Multiple Regression Model for Long Range Forecasting of South-West Monsoon Rainfall for Pune, Maharashtra

Abstract

The large spatial variability in monsoon rainfall over India demands for regional model to predict the seasonal rainfall. Hence, a local model was developed for predicting seasonal (June-September) rainfall of Pune using multiple regression technique. The monthly weather data of 36 years (1970-2005) was used for model development and data for next five years (2006-2010) were used for validation. The model explained 81% variability in seasonal rainfall with model error of 2.52%. During the validation period (2006-2010), the performance of model was quite satisfactory with model error of -1.94% only. This model was used to predict the rainfall for 2011 season. Results suggested that the rainfall during 2011 would be higher (51.2%) than the normal rainfall in Pune. Key words: Multiple regression, rainfall forecasting, rainfall analysis, statistical model.