Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/16549
Authors: Balasis, Georgios* 
Balikhin, Michael* 
Chapman, Sandra* 
Consolini, Giuseppe* 
Daglis, Ioannis A* 
Donner, Reik* 
Kurths, Jürgen* 
Paluš, Milan* 
Runge, Jakob* 
Tsurutani, Bruce* 
Vassiliadis, Dimitris* 
Wing, Simon* 
Gjerloev, Jesper* 
Johnson, Jay* 
Materassi, Massimo* 
Alberti, Tommaso* 
Papadimitriou, Constantinos* 
Manshour, Pouya* 
Boutsi, Adamantia-Zoe* 
Stumpo, Mirko* 
Title: Complex Systems Methods Characterizing Nonlinear Processes in the Near-Earth Electromagnetic Environment: Recent Advances and Open Challenges
Journal: Space Science Reviews 
Series/Report no.: /219 (2023)
Publisher: Springer
Issue Date: 2023
DOI: 10.1007/s11214-023-00979-7
Abstract: Learning from successful applications of methods originating in statistical mechanics, com- plex systems science, or information theory in one scientific field (e.g., atmospheric physics or climatology) can provide important insights or conceptual ideas for other areas (e.g., space sciences) or even stimulate new research questions and approaches. For instance, quantification and attribution of dynamical complexity in output time series of nonlinear dynamical systems is a key challenge across scientific disciplines. Especially in the field of space physics, an early and accurate detection of characteristic dissimilarity between nor- mal and abnormal states (e.g., pre-storm activity vs. magnetic storms) has the potential to vastly improve space weather diagnosis and, consequently, the mitigation of space weather hazards. This review provides a systematic overview on existing nonlinear dynamical systems- based methodologies along with key results of their previous applications in a space physics context, which particularly illustrates how complementary modern complex systems ap- proaches have recently shaped our understanding of nonlinear magnetospheric variability. The rising number of corresponding studies demonstrates that the multiplicity of nonlin- ear time series analysis methods developed during the last decades offers great potentials for uncovering relevant yet complex processes interlinking different geospace subsystems, variables and spatiotemporal scales.
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