Climate network suggests enhanced El Ni\~no global impacts in localized areas

TL;DR

This study constructs climate networks from surface air temperature data to identify localized regions with stronger El Nino and La Nina impacts, revealing variable and event-specific activity patterns that can enhance climate prediction.

Contribution

It introduces a novel network-based approach to analyze and quantify localized climate impacts of El Nino and La Nina events, improving understanding of their global effects.

Findings

Localized regions show stronger correlations during El Nino/La Nina periods.

The activity patterns vary between events, with some events being more similar.

Network community analysis quantifies event similarity.

Abstract

We construct directed and weighted climate networks based on near surface air temperature to investigate the global impacts of El Nino and La Nina. We find that regions which are characterized by higher positive or negative network in weighted links, are exhibiting stronger correlations with the El Nino basin and are warmer or cooler during El Nino or La Nina periods. These stronger in-weighted activities are found to be concentrated in localized areas, as compared to non-El Nino periods, whereas a large fraction of the globe is not influenced by the events. The regions of localized activity vary from one El Nino (La Nina) event to another; still some El Nino (La Nina) events are more similar to each other. We quantify this similarity using network community structure. The results and methodology reported here may be used to improve the understanding and prediction of El Nino or La Nina events and also may be applied in the investigation of other climate variables.