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Summary: Investigating magnetospheric dynamics using various
complexity measures
Georgios Balasis
, Ioannis A. Daglis
, Anastasios Anastasiadis
and Konstantinos
Eftaxias
Institute for Space Applications and Remote Sensing, National Observatory of Athens, Greece
Section of Solid State Physics, Department of Physics, University of Athens, Greece
Abstract. Dynamical complexity detection for output time series of complex systems is one of the foremost problems
in physics, biology, engineering, and economic sciences. Especially in magnetospheric physics, accurate detection of the
dissimilarity of complexity between normal and abnormal states (e.g. pre-storm activity and magnetic storms) can vastly
improve space weather diagnosis and, consequently, the mitigation of space weather hazards. A variety of complexity
measures based on linear and nonlinear analysis techniques (i.e., wavelet transforms and entropies, respectively) is applied to
the Dst index time variations in order to detect changes that can play the role of warnings for future magnetic storm occurrence.
INTRODUCTION
Accumulated evidence points to the complex character of
magnetosphere dynamics. For instance, Baker et al. [1],
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