On the Markov chain models for monsoonal rainfall occurrence in different zones of West Bengal

Abstract

The probability distribution of pattern of rainfall during the monsoon season (June-September) over different regions of West Bengal (India) has been analysed with the help of Markov chain models of various orders. The analysis is based on relevant data of 25 years (1971-1995) for ten meteorological stations spread over the state. The determination of the proper order that best describes the precipitation over the region is carried out using Akaike’s Information Criteria. The analysis clearly indicates that first order Markov chain model is the best one for rainfall forecasting. It is found that there is a period of occurrence of rainfall phenomenon (2-4 days) over the various stations. Moreover, the steady state probabilities and mean occurrence time of precipitation days and dry days have also been calculated for first and second order Markov chain models. The computation reveals that the observed and theoretical values of steady state probabilities are realistically matched.