Complex Systems Methods Characterizing Nonlinear Processes in the Near-Earth Electromagnetic Environment: Recent Advances and Open Challenges

被引:0
作者
Georgios Balasis
Michael A. Balikhin
Sandra C. Chapman
Giuseppe Consolini
Ioannis A. Daglis
Reik V. Donner
Jürgen Kurths
Milan Paluš
Jakob Runge
Bruce T. Tsurutani
Dimitris Vassiliadis
Simon Wing
Jesper W. Gjerloev
Jay Johnson
Massimo Materassi
Tommaso Alberti
Constantinos Papadimitriou
Pouya Manshour
Adamantia Zoe Boutsi
Mirko Stumpo
机构
[1] National Observatory of Athens,Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing
[2] University of Sheffield,Department of Automatic Control and Systems Engineering
[3] University of Warwick,Centre for Fusion, Space and Astrophysics, Physics Department
[4] University of Tromso,Department of Mathematics and Statistics
[5] International Space Science Institute,Department of Physics
[6] Istituto Nazionale di Astrofisica,German Aerospace Center (DLR)
[7] Istituto di Astrofisica e Planetologia Spaziali,Applied Physics Laboratory
[8] National and Kapodistrian University of Athens,Department of Engineering
[9] Hellenic Space Center,Dip. Fisica
[10] Magdeburg–Stendal University of Applied Sciences,undefined
[11] Potsdam Institute for Climate Impact Research (PIK) – Member of the Leibniz Association,undefined
[12] Humboldt University,undefined
[13] Institute of Computer Science of the Czech Academy of Sciences,undefined
[14] Institute for Data Science,undefined
[15] Technische Universität,undefined
[16] Jet Propulsion Laboratory California Institute of Technology,undefined
[17] NOAA/NESDIS,undefined
[18] The Johns Hopkins University,undefined
[19] Andrews University,undefined
[20] Istituto dei Sistemi Complessi,undefined
[21] Istituto Nazionale di Geofisica e Vulcanologia,undefined
[22] Università degli Studi di Roma Tor Vergata,undefined
来源
Space Science Reviews | 2023年 / 219卷
关键词
Solar wind – magnetosphere – ionosphere coupling; Magnetic storms; Magnetospheric substorms; Space weather; Nonlinear dynamics; Complex systems;
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摘要
Learning from successful applications of methods originating in statistical mechanics, complex 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 normal 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.
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