Abstract

The summer monsoon onset over Kerala (MOK) marks the beginning of the rainy season for the country. Associated with the MOK, significant transitions of large scale atmospheric and oceanic circulation patterns are observed over the Asia-Pacific region. In this study, a new method for the objective identification of MOK, based on large scale circulation features and rainfall over Kerala, is discussed. Further, a set of empirical models based on the principal component regression (PCR) technique was developed for the prediction of the date of MOK by keeping in mind the IMD’s operational forecasting service requirements. Predictors for the models were derived using correlation analysis from the thermal, convective and circulation patterns. Only five predictors pertaining to the second half of April were used in the first model (Model-1) so that the prediction of MOK can be prepared by the end of April itself. The second model (Model-2) used four additional predictors pertaining up to the first half of May along with two predictors used in the Model-1 for update prediction at the end of the first half of May. To develop each of the PCR models, Principal Components Analysis (PCA) of the respective predictor data was carried out followed by regression analysis of first two principal components (PCs) with the date of MOK. Both these models showed good skill in predicting the date of MOK during the independent test period of 1997–2007. The root mean square error (RMSE) of the predictions from both the models during the independent test period was about four days which was nearly half the RMSE of the predictions based on climatology.

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