Detection of Dynamical Complexity Changes in Dst Time Series Using Entropy Concepts and Rescaled Range Analysis

  • Georgios Balasis
  • Ioannis A. Daglis
  • Anastasios Anastasiadis
  • Konstantinos Eftaxias
Chapter
First Online:
Part of the IAGA Special Sopron Book Series book series (IAGA, volume 3)

Abstract

Using an array of diagnostic tools including entropy concepts and rescaled range analysis, we establish that the Dst index time series exhibits long-range correlations, and that the underlying stochastic process can be modeled as fractional Brownian motion. We show the emergence of two distinct patterns in the geomagnetic variability of the terrestrial magnetosphere: (1) a pattern associated with intense magnetic storms, which is characterized by a higher degree of organization (i.e., lower complexity or higher predictability for the system) and persistent behavior, and (2) a pattern associated with normal periods, which is characterized by a lower degree of organization (i.e., higher complexity or lower predictability for the system) and anti-persistent behavior.

Keywords

Magnetic Storm Shannon Entropy Fractional Brownian Motion Hurst Exponent Entropy Measure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgements

The Dst data are provided by the World Data Center for Geomagnetism, Kyoto (http://swdcwww.kugi.kyoto-u.ac.jp/).

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Georgios Balasis
    • 1
  • Ioannis A. Daglis
    • 1
  • Anastasios Anastasiadis
    • 1
  • Konstantinos Eftaxias
    • 2
  1. 1.Institute for Space Applications and Remote Sensing, National Observatory of AthensAthensGreece
  2. 2.Section of Solid State Physics, Department of PhysicsUniversity of AthensAthensGreece

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