Indian Ocean SST and Indian Summer Rainfall: Predictive Relationships and Their Decadal Variability

Abstract

The authors examine relationships between Indian Ocean sea surface temperature (SST) variability and the variability of the Indian monsoon, including analysis of potential long-lead predictions of Indian rainfall by regional SST and the influence of ENSO and decadal variability on the stability of the relationships. Using monthly gridded (4° × 4°) SST data from the Global Sea-Ice and Sea Surface Temperature (GISST) dataset that spans 1945–94, the correlation fields between the All-India Rainfall Index (AIRI) and SST fields over the tropical Indian Ocean are calculated. In the boreal fall and winter preceding the summer Indian monsoon, SST throughout the tropical Indian Ocean correlates positively with subsequent monsoon rainfall. Negative correlation occurs between SST and the AIRI in the subsequent autumn in the northern Indian Ocean only. A strong correlation (0.53) is found between the summer AIRI and the preceding December–February Arabian Sea SST. The correlation between the AIRI and the SST to the northwest of Australia for the same period is 0.58. The highest correlation (0.87) for the years following 1977 is found between the AIRI and the central Indian Ocean SST in the preceding September–November, but this relationship is much weaker in earlier years. Based upon these correlations, the authors define Arabian Sea (AS1), northwest Australia (NWA1), and central Indian Ocean (CIO1) SST indexes. The relationships of these indexes to the AIRI and ENSO are examined. The authors find that the high correlation of the AS1 and NWA1 SST indexes with the Indian summer rainfall is largely unaffected by the removal of the ENSO signal, whereas the correlation of the CIO1 index with the AIRI is reduced. The authors examine the interdecadal variability of the relationships between SST and the AIRI and show that the Indian Ocean has undergone significant secular variation associated with a climate shift in 1976. The possible mechanisms underlying the correlation patterns and the implications of the relationship to the biennial nature of the monsoon and predictability are discussed.