An oceanic model for the prediction of southwest monsoon rainfall over India
DOI:
https://doi.org/10.54302/mausam.v47i1.3694Keywords:
Southwest Monsoon, Long range forecasting, Principal component analysis (PCA), Correlation coefficient (CC), Multiple regressionAbstract
Nine new oceanic predictor for long range forecasting of Indian summer monsoon rainfall been identified utilizing the marine meteorological data of the North Indian Ocean and the monsoon rainfall data of the period 1961-91. In order to develop a reliable regression model the principal component analysis (PCA) of original variables has been done. Five parameters having maximum influence on first principal component, which is having highest correlation with the monsoon rainfall are : wind power in the atmospheric boundary layer over the north Indian Ocean between Equator and 100 N, mean evaporation over the Arabian Sea (00 -150 N) mean sea surface temperature (SST) gradient over the Arabian Sea between 7.50 – 17.50 N, mean evaporation over Bay of Bengal between Equator and 100 N and mean sea level pressure (SLP) over the Arabian Sea, each pertaining to the month of May. A multiple regression model for all Indian rainfall of southwest monsoon season has been developed using the principal components which have got good cor-relations with the monsoon rainfall. The model was tested for all the years from 1987 to 1991 and it has been found that the predicted values of all India summer monsoon rainfall of all the years except 1989 were very close to the actual values. However, there was a substantial difference between the predicted and actual rainfall of 1989 summer monsoon.
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