Climatic conditions influence the culture and economy of societies and the performance of economies. Specifically, El Niño 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 Niño and La Niña. We find that regions that are characterized by higher positive/negative network "in"-weighted links are exhibiting stronger correlations with the El Niño basin and are warmer/cooler during El Niño/La Niña periods. In contrast to non-El Niño periods, these stronger inweighted 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 Niño (La Niña) event to another; still, some El Niño (La Niña) 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 Niño/La Niña events and also may be applied in the investigation of other climate variables.climate | dynamic network | ENSO M ore than a decade ago, networks became the standard framework for studying complex systems (1-5). In recent years, network theory has been implemented in climate sciences to construct "climate networks." These networks have been used successfully to analyze, model, understand, and even predict climate phenomena (6-16). Specific examples of climate network studies include the investigation of the interaction structure of coupled climate subnetworks (17), the multiscale dependence within and among climate variables (18), the temporal evolution and teleconnections of the North Atlantic Oscillation (19,20), the finding of the dominant imprint of Rossby waves (21), the optimal paths of teleconnection (22), the influence of El Niño on remote regions (8,23,24), the distinction of different types of El Niño events (25), and the prediction of these events (15,16). A network is composed of nodes and links; in a climate network, the nodes are the geographical locations, and the links are the correlations between them. The "strength" of the links is quantified according to the strength of the correlations between the different nodes (21,26,27).El Niño is probably the strongest climate phenomenon that occurs on interannual time scales (28,29). El Niño refers to the warming of the central and eastern equatorial Pacific Ocean by several degrees ( • C). La Niña is the cooling of sea surface temperatures (SSTs) in the eastern tropical Pacific Ocean. La Niña usually follows an El Niño event, but not always; the overall phenomenon is referred to as El Niño-Southern Oscillation (ENSO). This cycle occurs every 3-5 y with different magnitudes. There are several indices that quantify the El Niño activity, including the Niño 3.4 Index, the Southern Oscillation Index (SOI) (see, e.g., ref. 30), and the Oceanic Niño ...