Revisiting ENSO – IOD Teleconnections With the Indian Summer Monsoon: Information Content and Spatial Organization of Seasonal Rainfall

ABSTRACT Understanding the teleconnections between large‐scale climate modes and the spatial organization of Indian summer monsoon rainfall (ISMR) remains an important scientific problem. This study revisits the relationship between ISMR and sea surface temperature (SST) variability associated with the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). Seasonal rainfall anomalies are categorized into deficit, normal and excess classes and their uncertainty is quantified using Shannon entropy. The reduction in uncertainty conditioned on ENSO and the IOD states is assessed using mutual information. Results show that knowledge of ENSO and the IOD reduces rainfall entropy by less than 10% over most regions, indicating a modest association of spatial rainfall anomalies with dominant SST variability. To examine the spatial organization of extremes, rainfall anomaly clusters are identified using connected‐component analysis. El Niño events preferentially produce large dry clusters, whereas La Niña events favour large wet clusters across the monsoon region. However, event‐to‐event variability in the locations of dominant anomaly clusters indicates that ENSO and the IOD primarily influence the probability of anomalies rather than imposing fixed spatial patterns. Comparisons between rainfall anomaly structures and SST patterns further suggest that a substantial fraction of ISMR spatial variability may be associated with other climate modes, internal atmospheric variability and regional‐scale processes not directly linked to SST forcing. Consistent with this interpretation, similarities among rainfall patterns are only weakly related to similarities in SST patterns. These findings indicate that ENSO and the IOD explain only a limited fraction of the spatial organization of ISMR anomalies, suggesting that additional sources of variability beyond these SST modes contribute to the observed rainfall patterns.