资源环境科技发展态势分析平台

Climatic conditions influence the culture and economy of societies and the performance of economies. Specifically, El Nino as an extreme climate event is known to have notable effects on health, agriculture, industry, and conflict. Here, 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 that are characterized by higher positive/negative network "in"-weighted links are exhibiting stronger correlations with the El Nino basin and are warmer/cooler during El Nino/La Nina periods. In contrast to non-El Nino periods, these stronger in-weighted activities are found to be concentrated in very localized areas, 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/La Nina events and also may be applied in the investigation of other climate variables.