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arXiv · 1310.5494

Disentangling different types of El Niño episodes by evolving climate network analysis

Alexander Radebach·Reik V. Donner·Jakob Runge·Jonathan F. Donges·Jürgen Kurths
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Abstract

Complex network theory provides a powerful toolbox for studying the structure of statistical interrelationships between multiple time series in various scientific disciplines. In this work, we apply the recently proposed climate network approach for characterizing the evolving correlation structure of the Earth's climate system based on reanalysis data of surface air temperatures. We provide a detailed study on the temporal variability of several global climate network characteristics. Based on a simple conceptual view on red climate networks (i.e., networks with a comparably low number of edges), we give a thorough interpretation of our evolving climate network characteristics, which allows a functional discrimination between recently recognized different types of El Niño episodes. Our analysis provides deep insights into the Earth's climate system, particularly its global response to strong volcanic eruptions and large-scale impacts of different phases of the El Niño Southern Oscillation (ENSO).

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Alexander Radebach, Reik V. Donner, Jakob Runge, Jonathan F. Donges, Jürgen Kurths. 2013-10-21. Disentangling different types of El Niño episodes by evolving climate network analysis. https://doi.org/10.1103/physreve.88.052807

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