

Consejo Nacional de Investigaciones Cientificas y Tecnicas, CONICET, Argentina 2 Universidad Nacional de Tucuman, Facultad de Ciencias Exactas y Tecnologia, Departamento de Fisica, Tucuman, Argentina 3 Universidad Nacional de Buenos Aires, Facultad de Ingenieria, FIUBA, Buenos Aires, Argentina

Abstract Geomagnetic activity and solar wind parameters are analyzed in terms of the periodicity linked to solar rotation that is the 27-day cycle. Its fluctuation in frequency and time is studied using the wavelet power spectrum. For this purpose we used the geomagnetic activity aa index and three solar wind parameters: magnetic field magnitude (B), density (d) and velocity (v). The sunspot number, Rz, is also analyzed to have a solar activity reference. The study was carried out for the period July 1996 – December 2005, which corresponds to solar cycle 23, except for the last years corresponding to its final minimum level. For the time period and parameters here analyzed, the 27-day periodicity is observed to have enhanced power during maximum and falling phase of the solar activity cycle, with no significant power during the ascending phase, not even in solar activity. Besides the time evolution, a periodicity variation is also noticed along the solar cycle. In some cases the period decreases as the solar cycle approaches minimum levels, as expected from the meridional movement of active regions towards lower solar latitudes during this time. However, periodicites lower than 27.27 days (synodic period at the solar equator ) are also observed, pointing out inner regions of the sun as possible sources of the active regions, or a surface phenomenon arising because of solar activity shifts during solar rotation.

392

Ana G. Elias, Virginia M. Silbergleit, Ana Curcio, et al.

Introduction Magnetic active regions’ distribution at the solar surface is not homogeneous, but tend to form regions of activity at preferred longitudes. This tendency for active regions to cluster in active longitudes has long been recognized (Warwick, 1964). The lifetime of these activity bands were found to be of several solar rotations (Bogart, 1982; Bai, 1987). A 27-day period is therefore reflected in solar and geomagnetic activity parameters as seen from Earth. Observations of different structures, however, give slightly different synodic periods of rotation (Ruzmaikin et al., 2001). Near the solar surface, the synodic rotation rate at the equator corresponds to 27.27 days (sidereal rotation period 25.38 days), increasing gradually to 35 days as one moves toward the poles in the sun. This pattern extends through the convection zone. After the tachocline, the angular velocity adjusts to apparent solid-body with a period of around 26.8 days (Howe et al., 2000). For a thorough analysis of the internal rotation of the sun see Thompson et al. (2003). The rotation rate changes through the solar cycle and also from one solar cycle to another (Gilman and Howard, 1984; Astafyeva and Bazilevskaya, 2000; Kane, 2002; Rybak et al., 2005; Balthasar, 2007; to mention a few). Many studies exist on this subject, some dating back to the XVIII century. Following, some works are mentioned as examples of the diversity of this theme. Pap et al. (1990) observed that the 27-day periodicty is more pronounced in the descending phase of the solar cycle than in the ascending phase, explaining that during maximum and falling phases of solar cycle, the magentic field is much more organized and long-lived. Temmer et al. (2004, 2005), analyzing solar cycles 19 to 22, reported a 24-day period in solar flare occurrence which is observed mainly around the solar maximum. An explanation refers to the rotation of the solar interior: deeper zones of activity rotate faster than the solar photosphere. Bai (1987) finds that active zones rotate with a period of 26.75 days. He also finds superactive regions which have similar longitudes in a frame rotating at a constant rate of 23.7 days. This could be due to activity sources in the deep layer rotating at that rate. Bai and Sturrock (1993), from an analysis of solar flares, proposed a fundamental period of 25.5 days as a result of two activity centers that rotate about an axis tilted by 40º, which gives rise to the well known 154-day period. In the present work, the fluctuation in frequency and time of 27-day periodicity is studied using the wavelet power spectrum. The aa index, three solar wind parameters (magnetic field magnitude, B, density, d, and velocity, v) and the sunspot number, Rz, are analyzed along solar cycle 23. With this study we attempt to find some additional results on a subject that already has many contributions.

Data Analysis Daily solar wind parameters, the aa index and Rz where analyzed for the period July 1, 1996 to December 31, 2005 (solar cycle 23). Magnetic field magnitude (B), density (d) and velocity (v) of the solar wind are OMNI data obtained from the GSFC/SPDF OMNIWeb interface at http://omniweb.gsfc.nasa.gov (King and Papitashvili, 2004). The aa index and Rz are available at the National Geophysical Data Center (http://www.ngdc.noaa.gov/).

The 27-Day Periodicity in Geomagnetic Activity and Solar Wind Parameters

393

The few data missing in the OMNI records for the period we choose to analyze, where linearly interpolated in order to obtain the complete daily data sets required by the statiscal method we applied. The wavelet power spectrum of the five data series was assessed using the wavelet software provided by C. Torrence and G. Compo (available at http://atoc.colorado.edu/research/wavelets/). The Morlet wavelet is used with the parameter ω = 40, which, in our case, shows a reasonable resolution in both frequency and time. The power spectra, shown in Figure 1, was assessed for the period range 24-30 days in order to determine frequency and time variation of periodicities linked to the solar rotation period. Zones in the figures with colors from yellow to red are significant at a 95% level. Beginning with the solar wind, in the case of B, enhanced power of the solar rotation period is obtained during solar maximum (around year 2000) and during almost the complete declining phase of the solar cycle. When a global power spectrum is calculated, the most prominent period is 27.5 days, however, it appears as a 28.6-day periodicity around solar maximum, decreasing towards the synodic period 27.25-days through the declining phase of the solar cycle. In the case of d, significant power is noticed at 27.0 days only at the maximum of the solar cycle. For V, enhanced power is obtained at the synodic rotation rate during solar maximum and during the declining phase, being the latter more prominent, as opposed to what happens with d.

(a) Figure 1. (Continued)


394

(b)

(c) Figure 1. (Continued)


395

(d)

(e) Figure 1. Wavelet power spectrum using the Morlet wavelet with the parameter ω = 40, for the period range 24-30 days assessed for the time series: (a) solar wind magnetic field intensity, B, (b) solar wind density, d, (c) solar wind velocity, v, (d) aa inex, (e) sunspot number Rz, during the period period July 1, 1996 to December 31, 2005 (solar cycle 23). Zones in the figures with colors from yellow to red are significant at a 95% level.


396

In the case of aa, the frequency and time behaviour of the spectrum is much more complex than in the case of the solar wind parameters just described. Again, enhanced power is oberved at the maximum and towards the declining phase of the solar cycle. The most important periodicity observed corresponds to 27.5 days during the maximum and falling phase. However, and with much less power, significant peaks are noticed at lower (∼26 days) and higher periods (∼30 days) towards the solar cycle minimum. During the falling phase, it also appears a significant peak at a 24-day period, as that already noticed by Temmer et al. (2004, 2005). For Rz, power peaks appear at 27.0-days at solar maximum, around year 2000, and then this peak period decreases to 26.3-days. This period variation is highly consistent with the fact that at the start of a cycle, sunspots tend to appear at mid-latitudes and then move toward the equator as each cycle progresses. Both values, lower than the synodic period, may be due to these magnetic features are anchored at levels below the photosphere moving faster (Gilman, 1974; Bai, 1987).

Comparison of the Solar-Rotation Related Cycle with Variations at Higher Frequencies The wavelet power spectrum was also assessed for the period range 11-30 days in order to determine the relative importance of the solar rotation related cycles with lower periodicities, as it is the well-known 13.5-day period. Figure 2 presents the results obtained for the five parameters here analyzed.

(a) Figure 2. (Continued)


(b)

(c) Figure 2. (Continued)

397


398

(d)

(e) Figure 2. Wavelet power spectrum using the Morlet wavelet with the parameter ω = 40, for the period range 11-30 days assessed for the time series: (a) solar wind magnetic field intensity, B, (b) solar wind density, d, (c) solar wind velocity, v, (d) aa inex, (e) sunspot number Rz, during the period July 1, 1996 to December 31, 2005 (solar cycle 23). Zones in the figures with colors from light-blue to red are significant at a 95% level.


399

In the case of B, the 13.5 day cycle has more power than the solar-rotation cycle. It appears with the same structure and time variation as the 27-day period, presenting halfperiod length and suggesting that the solar active structures are 180º appart over the solar surface. This is why, prominent half-rotation cycles are observed. During a short interval of time, between 2003 and 2004, a 22.5-day peak is also observed with similar power to that of the solar rotation period. In the case of V, the 13.5-day period presents again the same structure and variability as the solar rotation period, but with less power. For d, it has increased power during the declining phase of the solar cycle, although the rotation period is important during the maximum and almost absent during the phalling phase. The aa power spectrum, presents a prominent peak at 21.9 days with more than twice the power of the solar rotation cycle. However, when one looks at the global power spectrum during the whole solar cycle, it appears with half the power due to its short time interval appearance. The 13.5-day periodicity, which is significant only during the falling phase, is also more prominent than the solar rotation period. The Rz power spectrum, do not present a significant peak at the 13.5 days during solar cycle 23, being the solar rotation period the most important at the low frequency range here analyzed.

Conclusion As already mentioned and observed by several authors, the periodicity linked to solar rotation presents a time varying power and a fluctuating periodicity value. For the parameters here analyzed, and taking into account that only one solar cycle was studied, this periodicity is enhanced during maximum and falling phase of the solar activity cycle. During the ascending phase, there is no significant power at this period. One may think that its importance during maximum and falling phase may mask its presence during rising phase. However, Ozguc et al. (2002) analyzing only the ascending branch of the solar cycle of cycle 23, do not detect this periodicity, being a 35-day cycle the lowest significant periodicity they obtain. The frequency variation of the solar rotation period may be probably due, not only to meridional movements of active regions over the solar surface, but also to radial movements where a gradient of angular velocity exists. The 27.0 value observed in d and Rz coincides with the 27.03-day periodicity observed by Neugebauer et al. (2000), which they explain by a depth increase of the corresponding solar source. Ruzmaikin et al. (2001) further explains this fact by the presence of a robust magnetic structure on the sun which rotates more rapid than the solar equatorial rotation. Henney and Harvey (2002), who showed later that the coherency of this periodicity is significant for the past two decades, found that its origin are long-lived complexes of active regions in the norhtern hemisphere.. In the case of aa, a very strong 21.9-day period appear over a short time interval (20032004), which, although stronger than any other cycle in the 11-30 days range, due to its short duration, it does not appear as a significant peak in the global spectrum. Its time appearance coincides with the 22.5-day peak observed in B.

400


Regarding the 13.5-day period, although absent in Rz, it appears as the strongest cycle in most of the cases here analyzed: in the case of B, over the whole period when the solar rotation related period is significant, and in the cases of d and aa, during the solar cycle falling phase. For V, although not the strongest, the 13.5-day period is a very important cycle. This means, that the 180º separation in active longitudes is a strong determinant of time variation in active regions and solar wind characteristics. The study and understanding of periodic variations in solar and geomagnetic activity (including solar wind parameters) is essential for predicting future activity levels and for characterizing the sources in the sun that generates them. To understand solar influences on global climate change and space weather we need to comprehend solar variations. For this, we require models and analysis based on observation results. Our results, intend to contribute to this subject through the latter option.

Acknowledgements We acknowledge the National Space Science Data Center for providing the OMNI data, and C. Torrence and G. Compo for the wavelet software.

References Astafyeva, N.M., Bazilevskaya, G.A., Long term changes of cosmic ray intensity: spectral behaviour and 27-day variations. Phys. Cham. Eartc (C) 2000, 25, 129-132. Bai, T., Distribution of flares on the sun: Superactive regions and active zones of 1980-1985. Ao. J. 1987, 314, 795-807. Balthasar, H., Rotational periodicities in sunspot relative numbers. Astron. Astrophys. 2007, 471, 281-287. Bogart, R.S., Recurrence of solar activity: Evidence for active longitudes. Sol. Phys. 1982, 76, 155-165. Gilman, P.A., Solar rotation. Annu. Rev. Astron. Astrophys 1974, 12, 47-70. Gilman, P.A., Howard, R., Variations in solar rotation with the sunspot cycle. Ap.J. 1984, 283, 385-391. Henney, C.J., Harvey, J.W., Phase coherence analysis of solar magnetic activity. Solar Physics, 2002, 207, 199-218. Howe, R., Christensen-Dalsgaard, J., Hill, F., Komm, R.W., Larsen, R.M., Schou, J., Thompson, M.J., Toomre, J., Dynamic variations at the base of the solar convection zone. Science 2000, 287, 2456-2460. Kane, R.P., Variability in the periodicity of 27 days in solar indices. Solar Physics, 2002, 209, 207-216. King, J.H., Papitashvili, N.E., Solar wind spatial scales in and comparisons of hourly Wind and ACE plasma and magnetic field data. J. Geophys. Res. 2004, 110, doi 10.1029/2004JA010804. Neugebauer, M., Smith, E.J., Ruzmaikin, A., Feynman, J., Vaughan, A.H., The solar magnetic field and the solar wind: Existence of preferred longitudes. J. Geophys. Res. 2000, 105, 2315-2324.


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Ozguc, A., Atac, T., Rybak, J., Flare index variability in the ascending branch of solar cycle 23. J. Geophys. Res. 2002, 107, doi 10.1029/2001JA009080. Pap, J., Tobiska, W.K., Bouwer, S.D., Periodicities of solar irradiance and solar activity indices, I. Solar Physics 1990, 129, 165-189. Ruzmaikin, A., Feynman, J., Neugebauer, M., Smith, E.J., Preferred solar longitudes with signatures in the solar wind. J. Geophys. Res. 2001, 106, 8363-8370. Rybak, J., Ozguc, A., Atac, T., Sozen, E., Intermittence of the short-term periodicities of the flare index. Adv. Space Res. 2005, 35, 406-409. Temmer, M., Veronig, A., Rybak, J., Brajsa, R., Hanslmeier, A., On the 24-day period observed in solar flare occurrence. Solar Physics 2004, 221, 325-335. Temmer, M., Rybak, J., Veronig, A., Hanslmeier, What causes the 24-day period observed in solar flares?. Astron. Astrophys 2005, 433, 707-712. Thompson, M.J., Christensen-Dalsgaard, J., Miesch, M.S., Toomre, J., The internal rotation of the sun. Annu. Rev. Astron. Astrophys 2003, 41, 599-643. Warwick, C.S., Longitude distribution of solar flares. Ap. J. 1965, 141, 500-504.

In: Handbook on Solar Wind: Effect, Dynamics … Editor: Hans E. Johannson


Short Communication F

WEIBULL PARAMETERS FOR WIND SPEED DISTRIBUTION AT FIFTEEN LOCATIONS IN ALGERIA Y. Himri1,1, S. Himri2,2 and A. Boudghene Stambouli3,3 1

Electricity & Gas National Enterprise (SONELGAZ) Béchar, Algeria University of Béchar, Department of fundamental Sciences, Algeria 3 University of Sciences and Technology of Oran, Department of Electronics, Algeria 2

Abstract In the present study the Weibull parameters distribution function were computed for 15 locations in Algeria. The wind data which covers a period of almost 10 years between 1977 and 1988 was adopted. The average wind speed at a height of 10 m above ground level was found to range from 2.3 to 5.9 m/s. The Weibull distributions parameters (c & k) were found to vary between 3.1 and 7.2 m/s and 1.19 to 2.15 respectively. Higher wind speeds were observed in the day time between 09:00 and 18:00 h and relatively smaller during rest of the period. Generally the long-term seasonal wind speeds were found to be relatively higher during spring to the autumn month of September compared to other months. The two parameters of a Weibull density distribution function for the three areas namely (Littoral, Highlands and Sahara) were compared and wider distributions were observed in the Sahara. It is also noticed from this work that the Weibull distribution give a good fit to experimental data. The aim of this work is to provide information about the distribution of wind in different regions of Algeria (Littoral, Highlands and Sahara) and give useful insights to engineers and experts dealing with wind energy.

1

Correspondence to: Electricity & Gas National Enterprise (SONELGAZ) Béchar, Algeria, 05 rue Mokadem Ahmed, Béchar 08000, Algeria, E-mail: [email protected], Tel.: +213 774 757714; fax: +213 49 801674. 2 E-mail: [email protected] 3 E-mail: [email protected]

404

Y. Himri, S. Himri and A. Boudghene Stambouli

1. Introduction The Swedish physicist W. Weibull is among the first founders of Probabilistic Mechanics of Structures and Materials. His probability laws have been also used in many other applications, such as aerospace, electric power, medical, electronics and every industry. In recent years most attention has been focused on this method for wind energy applications, the many publications for different locations of the world have demonstrated that the Weibull two parameters distributions, is the most widely used to fit the wind speed data. Justus et al. [1] applied the Weibull and Log-normal distribution to wind speed data from more than a hundred stations of the USA National Climatic Centre and concluded that the Weibull Distribution rendered the best fit. Gupta [2] performed work on estimating the annual and monthly Weibull parameters for five locations in India and these revealed two parameters which varied over a wide range. Lun and Lam [3] computed the two parameters of the Weibull density distribution function for three different locations in Hong Kong, using a long-term data source, consisting of 30 years of hourly mean wind speed data. Hennessey [4] found that the energy output calculated using wind speeds derived from the Rayleigh distribution was within 10% of those derived from the Weibull distribution. Garcia et al. [5] solved the estimation of the annual Weibull and Lognormal parameters from 20 locations in Navarre, Spain. Akpinar et al. [6] carried out a study using Weibull density function to demonstrate wind energy potential of Maden-Elazıg in eastern Turkey. Results reveal that the mean speed for investigated site varies between 5 and 6 m/s and yearly average power density is 244.65W/m2. Ulgen et al. studied the wind variation for a typical site using Weibull distribution and Rayleigh distribution was found to be suitable to represent the actual probability of wind speed data for the site studied [7]. Sahin et al. [8] determined the wind energy potential of the east Mediterranean region of Turkey and identified the best wind source locations using a computer package program called the Wind Atlas Analysis and Application Program (WAsP). Youcef Ettoumi et al. used first-order Markov chain and Weibull distribution methods for statistical bivariate modeling of wind using the data wind speed and wind direction measurements collected every 3 h at the meteorological station of Essenia. Also, a detailed study has been made on the statistical features of the wind at Oran, in Algeria [9]. Himri et al [10] presented the wind characteristic at three locations in Algeria. They concluded that the energy could be harnessed for almost 64% the time using wind machines with cut-in –speed of 3 m/s or more. In the present study the Weibull parameters namely, scale parameter c and shape parameter k were used for describing the wind speed frequency distribution. These two parameters were computed using WAsP. The aim of this work is to provide information about the distribution of wind in different regions of Algeria (Littoral, Highlands and Sahara) and give useful insights to engineers and experts dealing with wind energy.

Weibull Parameters for Wind Speed Distribution at Fifteen Locations in Algeria

405

2. Wind Data and Sites Description In this study, the wind speed data which cover a period of 07 to 12 years (between1976 – 1988) are used at 15 sites in Algeria. Table 1 shows names, latitude, longitude, altitude, measurement duration and the measurement years of the locations. Table 1. Geographical coordinates of the data collection stations used in the study.

Adrar

Latitude (deg) 27° 49’ N

Longitude (deg) 00° 17’ E

Altitude (m) 263

Duration (years) 11

Measurement Years 1977 - 1988

Tindouf

27° 40’ N

08° 06’ W

401

8

1976 - 1984

Béchar

31° 37’ N

02° 14’ W

811

12

1976 - 1988

Tamanrasset

22° 47’ N

05° 31’ E

1377

12

1976 - 1988

In Amenas

28° 03’ N

09° 38’ E

561

11

1977 - 1988

Ghardaia

32° 24’ N

03° 48’ E

468

9

1978 - 1987

El Oued

33° 30’ N

06° 47’ E

62

12

1976 - 1988

M’sila

35° 40’ N

04° 30’ E

441

11

1977 - 1988

Setif

36° 11’ N

05° 15’E

1033

7

1981 - 1988

Tlemcen

34° 57’ N

01° 17’ W

592

7

1980 - 1987

Oran

35° 38’ N

00° 37’ W

90

9

1979 - 1988

Chlef

36° 12’ N

01° 20’ E

143

8

1977 - 1985

Algiers

36° 43’ N

03° 15’ E

24

9

1979 - 1988

Skikda

36° 53’ N

06° 54’ E

1

9

1979 - 1988

Annaba

36° 49’ N

07° 49’ E

5

9

1979 - 1988

Location

The wind speed measurements were made 10 meters above ground level and recorded every three hour interval (viz, 0, 3, 6, 9, 12, 15, 18 and 21 hours) at all the stations. These stations cover Algeria from north to south and from east to west, including the highland region. The geographical locations of these stations are also shown in Figure 1. Figure 2 provides the variation of long-term mean wind speed during entire data collection period at 15 stations under consideration in this study. It is seen from Figure 2 that Adrar has the maximum mean wind speed of 5.9 m/s while Tlemcen has the minimum wind speed of 2.3 m/s. It is also noticed that both the southern and highland regions have higher mean wind speeds compared to the northern regions like Oran, Chlef, Algiers, etc. it is also observed that towns in the south western area such as Tindouf and Adrar has higher mean wind speeds. The seasonal variation of mean wind speed for all the locations are depicted in Figure 3.

406


Figure 1. Map showing the locations of the wind measurement stations.

Figure 2. Variation of long-term mean wind speed at all sites.


407

Figure 3. Seasonal variation of long-term mean wind speed

As seen from Figure 3, higher wind speeds were found during spring to the autumn month of September compared to other months. This trend is true for all locations. The diurnal change in long-term mean wind speed at all stations is shown in Figure 4.

408


Figure 4. Diurnal variation of long-term mean wind speed


409

In general the higher wind speeds were observed in the day time between 09:00 and 18:00 h and relatively smaller during rest of the period. This indicates that higher electricity could be produced during 09:00–18:00 h, which also coincide with higher electricity demand time. It is also evident from this Figure that wind speed was highest at Adrar while lowest at Tlemcen during the entire day.

3. The Weibull Distribution Function The wind speed data is obtained from the Algerian Wind Energy Atlas (1990). As noticed from the Weibull parameters, namely, shape parameter k and scale parameter c are computed for all 15 locations in Algeria based on annual average wind speed. As shown from Figure 5.

Figure 5. Weibull distribution parameters in all 15 stations

The value of the shape parameter is found to be around 1.63 in the highland part of the country whereas at coastal sites this value ranges from 1.19 to 1.76. A higher value of k, i.e. 2.15, is obtained in the south western of Algeria. For the scale parameter c, highest values, i.e. greater than 5.5 were found at Adrar, Tindouf, In Amenas and Ghardaia (Sahara sites) whiles the lowest (lower than 5.5) at the rest areas of the country. Figure 6 shows the wind speed histograms of the percent frequency distribution for all 15 locations. These curves were obtained by superimposition of the values of k and c for different locations on the wind speed histograms the wind speed data for almost locations are good fit represented by the Weibull distribution.


410

Figure 6. Wind frequency histograms for all 15 stations

4. Conclusion We can conclude from this work the following results: 1. Using wind data, consisting of hourly wind speed records over almost 10 year period, 1977–1988, wind data at 15 locations, Algeria were investigated. 2. The average wind speeds were found to range between 2.3 – 5.9 m/s. The maximum mean wind speed was observed in Adrar while the minimum value was noticed in Tlemcen.


411

3. The shape parameter varies between 1.19 and 2.15. The higher values of the parameters k were found in the southwest region of Algeria (Adrar and Tindouf) while the minimum values in the northern region (Tlemcen, and Chlef). 4. The scale parameter varies between 3.1 and 7.2. The values of c have maximum at Adrar and Tindouf but their minimum values is found in Tlemcen. 5. Generally the long-term seasonal wind speeds were found to be relatively higher during spring to the autumn month of September compared to other months. 6. The higher wind speeds were observed in the day time between 09:00 and 18:00 h and relatively smaller during rest of the period. 7. The aim of this work is to provide information about the distribution of wind in different regions of Algeria (Littoral, Highlands and Sahara) and give useful insights to engineers and experts dealing with wind energy.

Acknowledgements The authors would like to thank Mr A. Slimani Rector of University of Béchar. Further thanks are due respectively to Mrs R. Aissaoui and Mr S. Guezzane Director of CREDEG (Centre Recherche Et Développement Electricité Gaz); Sonelgaz R&D Office for their cooperation.

References [1]

Justus, C. G; Hargraves, W.R.; Yalcin, A. Nation wide assessment of potential output from wind powered generators. Journal of Applied Meteorology. 1976,15(7),673-8. [2] Gupta, B.K. Weibull parameters for annual and monthly wind speed distributions for five locations in India. Solar Energy. 1986, 37(6), 469–71. [3] Lun, I.Y.F.; Lam, J. C.A study of Weibull parameters using long- term wind observations. Renewable Energy. 2000, 20, 145-153. [4] Hennessey, J. J. A comparison of the Weibull and Rayleigh distributions for estimating wind power potential. Wind Engineering, 1978, 2(3),156-64. [5] Garcia, A.; Torres, J.L.; Prieto, E.; De Francisco, A. Fitting wind speed distribution: a case study. Solar Energy. 1998, 62 (2), 139–144. [6] Akpinar, E.K.; Akpinar, S. Determination of the wind energy potential for MadenElazig Turkey. Energy Convers Manage. 2004, 45,2901–14. [7] Ulgen, K.; Genc, A. ; Hepbasli, A.; Oturanc, G. Assessment of wind characteristics for energy generation. Energy Sources. 2004,26(13),1227–37. [8] Sahin, B.; Bilgili, M.; Akilli, H. The wind power potential of the eastern Mediterranean region of Turkey. J Wind Eng Ind Aerodynam. 2005,93,171–83. [9] Youcef Ettoumi, F.; Sauvageot, H., Adane AEH. Statistical bivariate modeling of wind using first-order Markov chain and Weibull distribution. Renewable Energy. 2003,28,1787–802. [10] Himri, Y.; Draoui, B.; Himri, S. Wind characteristics of Algeria. Nanotechnology Conference and Trade Show June 1-5 Boston Massachusetts U.S.A. 2008.



Short Communication G

ON THE LIMITS OF APPLICABILITY OF THE RAY INTERFERENCE INTEGRAL METHOD FOR CALCULATIONS OF THE TEMPORAL STRUCTURE OF SOLAR RADIO BURSTS A.N. Afanasiev1 and N.T. Afanasiev2 1

Institute of Solar-Terrestrial Physics, Irkutsk, Russian Federation 2 Irkutsk State University, Irkutsk, Russian Federation

Abstract We discuss the possibility of using the ray interference integral method to carry out calculations of scattering of radio emission from sources embedded in the corona and solar wind. We point out that preliminary analysis of the topology of caustics produced by geometrical optics rays and by partial waves forming the interference integral enables correct calculations of the solar radio burst structure.

Introduction The interpretation of the temporal structure of solar radio bursts is one of the most difficult issues in solar physics. This structure in general is determined both by processes occurring within the source itself and by propagation effects in the corona and solar wind. The nearsolar plasma represents an extremely inhomogeneous and nonstationary medium. It is natural, therefore, that the universal analytical method to describe radio emission propagation in such a medium does not exist. That is why it is necessary to use various approximate approaches. Based on the ray interference integral (RII) approximation, Afanasiev and Altyntsev (2006) and Afanasiev (2006) analysed the observed temporal structure of the solar radio spikes and of the type IIId decameter bursts. However, the limits of applicability of the RII method for taking into account strong regular refraction of radio emission in the solar corona require additional discussion. Therefore, we shall consider here a question concerning the

A.N. Afanasiev and N.T. Afanasiev

414

fundamental possibility of calculating the structure of solar radio emission propagated through the corona and solar wind by the RII method.

Theoretical Relations and Discussion According to Orlov (1972, 1974), the ray interference integral represents the solution of the wave equation, written as a superposition of infinitely many partial waves (WKB modes):

U (r ) = ∫ U s (r,α )dα ,

(1)

where

U s (r,α ) = As (r,α )exp[ikψ s (r,α )] ,

(2)

k = 2πf c is the wave number, f is the radiation frequency, c is the velocity of light in a vacuum, and α is the spectral parameter.

The phase of a WKB mode ψ s (r,α ) is the solution of the eikonal equation

[∇ψ (r,α )]2 = ε (r ) , where

(3)

ε (r ) is the dielectric permittivity of medium.

The amplitude of a WKB mode is determined from solving the transport equation

2∇As ∇ψ s + As ∇ 2ψ s = 0

(4)

and have the form:

As (r ) =

As(0 )

J s (r )

,

(5)

(0 )

where J s is the ray divergence of the partial wave, and As

is determined by the initial

conditions. The calculation of Equation (1) by the stationary phase method results in the geometrical optics (GO) approximation for the field (Orlov, 1972). In this case, the equation, from which the stationary points are determined, coincides with the geometrical optics ray equation. If the observer is at the caustic formed by the geometrical optics rays, then the GO approximation gives an infinite increase in the field amplitude (Kravtsov and Orlov, 1990). Earlier publications repeatedly discussed the question of applicability of the RII method for studying radio emission propagation in both stratified and horizontally inhomogeneous media (Avdeev and Yarygin, 1978; Avdeev, Shilov, and Yarygin, 1981; Orlov and Demin,

On the Limits of Applicability of the Ray Interference Integral Method

415

1983; Avdeev et al., 1988; Krestjaninov and Permjakov, 1993). It is well known (Orlov, 1974; Avdeev et al., 1988) that the partial waves constituting the ray interference integral can produce caustics as well. At these caustics, the amplitudes of the WKB modes tend to infinity (the denominator in Equation (5) turns to zero). However, the partial wave singularities are usually integrated (Orlov and Demin, 1980, 1981a, 1981b, 1983; Avdeev et al., 1988; Krestjaninov and Permjakov, 1993). If the observer is far from the caustic of partial waves (but, maybe, close to the caustic of geometrical optics rays), then the RII method provides good coincidence with the exact solution. If the observer is at the point where these caustics coincide, then the RII method gives albeit a finite but overestimated value for the field amplitude (Orlov and Demin, 1983). In this case it is better to use a more general uniform (caustic) interference integral (a superposition of the Airy asymptotics, etc.) (Orlov, 1974; Avdeev et al., 1988). When solving the statistical problems of scattering by the RII method, in view of strong regular refraction of radio waves in randomly inhomogeneous media, the following integral representation is usually used (Afanasiev and Tinin, 1982; Tinin, 1983):

~ U (r ) = ∫ As 0 (r,α )exp{ ik [ψ s 0 (r,α ) +ψ~s1 (r,α )]}dα , where As 0 and

(6)

ψ s 0 are the amplitude and the eikonal of the partial wave in a regular

medium, and ψ~s1 describes the eikonal fluctuations related to the influence of random fluctuations of dielectric permittivity of medium. The latter function is calculated to a first approximation of the perturbation theory. Representation (6) takes into account only phase fluctuations of partial waves. Representation (6) has been successfully used in solving problems of radio wave scattering not only in the randomly inhomogeneous media that are stratified on average, but also in the media, the average dielectric permittivity of which is specified by a twodimensional function (Afanasiev et al., 1983; Az'muko et al., 1988, 1991; Afanasiev et al., 1997, 1998a, 1998b, 2001; Tinin et al., 1992; Zheonykh et al., 1999). In particular, Tinin (1989) has derived, based on the RII method in the form of Expression (6), an expression for the mean intensity of radio waves for any given horizontally inhomogeneous model for the ionosphere. Tinin et al. (1992), in addition to the plane-stratified model for a regular ionosphere, considered a more complex horizontally inhomogeneous model. The numerical calculations in the mentioned paper were carried out using the RII method in the form of Expression (6). When solving the statistical problems by the RII method, in view of strong regular refraction, the problem of calculating the moments of the field in the presence of caustics of partial waves remains to exist. Therefore, in order to apply the RII method in a correct way, it is necessary to analyse preliminarily the geometrical optics structure of the field and to reveal the presence of the caustics near the observer. Such an approach was applied by Az'muko et al. (1991), who performed calculations of the mean intensity of monochromatic radio waves propagating in an ionosphere containing periodic regular inhomogeneities. Using the same approach, Afanasiev et al. (1997) carried out a numerical modeling of the mean intensity of monochromatic radio waves for the case where a cloud-like sporadic layer E s presents in the ionosphere. Furthermore, Az'muko et al. (1988) calculated the mean profile of a radio pulse

416


propagated through an ionosphere with localized electron density inhomogeneities. In all the cases, there arise the caustics of geometrical optics rays and of partial waves. To apply the RII method in a correct way, Afanasiev and Altyntsev (2006) and Afanasiev (2006) carried out first the geometrical optics analysis of the field structure. This allowed the authors to draw conclusions that refraction of radio waves on large-scale regular inhomogeneities of the solar corona is responsible for the multi-component temporal profiles of the investigated radio bursts. Then, calculations of the mean temporal pulse profiles were carried out using the ray interference integral. When performing the calculations, true geometrical optics trajectories of radio emission, connecting the source and the receiver, were determined first, and then, in the vicinities of these trajectories, fluctuations of trajectory characteristics of partial waves were calculated. Under the condition of strong scattering (under which the expression for the frequency coherence function was derived by Afanasiev and Altyntsev, 2006), this way of calculating the interference integral is right because these vicinities are small. The burst profiles presented in the papers by Afanasiev and Altyntsev (2006) and by Afanasiev (2006) correspond to the observer's position in the area of geometrical optics multipathing, but not at caustics of geometrical optics rays. Therefore, the results of these calculations are correct. It is important to note that if the observer is at the caustic produced by geometrical optics rays, then the RII method-based calculations of pulse profiles are also correct, provided that the caustic of partial waves is far from the observer. Otherwise, such calculations give a finite but overestimated result. In this case, in order to fit experimental data better, it is necessary to calculate the moments of the field on the basis of the caustic interference integral. As concerns the amplitude fluctuations of partial waves, they are mainly caused by radio emission diffraction on plasma inhomogeneities with scales less than the size of the Fresnel zone. Therefore, strictly speaking, the amplitude fluctuations of partial waves cannot be neglected in the case of the horizontally inhomogeneous medium with small-scale random inhomogeneities. This limitation is indicated in the papers by Afanasiev and Altyntsev (2006) and by Afanasiev (2006). Note that this limitation refers to a plane-stratified background medium as well. At the same time, it is possible to develop the technique applied by Afanasiev and Altyntsev (2006) for taking into account inhomogeneities of smaller scales, using the method of smooth perturbations for calculating the amplitudes of the partial waves (see Zernov, 1994).

Conclusion Overall, the RII method correctly describes the refractive mechanism of formation of the multi-component temporal profiles of the solar radio spikes and of the type IIId decameter bursts, which was proposed by Afanasiev and Altyntsev (2006) and by Afanasiev (2006). Our calculations (Afanasiev, 2005, 2006, 2007; Afanasiev and Altyntsev, 2006; Afanasiev and Afanasiev, 2007, 2008) have revealed that the RII method represents in a number of cases a powerful tool to carry out mathematical modeling of scattering of radio emission in the corona and solar wind.

On the Limits of Applicability of the Ray Interference Integral Method

417

References Afanasiev, A. N. J. Atmos. Sol. Terr. Phys. 2005, 67, 1002-1013. Afanasiev, A. N. Solar Phys. 2006, 238, 87-104. Afanasiev, A.N. Astron. and Astrophys. Trans. 2007, 26, 647-653. Afanasiev, A. N.; Afanasiev, N. T. Solar Phys. 2007, 245, 355-367. Afanasiev, A. N.; Afanasiev, N. T. In Solar Physics Research Trends; Wang, P.; Ed.; Nova Science Publishers: Hauppauge, NY, 2008; pp 17-27. Afanasiev, A. N.; Altyntsev, A. T. Solar Phys. 2006, 234, 151-167. Afanasiev, N. T.; Tinin, M. V. Issledovaniya po geomagnetizmu, aeronomii i fizike Solntsa 1982, 61, 236-241. Afanasiev, N. T.; Grozov, V. P.; Krasikov, A. A.; Nosov, V. E.; Tinin, M. V. Issledovaniya po geomagnetizmu, aeronomii i fizike Solntsa 1983, 63, 180-196. Afanasiev, N. T.; Zheonykh, A. A.; Ivelskaya, M. K.; Sazhin, V. I.; Tinin, M. V. Issledovaniya po geomagnetizmu, aeronomii i fizike Solntsa 1997, 107, 327-332. Afanasiev, N. T.; Zheonykh, A. A.; Sazhin, V. I.; Tinin, M. V.; Ivelskaya, M. K. J. Atmos. Sol. Terr. Phys. 1998a, 60, 1687-1694. Afanasiev, N. T.; Zheonykh, A. A.; Ivelskaya, M. K.; Polyakov, V.M.; Sazhin, V. I.; Tinin, M. V. In Proc. URSI Symposium on Electromagnetic Theory; Thessaloniki, Greece, 1998b; Vol. 2, pp 328-332. Afanasiev, N. T.; Zheonykh, A. A.; Ivelskaya, M. K.; Sazhin, V. I.; Tinin, M. V.; Unuchkov, V. E. J. Atmos. Sol. Terr. Phys. 2001, 63, 1967-1972. Avdeev, V. B.; Yarygin, A. P. In Abstracts of the XII All-Union Conference on Radio Wave Propagation; Nauka: Moscow, USSR, 1978; Vol. 2, p 294. Avdeev, V.B.; Shilov, N.V.; Yarygin, A.P. In Abstracts of the XIII All-Union Conference on Radio Wave Propagation; Nauka: Moscow, USSR, 1981; Vol. 1, pp 302-303. Avdeev, V. B.; Demin, A. V.; Kravtsov, Yu. A.; Tinin, M. V.; Yarygin, A. P. Izv. VUZov Radiofiz. 1988, 31, 1279-1294. Az'muko, N. A.; Afanasiev, N. T.; Pobedina, A. P.; Tinin, M. V. Issledovaniya po geomagnetizmu, aeronomii i fizike Solntsa 1988, 81, 257-265. Az'muko, N. A.; Afanasiev, N. T.; Pobedina A. P.; Tinin, M. V. In Ionosphere Dynamics; Drobzhev, V. I.; Ed.;Gylym: Alma-Ata, USSR, 1991; Vol. 3, pp 69-74. Kravtsov, Yu. A.; Orlov, Yu. I. Geometrical Optics of Inhomogeneous Media; ISBN 3-54051944-0; Springer-Verlag: Berlin Heidelberg New York, 1990; 312 pp. Krestjaninov, S. V.; Permjakov, V. A. In Abstracts of the XVII Conference on Radio Wave Propagation; Nauka: Ulyanovsk, USSR, 1993; Vol. 6, pp 46. Orlov, Yu. I. Trans. Moscow Institute for Energy 1972, 119, 82-91. Orlov, Yu. I. Izv. VUZov Radiofiz. 1974, 17, 1035-1041. Orlov, Yu. I.; Demin, A. V. Trans. Moscow Institute for Energy 1980, 497, 10-15. Orlov, Yu. I.; Demin, A. V. Trans. Moscow Institute for Energy 1981a, 553, 5-9. Orlov, Yu. I.; Demin, A. V. In Abstracts of the XVII Conference on Radio Wave Propagation; Nauka: Moscow, USSR, 1981b; Vol. 1, pp 304-306. Orlov, Yu. I.; Demin, A. V. In Issledovanie uslovii rasprostraneniya radiovoln; IZMIRAN: Moscow, USSR, 1983; pp 48-57. Tinin, M. V. Izv. VUZov Radiofiz. 1983, 26, 36-43.

418


Tinin, M. V. Issledovaniya po geomagnetizmu, aeronomii i fizike Solntsa 1989, 88, 145-155. Tinin, M. V.; Afanasiev, N. T.; Mikheev, S. M.; Pobedina, A. P.; Fridman, O. V. Radio Sci. 1992, 27, 245-255. Zernov, N. N. Radiotekhnika i elektronika 1994, 39, 241-252. Zheonykh, A. A.; Afanasiev, N. T.; Ivelskaya, M. K.; Sazhin, V. I.; Tinin, M. V.; Unuchkov, V. E. In Proc. URSI XXVI General Assembly; Toronto, Canada, 1999, 519.

Reviewed by Dr. A. A. Stanislavsky, Institute of Radio Astronomy, NAS Ukraine

INDEX air quality, 168, 170, 173 Aircraft, 221, 222 Alabama, 223 AAS, 317 Alaska, 75, 192 abiotic, 74 Alberta, 27, 72 absorption, 216, 234, 272, 289, 351, 359, 370, 372 alcohol, 154 absorption coefficient, 359, 372 aldehydes, 167 academic, 9 Algeria, xiii, 403, 404, 405, 409, 410, 411 acceleration, x, xii, 185, 212, 213, 214, 219, 220, 232, algorithm, 191, 321, 324, 325 233, 238, 239, 244, 245, 248, 259, 260, 264, 277, alloys, 359 281, 284, 291, 292, 310, 311, 312, 315, 353, 354, alpha, 64, 217 355, 357, 360, 361, 368, 370, 371, 372, 373 alternative, 11, 148, 157, 162 accelerator, 202, 203, 218, 382 alternatives, 146, 158, 283 accommodation, 26 aluminium, 172, 357 accounting, 111, 127, 158, 332, 336 aluminum, xii, 62, 353, 355, 357, 359, 360, 362 accuracy, 82, 91, 112, 229, 237, 268, 283, 345 ambiguity, 18 ACE, 20, 30, 82, 87, 99, 127, 139, 141, 142, 400 amplitude, 14, 66, 74, 84, 88, 104, 113, 131, 315, achievement, 90, 354 414, 415, 416 acid, 163 anaerobic, 148, 149, 152 acoustic, 331, 335, 336 anaerobic digesters, 152 activity level, 178, 187, 400 angular momentum, 277 ADA, 318 angular velocity, 392, 399 aerosols, 16, 40, 187 animals, 149 aerospace, 222, 404 anisotropy, 100 Africa, 11, 33, 48, 67, 168 annihilation, 295 age, 68, 272, 289, 345 annuals, 171 ageing, 127 anomalous, 187 agents, 2, 20, 157, 175 Antarctic, 8, 55, 79, 177, 193 aggregates, 282, 289 antenna, 357 agricultural, 154, 165, 169, 342, 343 anthropogenic, 2, 4, 5, 15, 17, 158 agriculture, 155, 163, 169 application, viii, 26, 30, 68, 78, 145, 146, 166, 173, aid, 167 222, 223, 244, 251, 287, 348, 351, 364, 376 AIP, 337, 376 appraisals, 167 air, xi, 2, 6, 7, 9, 11, 12, 15, 18, 19, 21, 23, 26, 42, 45, appropriate technology, 175 47, 48, 49, 51, 53, 55, 58, 59, 69, 70, 77, 153, 155, Archimedes, 65 160, 167, 168, 170, 172, 173, 174, 191, 192, 198, Arctic, viii, 7, 9, 67, 77, 177, 179, 191, 192 221, 341, 342, 345, 347 Argentina, 13, 391 Air Force, 318

A

420 argument, 169, 239, 240, 248, 249, 250, 251, 252, 253, 259, 261, 264, 267 Arizona, 28, 74, 197, 222, 224, 289, 364, 376 Armenia, 23, 25 ash, 151, 167 Asia, 3, 11, 168, 175 Asian, 17 aspect ratio, 284, 286 asphalt, 151 assessment, 164, 336, 411 assumptions, 42, 157, 335, 344 asymmetry, 116, 132, 140, 329, 330 asymptotic, 257, 259, 261 asymptotically, 249, 252, 256, 257, 260, 261 asymptotics, 415 Athens, 57 Atlantic, 7, 9, 21, 41, 47, 55, 59, 67, 70, 79 Atlantic Ocean, 41 Atlas, 144, 351, 404, 409 atmosphere, vii, viii, 3, 4, 9, 12, 15, 18, 19, 20, 27, 35, 39, 41, 44, 45, 46, 47, 51, 53, 55, 58, 59, 60, 62, 63, 68, 69, 70, 73, 75, 137, 145, 158, 161, 177, 178, 179, 180, 181, 182, 184, 185, 186, 187, 188, 189, 190, 191, 193, 195, 196, 198, 218, 292, 313, 320, 344 atmospheric pressure, 45, 73 atoms, 45, 58, 156, 263, 264, 321, 326 Aurora, 54 Australia, 34, 55, 79, 379 authenticity, 68 automobiles, 147 availability, 2, 148, 149, 158, 160, 169, 342, 343 averaging, 112, 189, 237, 240, 247, 324 aviation, 198, 222

Index biotechnology, 169 birds, 167 black body, 374 black hole, 62 blowing agent, 157 boats, 148 boiling, 160 Boltzmann constant, 184, 264 bonding, 156 booms, 355 boreal forest, 73, 74, 75 Boston, 291, 411 boundary conditions, 190, 325 Brazil, 33 Britain, 67, 163 British Columbia, 5, 74, 78 Brooklyn, 197, 353, 367, 379 Brussels, 175 bubble, vii, 320 Buenos Aires, 391 building code, 158 buildings, 146, 160, 173 Bulgaria, 23, 25, 67, 78 burn, 35, 50, 60, 72, 76, 151 burning, viii, 27, 28, 30, 34, 35, 39, 50, 59, 68, 69, 70, 145, 163

C

cables, 202 campaigns, 165 Canada, 55, 73, 74, 78, 182, 418 capacitance, 217, 363 capacity building, 167 capital cost, 147, 160 carbon, 4, 72, 152, 158, 160, 163, 166, 167 B carbon dioxide, 4, 152, 158, 163, 167 carbon monoxide, 4, 167 balance of payments, 146 cardboard, 151 Balkans, 24, 58, 61 carrier, 147 batteries, 147 case study, 73, 411 battery, 171 behavior, viii, x, 21, 27, 67, 69, 81, 83, 109, 122, 126, Caspian, 29, 30, 32 cast, 67, 172 131, 137, 179, 227, 228, 251, 253, 257, 259, 261, catalyst, 3 266, 269, 273, 286, 292, 321, 327, 329, 333, 334, catastrophes, 26 335, 336 Caucasus, 30 Belarus, 22, 23 causality, vii, 1, 30, 68 Belgium, 23, 25 cavities, x, 291, 294, 295, 296, 297, 298, 299, 301, benefits, 157, 163 302, 303, 306, 308, 310, 311, 313, 314, 315 biodiversity, 170 CDC, 296, 299, 311 biofuels, 174 cell, 147, 321, 324, 325, 327, 333 biogas, 152 cement, 151 Biogas, 152, 175 Central America, 168 biomass, 69, 154, 157, 165, 166 Central Europe, 59 biosphere, 62

Index CERN, 20 certificate, 376 CH4, 148, 152 changing environment, 58 channels, 153, 308 charcoal, 156 charge density, 206, 209, 329, 330 charged particle, vii, x, 20, 41, 53, 63, 69, 70, 182, 183, 184, 185, 186, 187, 188, 195, 200, 201, 204, 205, 206, 219, 228, 291, 292, 294, 295, 298, 301, 304, 306, 307, 308, 310, 311, 313, 314, 315, 320, 330, 335, 356, 358, 379, 381, 382, 387 chemicals, 157 China, 351 chlorofluorocarbons (CFCs), 156, 157 CHP, 149, 157, 158, 159, 164, 175 chromosphere, 96 circulation, 9, 15, 21, 26, 39, 44, 46, 47, 51, 59, 60, 67, 160, 190, 280 classes, 354 classical, 172, 347 clay, 151 climate change, 2, 3, 4, 5, 8, 9, 10, 11, 13, 15, 20, 26, 51, 52, 71, 78, 79, 163, 175 climate warming, 14, 24 climatology, 2 clouds, 15, 16, 18, 19, 39, 51, 59, 69, 74, 77, 139, 326, 343, 348 clusters, 181, 182, 183, 187 CME, 42 CO2, 2, 3, 4, 5, 9, 149, 152, 163, 175 coal, viii, 145, 147, 154, 163, 167 codes, 320 coding, 282 coherence, 21, 55, 69, 400, 416 coil, 161 collaboration, 289 collisions, 55, 62, 183, 184, 185, 188, 189 colors, 330, 393, 395, 398 Columbia, 5, 74, 78 combustion, vii, 1, 39, 149 commodity, 169 communication, xi, 288, 341, 368, 370, 376 communication systems, 368, 376 community, 174 competitiveness, 147 complexity, 133, 137 components, 100, 102, 103, 104, 106, 117, 119, 121, 132, 150, 152, 164, 173, 174, 183, 184, 188, 229, 233, 239, 264, 281, 285, 297, 350 composition, 2, 100, 142, 181, 278, 282 computation, 200, 209, 210, 213, 217, 219, 220, 342, 351, 359, 361, 370, 380, 381, 382, 384

421

computing, 251, 320, 325, 351 concentrates, 20, 228, 370 concentration, 3, 5, 11, 40, 58, 98, 108, 152, 160, 163, 182, 183, 185, 186, 187, 189, 190, 191, 195, 217, 229, 263, 286 concrete, 1, 24, 60, 70, 151 condensation, 160 conditioning, 160 conduction, 160 conductive, 199, 379, 385 conductivity, ix, 161, 162, 178, 181, 185, 191, 192, 195, 292, 293 confidence, 6, 11, 18, 28, 180 confidence interval, 6, 180 configuration, ix, 14, 136, 161, 177, 308, 313, 330, 331, 336 confrontation, 9 confusion, 4, 12, 55, 60 Congress, 73, 198, 221, 222, 223, 387 connectivity, 55 conservation, 163, 170, 172, 343 constant rate, 392 constraints, 170 construction, viii, 145, 151, 162, 163, 168, 175, 355 Construction and demolition, 151 consumption, 147, 148, 150, 162, 163, 168, 174, 219 continuity, 322 control, 26, 51, 75, 106, 143, 171, 173, 174, 178, 190, 202, 358, 370, 375, 385 convection, 38, 69, 75, 300, 392, 400 convective, 25 conversion, 97, 148, 149, 150, 157, 342, 343 conviction, 51 cooking, 147, 148, 151, 167 cooling, 8, 19, 69, 149, 157, 165, 167, 191, 192, 385 corona, vii, xiii, 63, 82, 83, 195, 289, 292, 413, 416 coronal mass ejection, 16, 19, 20, 42, 55, 62, 139, 142 correlation, xi, 14, 16, 18, 28, 66, 109, 131, 132, 135, 180, 181, 186, 192, 195, 299, 311, 341, 343, 345, 347, 349, 350 correlation coefficient, 28, 66, 186, 192 correlations, xi, 18, 77, 100, 191, 341, 345, 347, 350, 351 corridors, 125, 130, 134 corrosive, 160 cosmic ray flux, 17, 78, 182, 183 cosmic rays, 17, 19, 20, 51, 58, 62, 73, 74, 78, 142, 182, 187, 316 cost-effective, 163, 164 costs, 148, 154, 160, 161, 163, 170 Coulomb, 107, 184, 205 coupling, ix, 75, 177, 179, 181, 220

422

Index

covering, xi, 153, 319, 320 CPU, 283 crack, 53 creativity, 62 credit, 170 critical value, 385 criticism, 5 Croatia, 23, 25 crop residues, 147, 151 crops, 156, 157, 171, 172 cross-sectional, 20 CRS, 73 crust, 11 cryogenic, 151 cultivation, 168 cultural heritage, 163 culture, 169 currency, 382, 383, 384, 386 customers, 162 cycles, vii, 12, 13, 66, 67, 81, 82, 83, 84, 92, 113, 114, 117, 122, 123, 126, 127, 128, 135, 137, 141, 142, 144, 181, 193, 194, 195, 292, 392, 396, 399 cyclone, 9, 51, 59, 79 cyclones, 14, 21, 59, 63 cyclotron, x, 108, 291, 299, 300, 311, 315, 324 Cyprus, 23, 25

D danger, 24, 35, 39, 74 data collection, 343, 405 data processing, 24, 28, 112 data set, vii, 11, 81, 82, 87, 88, 112, 114, 116, 135, 140, 180, 194, 393 database, 68, 127, 138, 283, 342 dating, 392 decay, 313, 331, 336 decision makers, 166 decomposition, 152, 233, 238 decompression, 137 deficiency, 96, 97 definition, 292 deforestation, 148 degradation, 155 delivery, 198, 222 Denmark, 23 depressed, 294, 295 depression, 295 derivatives, 246, 248, 249, 255 designers, 170 destruction, 39, 165, 228, 231 detection, 55 developed countries, 150, 151, 167, 169

developing countries, 147, 150, 151, 156, 167, 170, 342, 351 deviation, 40, 57, 88, 89, 90, 91, 93, 96, 102, 122, 123, 125, 126, 127, 130, 134, 200, 217, 334, 335 diamonds, 304, 313, 314 dielectric constant, 184 dielectric materials, 372 dielectric permittivity, 414, 415 differential equations, 241, 243 diffraction, 416 diffusion, 167, 314 diffusivity, 161 digestion, 148, 149 dipole, xi, 106, 136, 282, 287, 306, 319, 320, 321, 326, 331, 332, 333, 334, 335, 336, 374 direct measure, 82, 333 directives, 63 disaster, 36, 38 discharges, 9, 27, 68 Discovery, 287 discretization, 325 dispersion, 46, 70, 88, 89, 90, 91, 104, 122, 123, 125, 126, 127, 130, 131, 132, 133, 134, 135, 136, 308, 380 displacement, 21, 322, 323 distribution function, xiii, 84, 95, 322, 403, 404 district heating, 149 divergence, 13, 414 diversity, 79, 170, 392 division, 106 dollar costs, 163 drainage, 151 drought, 4, 14, 15, 26, 67, 69, 74, 75 droughts, 14, 50, 163 dry ice, 191 dung, 147, 151 duration, xi, 82, 83, 87, 88, 96, 104, 112, 117, 123, 143, 179, 341, 342, 344, 346, 347, 348, 399, 405 dust, x, 174, 227, 228, 229, 230, 231, 234, 238, 241, 243, 244, 245, 247, 248, 250, 251, 252, 253, 254, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289

E earth, 33, 42, 65, 67, 87, 116, 160, 161, 163, 174, 298, 342, 343, 344, 354 Eastern Europe, 168 ecological, vii, 1, 73, 163, 166, 170, 171 economics, 71, 163 ecosystem, 26 ecosystems, 170 electric charge, 58, 60, 63, 210, 218, 284, 285, 363

Index electric circuit, ix, 177, 179, 180, 181, 184, 190, 191, 192, 195 electric conductivity, ix, 178, 191, 192, 293 electric current, 181, 184, 185, 186, 188, 190, 191, 192, 375, 381, 384 electric energy, 181, 198, 206 electric field, x, 40, 56, 83, 105, 106, 119, 121, 130, 132, 143, 181, 184, 185, 186, 187, 190, 195, 202, 205, 206, 217, 219, 293, 299, 300, 301, 310, 311, 312, 315, 322, 323, 325, 326, 327, 329, 330, 333, 336 electric power, 69, 404 electrical power, 354 electrical resistance, 185 electricity, 149, 150, 152, 154, 157, 160, 162, 163, 199, 342, 351, 368, 370, 376, 409 electricity system, 149 electrodes, 204 electromagnetic, viii, x, 1, 19, 20, 30, 33, 35, 36, 39, 43, 54, 63, 64, 70, 77, 78, 108, 137, 177, 178, 190, 195, 227, 228, 234, 237, 238, 239, 243, 244, 246, 259, 261, 268, 269, 271, 275, 276, 277, 278, 279, 280, 281, 282, 284, 286, 288, 291, 300, 306, 315, 322, 330 electromagnetic wave, 19, 30, 33, 35, 36, 39, 54, 63, 70, 322 electromagnetic waves, 19, 30, 33, 35, 36, 39, 54, 63, 70, 322 electromotive force (EMF), ix, 177, 179, 190 electron, 13, 19, 20, 39, 55, 63, 108, 109, 111, 143, 182, 183, 184, 186, 188, 206, 207, 217, 218, 294, 295, 299, 300, 302, 303, 308, 310, 311, 312, 321, 322, 323, 326, 331, 382, 386, 387, 416 electron charge, 322, 386 electron density, 13, 143, 322, 416 electrons, vii, xii, 33, 42, 46, 58, 107, 183, 184, 186, 198, 200, 201, 206, 216, 218, 292, 294, 301, 302, 304, 305, 307, 308, 309, 310, 312, 314, 320, 322, 323, 356, 367, 369, 381, 382, 386 electrostatic force, 362 emission, vii, xiii, 1, 2, 5, 15, 20, 55, 70, 75, 122, 158, 160, 235, 272, 281, 413, 414, 416 emission source, 158 employees, 10 employment, 147, 169, 175 encouragement, viii, 145, 146, 147, 149 endurance, 374 energy audit, 164 energy channels, 308 energy consumption, 147, 150, 163, 168, 174 energy density, 360 energy efficiency, 145, 146, 149, 157, 158, 163, 167, 172

423

energy recovery, 150, 163 energy supply, 147, 148, 156, 157 energy transfer, 178 engines, viii, 145, 149, 162 England, 21 enterprise, 169 Enthalpy, 98 entropy, 112, 114 environment, 19, 40, 54, 68, 73, 76, 145, 146, 148, 149, 152, 155, 163, 167, 168, 170, 172, 306, 336, 343 environmental control, 174 environmental impact, 148, 149, 155 environmental issues, 165 environmental protection, 163 environmentalists, 163 equality, 88 equilibrium, 137, 182, 186, 190, 235, 386 equilibrium state, 235 erosion, 171, 231 estimating, 352, 404, 411 Estonia, 23, 25 ethanol, 154 Ethanol, 154 Europe, vii, 1, 2, 3, 21, 22, 23, 24, 28, 29, 30, 31, 32, 41, 49, 53, 58, 60, 62, 67, 70, 72, 149, 160 European Community, 351 European Space Agency, 74 European Union, 149 evaporation, 279, 280, 281, 286 evolution, x, xiii, 26, 74, 138, 227, 228, 239, 240, 241, 242, 243, 244, 246, 247, 249, 250, 251, 252, 253, 254, 256, 257, 258, 259, 260, 261, 264, 265, 269, 272, 276, 277, 278, 279, 286, 287, 329, 333, 391 exclusion, 171 exploitation, 154, 160, 382 explosions, 54 exposure, 56 extinction, 234 extraction, 160, 168 extrapolation, 15 Extraterrestrial, 341

F fabric, 148 failure, 5, 356 FAO, 22, 23, 25, 28, 68, 73 farmers, 154, 169, 170 farming, 147, 174 fear, 10 feedback, 11, 20 feet, 201

424 ferrous metal, 151 fertiliser, 170 Feynman, 76, 100, 104, 140, 142, 400, 401 FFT, 112 film, ix, xi, xii, 197, 198, 199, 201, 202, 204, 223, 353, 354, 355, 356, 357, 359, 360, 361, 367, 369, 370, 376 film thickness, 359, 360 films, 370 filtration, 270 finance, 163 financial resources, 167 financing, 167 finite differences, 324 fire, 2, 4, 5, 14, 16, 22, 24, 25, 26, 27, 28, 30, 33, 34, 35, 38, 39, 41, 47, 60, 68, 69, 70, 71, 72, 73, 74, 75, 76, 78, 79, 157 fire event, 69 fire suppression, 27 fires, vii, 1, 2, 3, 4, 9, 13, 14, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 35, 36, 37, 38, 39, 41, 47, 48, 50, 51, 52, 58, 59, 60, 61, 62, 63, 65, 68, 69, 70, 71, 72, 73, 74, 75, 76, 78, 147 firewood, 156, 165 fish, 167 fission, 150 flame, 35, 48 flank, 26 flare, 19, 32, 33, 39, 56, 67, 76, 114, 392, 401 flatness, 89 flexibility, 171 flight, xii, 197, 198, 205, 212, 220, 371, 372, 375, 379 flow, xi, 16, 19, 39, 41, 46, 48, 51, 53, 69, 96, 98, 109, 136, 143, 161, 167, 192, 198, 200, 204, 217, 229, 234, 289, 292, 319, 320, 321, 329, 331, 332, 334, 335, 336, 356, 369, 372, 383, 386 fluctuations, x, 75, 104, 139, 140, 154, 291, 298, 299, 300, 302, 303, 306, 310, 311, 312, 315, 415, 416 flue gas, 149 fluid, 160, 161, 320, 321, 322, 323, 324, 326, 328, 329, 332, 333, 335, 375 foams, 157 focusing, 167 food, 147, 150, 154, 156, 163, 167, 169, 170 football, 354 forecasting, 4, 10, 19, 70, 78, 144, 343 forest fire, vii, 1, 2, 4, 9, 13, 14, 16, 21, 22, 23, 24, 26, 27, 28, 29, 30, 35, 38, 50, 58, 63, 65, 68, 70, 71, 73, 74, 75, 78, 79 forest fires, vii, 1, 2, 4, 9, 13, 14, 21, 22, 23, 24, 26, 27, 28, 29, 30, 35, 38, 50, 58, 63, 65, 68, 70, 71, 73, 74, 78

Index forestry, 24, 73, 74, 76 forests, vii, 1, 5, 24, 50 fossil, 146, 148, 151, 154, 157, 163, 167 fossil fuel, 146, 148, 151, 154, 157, 163, 167 fossil fuels, 146, 148, 151, 154, 157, 163 Fourier, 82, 83, 112, 139 Fourier analysis, 139 fragmentation, 114 France, 13, 23, 25, 29, 38 frequency distribution, 404, 409 friction, 45 fuel, viii, 2, 26, 27, 69, 145, 148, 149, 152, 154, 162, 163, 164, 168, 197, 355 fuel type, 27 funds, 146 furniture, 151

G galactic, 16, 20, 51, 70, 142, 187, 195 Galileo, x, 275, 276, 278, 287 Gamma, 29 gas, x, 4, 10, 16, 41, 97, 99, 107, 108, 109, 111, 149, 152, 154, 157, 158, 162, 163, 167, 175, 183, 198, 227, 228, 263, 264, 265, 266, 267, 268, 269, 270, 272, 321, 326, 356, 369, 370, 374 gas turbine, 152 gases, 3, 152, 157, 185, 198, 356, 369 gasification, 151, 157 Gaussian, 88 generalization, 242, 244, 284, 322 generation, 82, 109, 148, 149, 151, 161, 163, 351, 411 generators, ix, 153, 177, 181, 198, 203, 219, 411 geomagnetic field, 41, 44, 55, 75, 183, 293, 297, 298, 304, 305, 306, 314 geometrical optics, xiii, 413, 414, 415, 416 geophysical, 32, 75, 78 geothermal, 160, 161, 162 geothermal field, 160 Germany, 23, 25, 143 glaciers, 7 glass, 151, 164, 171, 172, 173 glasses, 287 global climate change, 5, 400 global warming, 3, 4, 5, 6, 9, 10, 13, 14, 15, 26, 27, 69, 73, 75, 76, 78, 148 goodness of fit, 348 government, 10, 51, 149, 158, 170, 382 grains, x, 12, 227, 228, 238, 243, 244, 258, 259, 261, 263, 265, 266, 272, 273, 275, 276, 277, 283, 286, 287, 288, 289 grants, 138, 337, 382 graphite, 287

Index grass, 75 gravitation, 238, 262, 372 gravitational constant, 238, 276 gravitational effect, x, 245, 275 gravitational field, 370 gravitational force, 43, 45, 50, 228, 243, 244, 276, 277 gravity, vii, x, 227, 262, 263, 265, 266, 267, 268, 269, 275, 276, 277, 279, 281, 284, 364, 370 Greece, 23, 25, 29, 58, 417 Green Revolution, 170, 175 greenhouse, 3, 4, 5, 9, 10, 11, 16, 27, 72, 148, 155, 158, 163, 164, 168, 171, 172, 173, 174, 175 greenhouse gas, 3, 4, 10, 11, 158, 163 greenhouse gas (GHG), 158 greenhouse gases, 3, 4, 11 Greenland, 6 grid services, 147 grids, vii, 324, 354 grouping, 84 groups, 39, 164, 310 growth, 7, 8, 27, 128, 131, 144, 149, 157, 169, 329 GSM, 106, 304, 305 guilt, 68 guilty, 69 Guinea, 33

425

hemisphere, 7, 12, 18, 44, 70, 76, 182, 189, 297, 298, 302, 307, 309, 399 heuristic, 16 high pressure, 99, 218 high temperature, vii, 1, 14, 96, 97, 126, 135, 374 high-speed, 19, 41, 65, 72, 104, 144, 198, 356, 367, 369 histogram, viii, 81, 83, 103, 122, 123, 125, 126, 127, 128, 130, 131, 132, 133, 134, 135, 243, 409, 410 Hm, 45, 345 Holland, 318 Holocene, 74, 75 Hong Kong, 404 hospitals, 148 hot water, 160, 161, 165, 167 household, 165 households, 163, 169, 342 housing, vii, 1, 149, 170 human, 2, 53, 148, 149, 163, 167, 174, 195 human activity, 195 humans, 2, 15 humidity, 2, 26, 51, 59, 168, 172, 173, 174, 192 Hungary, 61 hurricanes, 163 hybrid, xi, 108, 167, 319, 320, 321, 322, 323, 325, 331 hydro, 4, 174 H hydrocarbons, 4 hydrodynamic, 19, 45, 48, 55 H1, 347, 348, 381, 382 hydrogen, 154, 160, 263, 264, 266, 267, 269 H2, 347, 348, 382 hydrogen atoms, 263, 264 handling, 162 hydrogen gas, 266, 267, 269 harmonics, 112, 114, 117, 119, 121 hydropower, 146, 167 hazards, 3, 61, 74, 150, 356 hyperbolic, 200, 201, 202, 277, 278 health, 15, 24, 163 hypothesis, 18, 19, 30, 39, 41, 47, 51, 55, 60, 63, 66, heart, 343 68, 69, 191 heat, 3, 25, 72, 77, 147, 149, 151, 152, 157, 160, 161, hysteresis, 83, 122, 131, 140 168, 170, 171, 172, 173, 190, 368, 369, 370, 372 heat loss, 173 I heat transfer, 25 IAC, 221, 222, 387 heaths, 104 Iberian Peninsula, 51 heating, ix, 21, 62, 66, 82, 146, 147, 148, 149, 151, ice, 6, 7, 8, 11, 12, 79, 191, 192, 193, 195, 196, 262 165, 167, 172, 174, 178, 181, 184, 186, 188, 189, ICE, 143 190, 191, 342, 368, 370 identity, 170, 322 heating rate, 66, 188, 189 IDP, 231, 232, 233, 234, 238, 239, 243 heavy particle, 53, 383 images, 64 height, xiii, 14, 70, 88, 90, 180, 182, 183, 403 IMF, vii, xi, 17, 21, 55, 63, 75, 81, 82, 83, 85, 86, 87, heliosphere, 82, 100, 116, 137, 139, 140, 142, 144, 88, 100, 101, 102, 103, 104, 105, 106, 108, 111, 263, 264, 269, 270, 276, 288 112, 117, 119, 121, 122, 128, 130, 131, 132, 133, helium, 86, 98, 99, 108, 127, 273, 299, 301, 302, 303, 135, 136, 137, 141, 142, 187, 189, 297, 298, 313, 308, 311 319, 326, 329, 330, 336 helix, 44 implementation, 157, 167, 321, 325 helplessness, 15 imports, 146, 147

426 impurities, 160 in situ, x, 55, 82, 143, 291, 295, 304 incentives, 154, 165, 170 incidence, 4, 20, 27, 234, 282, 284 incineration, 163 inclusion, 191, 280 income, 167, 169 India, 33, 404, 411 Indian, 18, 41, 72 Indian Ocean, 41 indication, 51, 112, 179, 182 indices, 12, 14, 27, 114, 178, 400, 401 induction, 43, 44, 45, 46, 47, 60 industrial, 6, 7, 15, 147, 149, 150, 159, 162, 169, 175, 342 industry, viii, 145, 147, 149, 152, 155, 163, 404 inefficiency, 154 inequality, 256, 257 inertia, 323, 343 infinite, 217, 218, 220, 277, 414 infrared, 284 infrastructure, 147, 167, 170 inherited, 117, 133 inhomogeneities, 83, 137, 415, 416 initiation, 2, 27, 74 injections, 195, 306, 336 innovation, 156, 198, 218, 220, 224, 364, 368, 385 inspection, 38, 39, 329 instabilities, 289 institutions, 13, 342 instruments, 10, 30, 34, 35, 38, 39, 51, 54, 60, 63, 71, 82, 342 insulation, 150, 151, 164, 167, 168, 174, 201 insurance, 163 integration, 148, 200, 243 integrity, 169 interaction, ix, 13, 18, 53, 58, 96, 97, 100, 104, 117, 137, 178, 182, 183, 184, 187, 199, 200, 203, 232, 235, 236, 237, 244, 281, 283, 294, 311, 313, 320, 321, 335, 336, 382 interdisciplinary, 69 interface, 336, 392 interference, xiii, 112, 114, 116, 117, 121, 413, 414, 415, 416 Intergovernmental Panel on Climate Change (IPCC), 2, 5, 6, 26, 163, 175 International Energy Agency (IEA), 175 interplanetary medium, 42, 62, 85, 104, 106, 143, 374 interstellar dust, x, 275, 276, 277, 278, 279, 280, 283, 285, 287, 288, 289 interval, 83, 85, 88, 93, 95, 96, 101, 102, 104, 105, 106, 110, 111, 113, 115, 119, 120, 122, 123, 132,

Index 178, 198, 242, 261, 265, 278, 280, 311, 326, 344, 356, 369, 399, 405 intrinsic, 27 investment, 157, 164 ion-clusters, 181, 187 ionic, 186 ionization, 79, 182, 183, 187, 189 ionosphere, 19, 20, 53, 55, 178, 181, 190, 195, 196, 415 ions, ix, xi, 45, 53, 98, 177, 182, 183, 184, 185, 186, 187, 188, 195, 217, 218, 292, 294, 295, 296, 301, 303, 304, 306, 308, 311, 313, 314, 315, 319, 320, 321, 322, 323, 324, 327, 329, 330, 331, 336 IOP, 333, 334, 335 irradiation, 341, 343, 344, 346, 347, 348, 349 irrigation, 170 Israel, 22, 223, 376 Italy, 29, 58, 61, 345, 351

J Japan, 54 Japanese, 356 Jerusalem, 223 jobs, 163 joints, 164 Jordan, xi, 289, 341, 345, 347, 350, 351 Joule heating, ix, 178, 181, 184, 186, 188, 189, 190, 191 judge, 114 justification, 18, 30

K Kazakhstan, 23, 25 kinetic energy, vii, 42, 43, 50, 55, 65, 70, 95, 97, 99, 184, 202, 215, 292, 311, 312, 313 kinetics, 321 King, 82, 92, 100, 102, 138, 139, 141, 143, 196, 392, 400 Kosovo, 35 Kyoto protocol, 3, 166

L land, 2, 7, 8, 9, 13, 15, 28, 36, 76, 149, 154, 160, 168, 169, 170 land use, 169 landfill, 151, 152, 157, 158, 159, 175 landfill gas, 152, 158, 175 landfills, 158, 162 large-scale, 15, 78, 82, 100, 137, 169, 416 lasers, 355, 356 lattice, 287 Latvia, 23, 25

Index law, 46, 73, 178, 205, 245, 292, 293, 303, 304, 323, 329, 336 laws, 50, 70, 240, 404 legislation, 162 lettuce, 171 lifetime, 392 light scattering, 283 light transmission, 172 limitation, 416 limitations, 112 linear, 6, 7, 45, 47, 84, 85, 90, 91, 96, 97, 112, 117, 206, 218, 347, 348, 359 linear model, 347 linear regression, 348 linkage, 51 links, 5, 11, 52, 137, 167, 170, 202 liquid water, 18 liquids, 154 Lithium, xi, 319, 321, 326, 327, 329, 330, 333 Lithuania, 23, 25 Little Ice Age, 75 livestock, 169 living standards, 167 loading, 26 lobby, 163 location, 14, 19, 26, 27, 29, 343, 344, 348 lognormal, 85, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 102, 106, 109, 110, 111, 113, 123, 126, 127, 131, 133, 135, 136, 137 London, 71, 221, 271, 272, 289, 364, 376, 387 long distance, 219 long period, 21, 53, 182, 320, 342 long-distance, 368, 370, 376 longevity, 165 losses, 39, 44, 216 low temperatures, 126 low-density, 99 low-income, 167 low-temperature, 97 luminosity, 17, 238

M Macedonia, 23, 25 machinery, 148 machines, viii, 145, 147, 149, 404 magnesium, 277, 278, 284, 286 magnet, 321, 331, 332, 333, 334 magnetic moment, 295, 313, 314, 315, 332, 336 magnetic structure, 29, 399 magnetism, 65 magnetosphere, ix, x, 12, 18, 20, 21, 39, 40, 41, 42, 43, 53, 54, 55, 56, 62, 63, 64, 65, 69, 70, 87, 106, 109, 143, 178, 179, 190, 199, 291, 292, 293, 297,

427

298, 306, 309, 313, 314, 315, 316, 320, 321, 331, 336 maintenance, viii, 145, 147, 148, 164, 170, 174, 343, 355 management, 26, 157, 158, 162, 163, 169, 175 man-made, 10, 26 manpower, 342 mantle, 63 market, 158, 160, 163, 166, 169, 170 marketing, 166 markets, 169, 343 Markov, 404, 411 Markov chain, 404, 411 Mars, ix, 6, 114, 197, 198, 215, 221, 225, 355 Martian, 320 mask, 399 Massachusetts, 71, 411 mathematics, 68 matrix, 282, 283 meanings, 348 measurement, 10, 55, 333, 342, 343, 405, 406 measures, 24, 68, 69, 70, 158, 162, 164, 166, 170, 173, 174 media, 9, 33, 414, 415 median, 88, 90, 91, 92, 97, 99, 104 Mediterranean, 24, 38, 73, 404, 411 megawatt, 53 melon, 172 melt, 375 melting, 7, 8 melts, 8 memory, 41, 137 men, 27, 69, 201 Mercury, xii, 114, 367 meridian, 96, 97 messages, 16 metals, 159 meteor, 35, 273 meteorological, 11, 13, 16, 30, 51, 59, 62, 63, 70, 342, 343, 344, 404 methane, 4, 149, 152, 158, 159, 160 methanol, 154 metric, 168 Mexico, 28, 74 MHD, 137, 289, 320, 321, 322, 331, 336, 374 micrometer, 356 microorganisms, 157 micro-turbine, 162 microwave, 151 military, 354 mineralogy, 287 mining, 163 Minnesota, 151

428

Index

mirror, xii, 200, 202, 203, 204, 354, 355, 358, 359, 364, 367, 368, 369, 370, 372, 375 misconception, 157 misleading, 43, 67 missions, 4, 71, 116, 145, 149, 158, 159, 163, 168, 175, 320, 354 MIT, 71, 141, 338 mites, 174 MLT, 294, 296, 300, 302, 307, 311 mobility, 185 modeling, 27, 55, 75, 137, 179, 244, 283, 321, 336, 404, 411, 415, 416 models, ix, 2, 4, 5, 11, 14, 26, 44, 56, 63, 65, 67, 69, 140, 142, 172, 178, 191, 196, 203, 312, 322, 343, 351, 400 modulation, 139, 316 modules, 171, 343 moisture, 14, 19, 51, 69, 79, 174 molecules, 51, 183, 185, 187, 188 momentum, x, 108, 111, 137, 229, 231, 232, 234, 235, 236, 237, 277, 291, 355 money, 168, 382 monsoon, 17, 72 Montana, 141 Moon, xii, 221, 222, 270, 271, 353, 364 Moscow, 76, 81, 143, 144, 196, 221, 223, 365, 376, 417 moulding, 151 mountains, 34, 167, 343 movement, ix, xiii, 13, 60, 70, 178, 183, 391 MPI, 325, 338 multifractal, 131, 138 multiplication, 106, 132, 136 municipal solid waste (MSW), 162

negligence, vii, 1 neighbourhoods, 170 Netherlands, 73, 316 network, 10, 342 neutrons, 60, 313 Nevada, 5 New Mexico, 28, 74 New York, 77, 138, 175, 269, 270, 287, 289, 317, 318, 351, 417 NGOs, 158, 162 Ni, 182, 183, 184 Nielsen, 338 nitrogen, 152, 160, 167 nitrogen oxides, 167 NOAA, 9, 19, 76, 77, 140, 141, 143, 144, 354 nodes, 325 noise, 91, 143, 163, 167, 170 nonlinearities, 137 normal, viii, 40, 52, 60, 69, 81, 88, 89, 90, 91, 92, 97, 99, 100, 104, 105, 106, 137, 161, 233, 277, 404 normal distribution, 88, 89, 100, 137, 404 normalization, 9 North America, 21, 28, 77, 160, 168 North Atlantic, 9, 59, 67, 79 Northern Hemisphere, 13, 76 Norway, 23 nuclear, 146, 148, 150, 163, 167, 204, 216, 217, 219 nuclear charge, 216 nuclear power, 146, 148, 163, 167 nucleation, 18, 40 nucleons, 20

O

obligation, 160 observations, xi, 6, 10, 11, 16, 17, 30, 32, 41, 53, 54, 55, 58, 62, 67, 68, 75, 99, 137, 139, 140, 178, 244, NAS, 418 291, 292, 297, 299, 302, 304, 305, 306, 310, 313, NASA, 3, 6, 19, 54, 77, 138, 139, 187, 189, 196, 201, 314, 321, 334, 374, 411 225, 284, 287, 289, 315, 317, 318, 354, 362, 365, Oceania, 168 370, 371, 375, 377, 380, 382, 388 oceans, viii, 11, 145 National Oceanic and Atmospheric Administration oil, viii, 145, 146, 147, 154, 163, 167 (NOAA), 9, 354 oil spill, 163 NATO, 316 opposition, 5, 9 natural, viii, 3, 5, 6, 9, 15, 41, 61, 73, 88, 97, 113, optical, 238, 241, 245, 266, 267, 282, 283 145, 154, 158, 160, 163, 165, 167, 168, 170, 174, optical properties, 238, 241, 245, 266, 267, 282, 283 192, 205, 243, 245, 413 optics, xiii, 413, 414, 415, 416 natural capital, 73 optimization, 325 natural gas, 154, 158 Oregon, 71 natural resource management, 163 organic, 152 natural resources, viii, 145, 165, 170, 174 organic compounds, 152 NEA, 342, 351 orientation, 102, 103, 104, 106, 132, 171, 187, 234, negativity, 358 237, 264, 282, 283, 284 neglect, 108, 109, 234, 381, 382, 386 orthodox, viii, 145

N

Index oscillation, 141, 253 oscillations, 15, 67, 112, 114, 143, 261 oxides, 167 oxygen, 142, 152, 156 ozone, ix, 9, 16, 44, 53, 58, 156, 157, 178, 181, 182, 188, 189, 190, 191

P Pacific, 7, 14, 41, 55, 67, 69, 76 packets, 154 Pap, 392, 401 parabolic, 204 parameter, 83, 88, 89, 90, 91, 92, 99, 117, 121, 122, 135, 136, 137, 144, 178, 186, 187, 188, 189, 192, 238, 245, 246, 252, 254, 255, 259, 260, 263, 277, 278, 279, 283, 321, 332, 333, 335, 342, 345, 393, 395, 398, 404, 409, 411, 414 particle density, 32, 70, 208, 209 particle shape, 282 particulate matter, 4 passive, ix, 175, 177, 181 pathways, 154 Pb, 45 PCA, 9 per capita, 150 perception, 10 periodic, 11, 14, 83, 187, 326, 400, 415 periodicity, xii, 71, 82, 113, 114, 116, 117, 121, 127, 131, 135, 139, 141, 142, 195, 391, 392, 393, 396, 399, 400 peri-urban, 169 permafrost, 191, 192 permeability, 323 permit, 219, 310, 387 permittivity, 285 Perth, 34 perturbation, 239, 259, 260, 264, 268, 415 perturbation theory, 415 perturbations, 62, 69, 246, 416 pesticide, 170 phase shifts, 131 phase space, 313, 314, 315, 326 Philadelphia, 338 photochemical, 184 photon, 62, 204, 231 photons, xii, 204, 234, 235, 236, 355, 367 photovoltaic, 343 photovoltaics, 342 physical properties, 106 physicists, 20, 21 physics, 5, 10, 15, 54, 66, 68, 71, 78, 82, 88, 178, 220, 228, 243, 288, 292, 306, 321, 322, 413 pilot studies, 167

429

pitch, 305, 313 PL, 225, 362 plague, 354 planar, 244, 250, 277 Planck constant, 231 planetary, 18, 67, 72, 99, 113, 114, 197, 218, 246, 251, 252, 253, 260, 261, 320, 336 planets, x, xii, 113, 114, 116, 139, 219, 220, 227, 228, 243, 271, 272, 367, 371, 372, 374, 375 planning, 149, 157, 166, 343 plants, 152, 157, 160, 165, 167, 168, 171, 172, 173 plasma physics, 322 plastic, xi, xii, 62, 151, 353 play, 15, 16, 19, 51, 102, 106, 146, 149, 156, 168, 173 Pliocene, 74 Poland, 23, 24, 58, 59, 61, 78 polarity, 100, 117, 121, 122, 131, 132, 219, 285 polarization, 70, 234, 283, 311, 312 policy makers, 343 pollutants, 152, 174 polluters, 15 pollution, viii, 3, 145, 148, 150, 154, 155 polynomial, 4 polynomials, 112 poor, 14, 62, 85, 91, 95, 99, 131, 161, 169, 172 population, 30, 99, 163, 165, 166, 169, 305, 306, 312 population growth, 169 porosity, 45, 62 porous, 282 Portugal, vii, 1, 2, 13, 23, 24, 25, 29, 30, 41, 47, 48, 50, 51, 55, 73, 75, 76, 337 positive correlation, 191 positive feedback, 20 potential output, 411 poverty, 169 powder, 151 power plant, 146, 148, 149, 157, 168, 173 powers, 342 precipitation, 2, 9, 10, 14, 18, 19, 27, 28, 44, 51, 55, 59, 73, 181, 364 prediction, xi, 4, 26, 39, 66, 68, 333, 334, 335, 341, 343, 345, 350 predictive models, 69 press, 78, 271, 337, 338 prevention, 69 prices, viii, 145, 158, 168, 169, 171, 174 private, 168, 288, 356 probability, 27, 73, 88, 102, 137, 278, 279, 280, 281, 283, 285, 404 probability distribution, 88, 102, 137 probe, ix, 197, 202, 210, 212, 213, 214, 215, 220 producers, 150

430

Index

production, 149, 151, 152, 154, 155, 156, 161, 162, 169, 171, 174, 182, 343 productivity, 169, 175, 343 professionalism, 14 profit, 282 profitability, 169 profits, 163 prognosis, 5, 67, 68 program, 9, 54, 354, 404 propagation, 234, 322, 331, 413, 414 propane, 154 property, 88, 89, 91, 113, 162, 245, 249, 381, 386 propulsion, ix, xi, xii, 197, 198, 199, 200, 202, 203, 204, 218, 219, 220, 319, 320, 353, 354, 355, 356, 367, 370, 376 protection, 24, 26, 151, 163, 171, 201, 320, 321, 335 protocol, 3 protons, vii, ix, xii, 20, 29, 40, 42, 50, 60, 62, 63, 70, 98, 107, 108, 197, 198, 199, 200, 201, 204, 206, 208, 210, 215, 216, 218, 220, 292, 294, 304, 308, 309, 310, 311, 313, 320, 332, 336, 355, 356, 357, 359, 367, 369, 381, 383 prototype, 356 proxy, 10, 72 PSD, 313, 314 pseudo, 382 PTO, 222, 223, 364, 376 public, 4, 5, 27, 35, 149, 154, 170, 382 public health, 170 pulse, 167, 415, 416 pumping, 148 pumps, 381 purification, 148 pyrolysis, 151 pyromania, vii, 1

Q quality of life, 150, 165 quantitative estimation, 83 quasi-periodic, 14

R Radiation, 173, 229, 234, 236, 238, 269, 271, 272, 288, 289, 301, 312, 318, 341, 343, 347, 348, 368 radiation damage, 88 radio, xiii, 122, 357, 370, 413, 414, 415, 416 rain, 2, 15, 18, 148, 163 rainfall, 15, 18, 72, 160 rainwater, 166, 167 random, 88, 90, 106, 112, 137, 344, 350, 415, 416 range, xiii, 11, 38, 75, 84, 87, 96, 97, 100, 104, 109, 111, 113, 114, 116, 122, 132, 133, 135, 148, 150,

152, 155, 161, 165, 171, 185, 186, 198, 219, 276, 303, 311, 312, 313, 334, 355, 356, 369, 374, 375, 393, 395, 396, 398, 399, 403, 404, 410 Rayleigh, 282, 404, 411 reality, ix, 67, 177, 179, 181, 182, 184, 191, 228, 246, 262 recognition, 306 recombination, 55, 182, 183, 187 recovery, 135 recreation, 170 rectum, 241, 242, 243 recyclables, 150 recycling, 148, 150, 151, 157, 163, 175 redistribution, 192 reference frame, 229, 230, 231, 232, 233, 244, 264, 282, 382 reflection, 173, 198, 332, 336, 356, 361, 369 reflectivity, 355, 357, 368, 374, 375 regenerate, 170 regeneration, 59, 151 regional, 5, 7, 9, 10, 13, 16, 18, 21, 24, 51, 69, 147, 155 regression, 342, 344, 346, 347, 348, 350 regression analysis, 344 regression line, 344, 348 regression method, 350 regular, 82, 83, 99, 127, 131, 135, 137, 178, 324, 413, 415, 416 regulation, 74 rejection, 21 relationship, vii, 1, 14, 16, 20, 27, 42, 52, 76, 96, 97, 132, 135, 139, 141, 142, 161, 162, 348 relationships, 20, 25, 26, 69, 78 relevance, xi, 320, 326 reliability, 112, 137, 165 renewable energy, viii, 145, 146, 147, 149, 157, 165, 166, 167, 174, 175, 342 representative samples, 30 research and development (R&D), 342, 351, 411 residues, 147, 151, 156 resistance, 171, 185, 186 resistivity, 40, 322 resolution, 71, 112, 114, 320, 333, 334, 335, 393 resources, viii, 76, 145, 146, 147, 148, 150, 153, 155, 156, 158, 163, 165, 167, 170, 174, 351 retention, 158 returns, 198, 356, 369 revenue, 166 Rhode Island, 222 ring magnet, 381, 382, 383, 386 rings, 10, 73, 265 risk, 25, 79, 158 risks, 158, 163

Index roadmap, 354 robustness, 174 Romania, 23, 25, 61 Rome, 73, 76 rotation axis, 283, 284 rotations, 100, 392 routines, 325 Royal Society, 272, 289 runoff, 170 rural, viii, 145, 146, 147, 148, 150, 151, 160, 165, 167, 169, 342 rural areas, viii, 145, 147, 148, 150, 151, 165, 342 rural development, 165 Russia, 22, 24, 29, 168, 177, 196 Russian, viii, 6, 21, 23, 76, 81, 138, 140, 143, 144, 177, 195, 196, 221, 222, 223, 288, 356, 364, 365, 376, 413 Russian Academy of Sciences, 6, 81, 138

431

seed, 171, 306, 307, 310, 312 selecting, 148 sensitivity, 11, 71 sensors, 144, 304 separation, 162, 198, 219, 308, 400 Serbia, 1, 23, 25, 28, 35, 36, 37, 38, 77 Serbia & Montenegro, 23, 25 series, 6, 11, 13, 18, 21, 28, 33, 35, 56, 65, 67, 189, 194, 198, 219, 393, 395, 398 services, 147, 169 settlements, 167 severity, 4, 10, 158 shade, 172 Shanghai, 351 shape, 16, 35, 72, 91, 92, 99, 102, 108, 122, 136, 170, 182, 268, 282, 284, 333, 404, 409, 411 shock, xi, 19, 20, 75, 96, 109, 137, 140, 270, 319, 320, 321, 326, 329, 330, 333, 334, 335, 336 shock waves, 19, 20 S shocks, xi, 71, 96, 97, 319, 320 shortage, 168 SAE, 222, 223 short-term, 157, 165, 178, 193, 344, 401 safety, 73, 146, 150, 386 Siberia, 21, 55, 72 sales, 163, 165 sign, 11, 14, 20, 21, 33, 55, 192, 218 salinity, 160 signals, 44, 63, 112 sample, 326, 330 signs, 10, 13, 33 sampling, 112, 122 silicate, 277, 278, 284, 286, 287 sand, 12 similarity, 83, 91, 126, 194, 306 satellite, 3, 12, 29, 30, 32, 33, 38, 39, 41, 51, 53, 60, simulation, 14, 25, 70, 320, 321, 324, 325, 326, 327, 63, 68, 77, 85, 92, 178, 189, 201, 272, 292, 295, 331, 332, 333, 334, 335, 336, 343 297, 298, 299, 300, 302, 303, 307, 308, 309, 314, simulations, ix, 25, 72, 75, 178, 190, 260, 285, 312, 370, 374 320, 321, 331, 332, 333, 336, 337 satisfaction, 282 Singapore, 141 saturation, 19, 172 singular, 112 savings, 149, 150 singularities, 415 scalability, 325 sites, 5, 152, 170, 342, 405, 406, 409 scalar, 236 skeptics, 3 scaling, 334 skewness, 88, 89, 91, 93, 97, 99, 100, 102, 104, 106, scatter, 344 111, 126, 133 scattering, xiii, 234, 272, 282, 283, 289, 314, 413, Slovakia, 23, 61 415, 416 Slovenia, 23, 25 sea ice, 192 sludge, 149 sea level, 79, 163, 347 smoke, 47 search, 178, 221, 364, 376, 387 smoothing, 112 searching, 30 snaps, 43 seasonal variations, 192 social benefits, 157 seasonality, 2 social development, 165 seawater, 191, 192 software, 393, 400 secular, x, 11, 113, 227, 228, 239, 240, 241, 242, 243, SOHO, 141 246, 247, 248, 249, 250, 251, 252, 253, 256, 257, soil, 70, 151, 156, 161, 170, 191 258, 259, 260, 261, 264, 265, 266, 268, 269, 286 soil erosion, 156, 170 secular trend, 11 solar cells, 198, 355 security, 163, 169 solar collectors, 146 sediments, 10

432 solar energy, xi, 20, 167, 178, 341, 342, 343, 367, 375 solar plasma, 306, 413 solar prominences, 374 solar system, vii, xii, 20, 51, 62, 68, 198, 263, 288, 342, 343, 354, 355, 356, 367, 369, 375 solid waste, 162, 163 South America, 8, 11, 168 Southeast Asia, 3 Southern Hemisphere, 9 Soviet Union, 223 space environment, x, 42, 197, 320, 337 space exploration, 220, 354, 382 space-time, x space-time, 227, 228, 268 Spain, vii, 1, 13, 23, 24, 25, 29, 48, 73, 404 spatial, 24, 28, 77, 137, 141, 293, 320, 324, 325, 326, 329, 332, 400 species, 7, 170, 181, 313, 323, 324, 325 specific heat, 161 spectral analysis, 121, 311 spectrum, xiii, 82, 112, 116, 140, 237, 276, 277, 278, 303, 304, 359, 368, 374, 375, 391, 392, 393, 395, 396, 398, 399 speculation, 220 speed of light, 63, 208, 217, 229, 276, 309, 322, 355 spheres, 319, 320 spills, 163 spin, 141 sporadic, 4, 69, 415 sputtering, 228 stability, 355 stages, 333, 342 standard deviation, 85, 88, 89, 90, 91, 92, 96, 102, 104, 111 standards, 167 stars, 62, 63, 138 statistical analysis, 88 statistics, 63, 88, 92, 93, 97, 99, 100, 102, 103, 104, 106, 111, 112, 136, 137, 141, 348 steady state, 161, 293 steel, 151, 172 stimulus, 3 stochastic, 26, 51, 62, 75, 273 stochastic processes, 51 storage, 148, 154, 158, 168, 198 storms, vii, viii, 14, 19, 40, 43, 67, 76, 106, 138, 177, 178, 320, 354 strain, 369, 370 strategies, 157, 320 stratosphere, ix, 44, 53, 58, 76, 77, 178, 179, 180, 181, 182, 183, 184, 186, 187, 188, 189, 190, 191, 192, 193, 195

Index streams, 18, 65, 96, 97, 99, 104, 106, 111, 122, 123, 126, 127, 131, 132, 136, 144, 198, 287, 356, 369 strength, 16, 33, 41, 53, 63, 67, 86, 87, 101, 119, 131, 132, 135, 136, 139, 140, 185, 186, 187, 294, 295, 296, 297, 299, 300, 301, 302, 303, 307, 308, 309, 310, 311, 374 stress, 112, 210, 212, 213, 214, 215, 216, 237, 246, 363, 364 stress level, 364 stretching, 104, 223, 376 strikes, 26, 27, 28, 171 subjective, 9 subsidies, 171 substitution, 277 Sudan, v, xi, 341, 342, 343, 347, 348, 350, 351 suffering, 170 summer, 5, 8, 13, 67, 69, 77, 171, 172, 173, 186, 189, 192 sunlight, xi, 171, 173, 174, 353, 355 sunspot, xiii, 5, 13, 17, 20, 42, 66, 67, 69, 74, 83, 84, 91, 112, 113, 114, 116, 117, 121, 122, 123, 127, 131, 133, 135, 178, 194, 292, 391, 392, 395, 398, 400 superimposition, 409 superposition, 113, 117, 135, 414, 415 supply, 146, 147, 148, 149, 158, 165, 169 suppression, 27, 96, 132 surface area, 19, 24, 171, 211, 363 surface water, 170 surpluses, 154, 156 surprise, 16, 26, 65, 292 surveillance, 62 survival, 174 surviving, 285 sustainability, 165 sustainable development, 145, 147, 158, 163, 174 Sweden, 23, 25 Switzerland, 3, 23, 25, 72 symmetry, 40, 89 synchronous, 9, 386 synchrotron, 218 synergistic effect, 169 systems, xi, 27, 39, 69, 149, 153, 160, 164, 203, 219, 222, 227, 228, 321, 336, 342, 343, 346, 356

T Taiwan, 81, 138 tariff, 164, 171 technical assistance, 167, 169 technical change, 170 technology, xii, 27, 62, 151, 153, 157, 165, 166, 169, 219, 220, 353, 354, 355, 356, 379

Index temporal, 6, 11, 15, 24, 28, 69, 77, 135, 136, 137, 194, 298, 320, 413, 416 tensile, 210, 211, 363 tensile stress, 210, 363 terrorist, 30 Texas, 56, 198, 221, 222 thermal energy, 97, 111, 292, 342 thermal properties, 161 thermodynamic, 97 thermodynamic properties, 97 thermonuclear, 203, 204, 217, 219, 220 Thessaloniki, 417 thin film, ix, xii, 197, 198, 201, 204, 223, 354, 355, 357, 367, 369, 370, 376 thin films, 370 Thomson, 76, 112, 143 threat, 26, 169 threatening, 169 three-dimensional, 25, 141 tides, 161 timber, 151 time resolution, 71, 112, 114 time series, 6, 13, 18, 189, 194, 395, 398 tissue, 169 topographic, vii, 1, 39, 70 topology, xiii, 136, 413 torque, 69 total energy, 12, 108, 147, 150, 158, 172, 179 total internal reflection, 369 tourist, 28, 198 toxic, 15, 166 tracking, 79, 321, 326 traffic, 163 training, 157, 164, 166 trajectory, 43, 44, 45, 50, 183, 200, 201, 202, 206, 221, 281, 370, 371, 372, 380, 387, 416 transcripts, 71 transfer, 25, 70, 137, 355 transformation, 137, 158, 229, 230, 231, 232 transformations, 91, 236 transition, 136, 385 transition temperature, 385 transmission, 87, 106, 149, 172, 342, 345 transparency, 346 transparent, 370 transport, 14, 55, 150, 155, 163, 308, 313, 314, 315, 321, 414 transportation, 147, 307 travel, 202, 234 troposphere, 9, 12, 19, 43, 44, 48, 51, 55, 56, 77 trust, 358, 359 tsunamis, 41 tunneling, 19

433

turbulence, 71, 140, 296, 306, 316, 330 turbulent, 137, 306, 334 Turkey, 22, 23, 25, 404, 411 two-dimensional, 102, 103, 104, 415

U UAE, 175 Ukraine, 22, 23, 61, 418 ultraviolet, 53, 62, 321, 351, 355 Ultraviolet, 53 ultraviolet light, 53 umbra, 20, 63 uncertainty, 11, 67, 158, 333 unfolded, 357 uniform, 329, 415 United Kingdom (UK), 76, 79, 145, 154, 160, 175, 196, 272, 341 United Nations (UN), 28, 68, 71, 76, 175, 351 United Nations Environment Program (UNEP), 71, 75 United States, 14, 72, 73, 74, 78 universities, xii, 379, 382 uranium, viii, 145, 163 urban areas, 7, 15, 165, 169, 170 urban population, 169 urbanisation, 154, 156 USSR, 196, 376, 417 UV, ix, xi, 178, 188, 189, 193, 271, 319, 326 UV radiation, ix, xi, 178, 188, 189, 193, 319, 326

V vacuum, 45, 205, 206, 210, 218, 285, 331, 363, 374, 414 valence, 19 validity, 18 vapor, 39, 364 variability, viii, 3, 4, 5, 10, 12, 15, 16, 44, 51, 70, 71, 73, 77, 78, 79, 81, 82, 83, 88, 100, 102, 114, 121, 122, 127, 135, 137, 138, 142, 179, 191, 292, 399, 401 variables, 106, 137, 344 variance, 100 variation, xi, xiii, 14, 17, 82, 89, 102, 104, 116, 117, 122, 127, 128, 131, 132, 133, 135, 140, 144, 161, 195, 293, 294, 295, 296, 303, 307, 308, 313, 329, 341, 391, 393, 396, 399, 400, 404, 405, 407, 408 vector, vii, x, 21, 39, 43, 44, 46, 81, 101, 102, 103, 205, 227, 229, 230, 231, 233, 234, 237, 238, 244, 245, 262, 264, 276, 277, 278, 322, 332 vegetables, 157, 168 vegetation, 7, 14, 15, 27, 30, 39, 68, 70 vehicles, 148, 162, 198, 221, 354

434

Index

ventilation, 167, 171, 174 Venus, xii, 114, 367 village, 35, 51 violence, 62 violent, 63 visible, 53, 63, 292, 330, 334 vision, 69, 157 visualization, 137, 321 vortex, 48, 53, 189 vulnerability, 169

W waking, 163 waste management, 162, 163, 175 wastes, 149, 157, 163, 168 wastewater, 152 wastewater treatment, 152 water, 5, 11, 15, 18, 146, 149, 151, 152, 153, 160, 161, 163, 165, 166, 167, 170, 172, 174, 342, 351 water quality, 163 water vapour, 152, 172 wave number, 414 wave power, viii, 145, 153, 175 wave propagation, 287 wavelengths, 63 wavelet, xiii, 18, 82, 112, 114, 116, 138, 391, 392, 393, 395, 396, 398, 400 wavelet analysis, 82, 138 wavelets, 393 wealth, 169

web, 82, 387 web pages, 387 Weibull, vi, xiii, 403, 404, 409, 411 Weibull Distribution, xiii, 403, 404, 409, 411 West Africa, 33 Western Europe, 168 wholesale, 165 wildfire, 28, 34, 58, 69, 71, 72, 73, 75 wildfires, 4, 28, 69, 74 wildland, 73 wildlife, 169, 170 wind speeds, xiii, 142, 403, 404, 405, 407, 409, 410, 411 windows, 64 winning, viii, 145 winter, 2, 9, 15, 25, 67, 171, 172, 173, 179, 189, 192, 193 wood, 147, 151, 157, 167, 172 Wyoming, 182

X X-axis, 102, 103, 104 X-rays, 62, 187

Y Y-axis, 102 Yemen, 175 yield, 67, 172, 232, 236, 247, 259, 262, 324

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