Abstract

Rainfall variability at interannual and longer time scales is a crucial area of study with many practical implications for the way we manage our water resources. This variability, which is often linked to both internally and externally forced fluctuations in the global Sea surface Temperature (SST) field can often affect the weather patterns of entire continents via a group of large-scale pressure and circulation anomalies referred to as teleconnections that transmit these anomalies across large distances. The El Niño (warm phase) and La Niña (cold phase) are two opposite phases of the ENSO cycle. The annual and seasonal increasing or decreasing trend of precipitation in the southern states of peninsular India have teleconnections with ENSO warm (El Niño) and cool (La Niña) phases and has been the considered as the significant area of this study. The anomaly rainfall patterns of the 4 seasons namely Summer, Monsoon, Post Monsoon and Winter over the Southern States of India during the 30-year period (1991-2020) corresponding to the El Niño-Southern Oscillation have been studied. Spatially coherent increasing and decreasing trends in seasonal and annual rainfall are found in the southern states of India and the ENSO–Indian Rainfall has been found to have an inverse relationship. During the study period, 9 drought years were observed in southern parts of India, among which three were in non-El Niño years, and specifically the year of 2012 and 2017 were reported to be La Nina years. Likewise, 12 heavy rainfall years were received in the southern states of India, out of which four were in non-La Nina years, and of these 3 years namely 1997, 2015 and 2019 were actually in El Niño years including the well-known Chennai (Tamil Nadu) Floods (2015). The ENSO–Indian Rainfall relationship stands contrary to popular beliefs, stating not all La Niña years does guarantee better-than-normal rains and similarly an El Niño year does not always translate into below-normal rains. Overall, the findings provide a better understanding of the rainfall variability in the southern states of our country, and this information is of potential use for mitigating and managing disaster risks.