Nonlinear Time Series Analysis in the Geosciences Applications i
This book presents recent developments in nonlinear time series which have been motivated by present day problems in geosciences. Modern methods of spatio-temporal data analysis, time-frequency analysis, dimension analysis, nonlinear correlation and synch
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Reik V. Donner · Susana M. Barbosa (Eds.)
Nonlinear Time Series Analysis in the Geosciences Applications in Climatology, Geodynamics and Solar-Terrestrial Physics
With 151 Figures
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Editors Dr. Reik V. Donner TU Dresden Institut für Wirtschaft und Verkehr Andreas-Schubert-Str. 23 01062 Dresden Germany [email protected]
Dr. Susana M. Barbosa Universidade do Porto Fac. Ciencias Depto. Matematica Aplicada Rua do Campo Alegre 687 4169-007 Porto Portugal
“For all Lecture Notes in Earth Sciences published till now please see final pages of the book” ISBN: 978-3-540-78937-6
e-ISBN: 978-3-540-78938-3
Lecture Notes in Earth Sciences ISSN: 0930-0317 Library of Congress Control Number: 2008930228 c 2008 Springer-Verlag Berlin Heidelberg This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable for prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Cover design: WMXDesign GmbH Printed on acid-free paper 987654321 springer.com
Preface
The enormous progress over the last decades in our understanding of the mechanisms behind the complex system “Earth” is to a large extent based on the availability of enlarged data sets and sophisticated methods for their analysis. Univariate as well as multivariate time series are a particular class of such data which are of special importance for studying the dynamical processes in complex systems. Time series analysis theory and applications in geo- and astrophysics have always been mutually stimulating, starting with classical (linear) problems like the proper estimation of power spectra, which has been put forward by Udny Yule (studying the features of sunspot activity) and, later, by John Tukey. In the second half of the 20th century, more and more evidence has been accumulated that most processes in nature are intrinsically non-linear and thus cannot be sufficiently studied by linear statistical methods. With mathematical developments in the fields of dynamic system’s theory, exemplified by Edward Lorenz’s pioneering work, and fractal theory, starting with the early fractal concepts inferred by Harold Edwin Hurst from the analysis of geophysical time series, nonlinear methods became available for time series analysis as well. Over the last decades, these methods have attracted an increasing interest in various branches of the earth sciences. T
