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

Abstract

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.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 approaches have recently shaped our understanding of nonlinear magnetospheric variability. The rising number of corresponding studies demonstrates that the multiplicity of nonlinear 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.

Persistent Behavior in Solar Energetic Particle Time Series

“…where the exponent H is called (Varotsos et al 2002;Weron 2002;Balasis et al 2023) the Hurst exponent. As already mentioned, when H = 0.5, the time series is a white noise, while when H > 0.5, the time series is persistent, i.e., increments are more likely to be followed by increments and decrements by decrements (for a systematic study of persistence in geophysical time series, see also Witt & Malamud 2013).…”

“…In the field time-series analysis, a signature of complexity is persistence (Salcedo-Sanz et al 2022), i.e., the tendency of increases to be followed by increases and vice versa. Hence, the purpose of the present study is to examine the persistence in SEP events, which is a property that may characterize complexity and distinguish these events from others or solar quiet times (i.e., Balasis et al 2023;Malandraki et al 2023). Wanliss & Dobias (2007) have previously suggested that geomagnetic storms should be considered as phase transitions-however, not an equilibrium transition, like the freezing observed when the temperature falls below the melting point of a substance, but a dynamic phase transition, where time is the control parameter instead of temperature.…”

Analysis of Controllability in Cyber–Physical Power Systems under a Novel Load-Capacity Model

“…However, they overlook the information exchange between nodes. Entropy [30], which reflects the degree of disorder in a system, is a concept in physics. A higher entropy value indicates a more disordered system, while a lower entropy value indicates a more ordered system.…”

Dynamical Complexity Transitions During High‐Intensity Long Duration Continuous Auroral Activities (HILDCAA) Events: Feature Analysis Based on Neural Network Entropy

“…Interestingly, the underlying physical processes of the AE signatures as HILDCAA emerges are connected with long‐duration of large amplitude Alfvénic fluctuations, which possess some inherent irregularities in its underlying dynamics. Its influence on the internal dynamics of the magnetosphere would lead to chaotic variation due to the inherent irregularities driven by magnetic reconnections and viscous interactions (Alberti et al., 2020, 2022; Balasis et al., 2009, 2023; Consolini, 2018; Donner et al., 2019; Manshour et al., 2021; Mendes et al., 2017; Ogunsua, 2018; Oludehinwa, Olusola, Bolaji, & Odeyemi, 2021; Oludehinwa, Olusola, Bolaji, Odeyemi, & Njah, 2021; Pavlos, 1994; Pavlos et al., 1992, 1999; Toledo et al., 2021). It is well established that the Earth's magnetosphere is driven by the solar wind and exhibits complex dynamical features especially during severe space weather conditions.…”