Temporal organization of magnetospheric fluctuations unveiled by recurrence patterns in the Dst index

作     者：Donner, Reik V. Stolbova, Veronika Balasis, Georgios Donges, Jonathan F. Georgiou, Marina Potirakis, Stelios M. Kurths, Jürgen 

作者机构：Research Domain IV-Transdisciplinary Concepts and Methods Potsdam Germany Department of Physics Humboldt University Berlin Germany Department of Banking and Finance University of Zurich Switzerland Department of Control Theory Nizhny Novgorod State University Nizhny Novgorod Russia Institute for Astronomy Astrophysics Space Applications and Remote Sensing National Observatory of Athens Penteli Athens Greece Research Domain I-Earth System Analysis Potsdam Germany Stockholm Resilience Centre Stockholm University Stockholm Sweden Department of Physics Section of Astrophysics Astronomy and Mechanics National and Kapodistrian University of Athens Zografos Athens Greece Department of Space and Climate Physics University College London Dorking Surrey United Kingdom  Aigaleo Athens Greece Institute for Complex Systems and Mathematical Biology University of Aberdeen Aberdeen United Kingdom 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2018年

核心收录：

主　　题：Degrees of freedom (mechanics) 

摘      要：Magnetic storms constitute the most remarkable large-scale phenomena of nonlinear magnetospheric dynamics. Studying the dynamical organization of macroscopic variability in terms of geomagnetic activity index data by means of complexity measures provides a promising approach for identifying the underlying processes and associated time-scales. Here, we apply a suite of characteristics from recurrence quantification analysis (RQA) and recurrence network analysis (RNA) in order to unveil some key nonlinear features of the hourly Disturbance storm-time (Dst) index during periods with magnetic storms and such of normal variability. Our results demonstrate that recurrence-based measures can serve as excellent tracers for changes in the dynamical complexity along non-stationary records of geomagnetic activity. In particular, trapping time (characterizing the typical length of laminar phases in the observed dynamics) and recurrence network transitivity (associated with the number of the system s effective dynamical degrees of freedom) allow for a very good discrimination between magnetic storm and quiescence phases. In general, some RQA and RNA characteristics distinguish between storm and non-storm times equally well or even better than other previously considered nonlinear characteristics like Hurst exponent or symbolic dynamics based entropy concepts. Our results point to future potentials of recurrence characteristics for unveiling temporal changes in the dynamical complexity of the magnetosphere. Copyright © 2018, The Authors. All rights reserved.