Revisiting the predictors for the long‐range forecasting of southwest monsoon rainfall over South Asia with a focus on Pakistan

Abstract

The predictors of the south Asian summer monsoon used in statistical long‐range forecasting by the Indian and Pakistan Meteorological Departments have, in recent decades, had their validity reassessed. The results of such studies, including this one, show that the relationships between numerous predictors and the monsoon rainfall have changed over time, and many predictors have lost or gained significance. Tropical Atlantic sea surface temperature (SST) has been identified as a robust new predictor, having been found to exhibit a significant correlation with monsoon rainfall in northern Pakistan as well as with Indian summer monsoon rainfall. Empirical orthogonal function (EOF) analysis is performed on the Pakistan monsoon rainfall data in order to identify the dominant coupled modes of variability, on interannual timescales, for the classification of two sub‐regions of Pakistan. Overall, few predictors showed significant correlations with the monsoon rainfall across Pakistan. However, with respect to rainfall over northern Pakistan, significant correlations were found for the tropical Atlantic SST anomaly, equatorial southeast Indian Ocean SST anomaly and quasi‐biennial oscillation anomaly. With respect to rainfall over southern Pakistan, warm water volume anomaly, North Asia sea level pressure tendency and Nino3.4 SST tendency showed significant correlations. Although the predictability of Pakistan summer monsoon rainfall is low, a simple multiple linear regression model has nevertheless been developed for its prediction. The model has shown good predictive skill for the primary monsoon region of Pakistan