  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.
