A Climate Network Based Stability Index for El Ni\~no Variability

TL;DR

This paper introduces a novel climate network-based stability index that improves El Niño variability prediction by monitoring spatial correlations in sea surface temperature data, addressing limitations of traditional indices.

Contribution

A new stability index based on complex network theory is proposed, enabling more effective monitoring of Pacific climate stability using only sea surface temperature data.

Findings

The index effectively tracks changes in Pacific climate stability.

It can be evaluated with limited data, overcoming previous data constraints.

The method shows promise for improving El Niño prediction accuracy.

Abstract

Most of the existing prediction methods gave a false alarm regarding the El Ni\~no event in 2014. A crucial aspect is currently limiting the success of such predictions, i.e. the stability of the slowly varying Pacific climate. This property determines whether sea surface temperature perturbations will be amplified by coupled ocean-atmosphere feedbacks or not. The so-called Bjerknes stability index has been developed for this purpose, but its evaluation is severely constrained by data availability. Here we present a new promising background stability index based on complex network theory. This index efficiently monitors the changes in spatial correlations in the Pacific climate and can be evaluated by using only sea surface temperature data.