Investigation of Probability of Occurrence and Persistence of Rainy Days by Using Markov Chain Model (Case Study: Lamerd City)

In the present study, using available records of daily rainfall of 22 years (1995-2016) of the Lamerd (Fars Province) weather station, frequencies and durations of rainy days were studied by using the Markov chain model. In this study, the months of May to October were disregarded due to the insignificant number of daily precipitations. The daily rainfall data were arranged based on the transition matrix of occurrence of dry and wet days, while the transition matrix was calculated based on the maximum likelihood method. In all studies done in Iran, in order to forecast precipitation by using the Markov chain, only the first order of the Markov chain was used which may not be in good agreement with data and resulted to incorrect results. But in this study, by using an accurate statistical method, the appropriate order of the Markov chain was diagnosed to be used. Matrices of stationary probability and the return periods of rainy days for 2 to 5-day precipitations were determined for the studied months in this research. The results showed that the probability of precipitation per day is 0.126, and the probability of absence of precipitation is 0.874.