Network percolation provides early warnings of abrupt changes in coupled oscillatory systems: An explanatory analysis

Abstract

Functional networks are powerful tools to study statistical interdependency structures in spatially extended or multivariable systems. They have been used to get insights into the dynamics of complex systems in various areas of science. In particular, percolation properties of correlation networks have been employed to identify early warning signals of critical transitions. In this work, we further investigate the corresponding potential of percolation measures for the anticipation of different types of sudden shifts in the state of coupled irregularly oscillating systems. As a paradigmatic model system, we study the dynamics of a ring of diffusively coupled noisy FitzHugh-Nagumo oscillators and show that, when the oscillators are nearly completely synchronized, the percolation-based precursors successfully provide very early warnings of the rapid switches between the two states of the system. We clarify the mechanisms behind the percolation transition by separating global trends given by the mean-field behavior from the synchronization of individual stochastic fluctuations. We then apply the same methodology to real-world data of sea surface temperature anomalies during different phases of the El Niño-Southern Oscillation. This leads to a better understanding of the factors that make percolation precursors effective as early warning indicators of incipient El Niño and La Niña events.

References in corpus (19)

• Temporal Networks
• Tipping points in open systems: bifurcation, noise-induced and rate-dependent examples in the climate system
• Complex networks in climate dynamics - Comparing linear and nonlinear network construction methods
• A mathematical framework for critical transitions: bifurcations, fast-slow systems and stochastic dynamics
• Statistical physics approaches to the complex Earth system
• Dynamics of Elastic Excitable Media
• FitzHugh-Nagumo oscillators on complex networks mimic epileptic-seizure-related synchronization phenomena
• Small-world structure of earthquake network
• A mathematical framework for critical transitions: normal forms, variance and applications
• Disentangling different types of El Niño episodes by evolving climate network analysis
• Using Network Theory and Machine Learning to predict El Niño
• Percolation framework to describe El Niño conditions
• Climate network percolation reveals the expansion and weakening of the tropical component under global warming
• Assessing the direction of climate interactions by means of complex networks and information theoretic tools
• A climate network-based index to discriminate different types of El Niño and La Niña
• Percolation-based precursors of transitions in extended systems
• Precursors of the El Niño Phenomenon: A climate network analysis
• Optimal Control in Pandemics
• Analysis and Predictability for Tipping Points with Leading-Order Nonlinear Terms