Analyzing Rainfall Condition of Bangladesh: An Application of Markov Chain

  • Janardan Mahanta Department of Statistics, University of Chittagong, Chittagong 4331, Bangladesh.
  • Srabani Dey BGC Trust University Bangladesh, Chittagong, Bangladesh.
  • Parves Khosro Department of Statistics, University of Chittagong, Chittagong 4331, Bangladesh.
Keywords: Markov chain, rainfall

Abstract

This paper aims to study the long term changes of rainfall at two stations in Bangladesh by using Markov Chain Model. For this study daily rainfall data were collected from Bangladesh Meteorological Department (BMD). Stationary distribution test has been employed and to test whether the daily rainfall occurrences are stationary or not. After 10 days and 8 days, stationary probabilities have been observed for Dhaka and Chittagong station, respectively. By analyzing limiting behavior of current day’s rainfall, it also has been observed that in Dhaka station 56% status of the day will be rainy and the rest of the condition will be sunny in May to October, whereas in Chittagong it is 58%. Lastly, using Cramer’s gif.latex?V^{2}  and the test of several correlations coefficient, it has found that the association among the daily rainfall occurrences decreases when order of the Markov chain increases.

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Published
2018-07-19
Section
Articles