Analysis of wet and dry periods by Markov Chain Model in southern of Caspian sea

This paper is about to analyze the dry and wet periods of spring and summer that are the agricultural and tourist seasons for this region. In order to approach to this goal, we used daily precipitation statistics data of the meteorology office of Rasht for a period of 11 years from 1997 to 2007 inclusive. We analyzed these data using Two State First-order Markov Chain Model and we also have determined the relating short term features of wet and dry periods like simple and ecological probabilities, Duration of wet and dry periods, mathematical expectations, and meteorological cycles. Analyzing the daily precipitation clarified the condition of spring and summer seasons from the viewpoint of wet and dry periods. The results expressed that the number of dry days were more than the number of wet days in summer. Also the probability of the occurrence of two successive dry days is more than the other probabilities both in spring and summer. The results also showed that no conspicuous difference between simple and ecological probabilities in our station of study is noted. The maximum of mathematical expectation and meteorological cycle of dry periods in summers was more than that for spring and wet periods which shows that the dry periods expected for summer is more than that for spring and wet periods. The results of this research can be used for local planning and proper local anticipations.