Stochastic dynamic model for long range prediction of monsoon rainfall in Peninsular India


  • V. THAPLIYAL India Meteorological Department, Pune, India



An attempt has been made to develop a Stochastic dynamic model that could be used for forecasting monsoon rainfall, June to September, in the larger sub-division of India, viz., Peninsula. For building such a model the atmosphere bas been considered as a linear dynamic system that converts various inputs into the output, say the rainfall. In this study the 500 mb mean April sub-tropical ridge position along Long. 75° E has been used as input to the atmosphere. The input~ output data for the recent 38 years (1939-1976) have been utilised for developing the model which utilises the dynamics of the atmosphere and also that of the ARIMA process to forecast the rainfall.


The performance of the model has been found good during the sample and the test (1977 to 1980) periods. Even in rank drought and excess rainfall years the closeness of the predicted and realised values stands out well. In terms of seven categories currently being used by the India Meteorological Department for describing its long range forecasts, the skill score of the model forecast for the test period has been found equal to one which is the highest that a forecast formula can have. This suggests that the Stochastic Dynamic Model developed here can therefore, be used for issuing more accurate long range monsoon rainfall forecasts about a month ahead of the season for the Peninsula. This would provide enough time for planning adequate strategies for mitigating the disastrous effects that are produced due to the large vagaries of monsoon.




How to Cite

V. THAPLIYAL, “Stochastic dynamic model for long range prediction of monsoon rainfall in Peninsular India”, MAUSAM, vol. 33, no. 4, pp. 399–404, Oct. 1982.



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