Long-lead prediction of Indian summer monsoon rainfall from global SST evolution

Abstract. A methodology is presented for making optimum use of the global sea surface temperature (SST) field for long lead prediction of the Indian summer monsoon rainfall (ISMR). To avoid the node phase of the biennial oscillation of El Niño Southern Oscillation (ENSO)-monsoon system and also to include the multiyear ENSO variability, the ISMR-SST relationship was examined from three seasons lag prior to the start of the monsoon season up to four years lag. First, a correlation analysis is used to identify the regions and seasonal lags for which SST is highly correlated with ISMR. The correlation patterns show a slow and consistent temporal evolution, suggesting the existence of SST oscillations that produce significant correlation even when no direct physical relationship between SST and ISMR, at such long lags, is plausible. As a second step, a strategy for selecting the best 14 predictors (hot spots of the global oceans) is investigated. An experimental prediction of ISMR is made using the SST anomalies in these 14 hot spots. The prediction is consistent for the 105 years (1875 to 1979) of the model development and the 22 years (1980 to 2001) of the model verification period (these last years were not included in the correlation analysis or in the computation of the regression model). The predicted values explain about 80% of the observed variance of ISMR in the model verification period. It is shown that, to a large extent, the behavior of the ensuing ISMR can be determined nine months in advance using SST only. The consistent and skillful prediction for more than a century is not a product of chance. Thus the anomalously strong and weak monsoon seasons are parts of longer period and broader scale circulation patterns, which result from interactions in the ocean–atmosphere coupled system over many seasons in the past. It is argued that despite the weakening of the ENSO-ISMR relationship in recent years, most of the variability of ISMR can still be attributed to SST in a global perspective.

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