Estimating the Occurrence Probability of Heat Wave Periods Using the Markov Chain Model

Regarding the climate changes, global warming, recent drought, forecasting the maximum temperature and hot weather waves has been considered as one of the most important climatic parameters which affects the ecosystems and provides a proper opportunity for the planners to prepare necessary arrangements. Studying and analyzing the maximum temperature is of great importance in managing the water and natural resources, agricultural products, spreading pests and diseases, melting the snow and flood, Evaporation and transpiration, drought and etc. In the present paper, the daily maximum temperature of ten weather stations in northern and southern hillside of Alborz which are geographically corresponded have been collected during 1980 to 2010 in order to determine the hot weather waves in these two hillside and also compare them with each other in April to September, furthermore, a heat index was specified for each month according to the above mentioned data, and the maximum temperatures which were more than the defined index were determined as the heat wave and these waves were categorized into two classes of short term and long term and then the related diagram were drawn and finally using the Markov Chain Model, the transition probability matrix and the reliability probability has been computed with multiple power. The duration period and the return of 1 to ten days for each month and in each weather forecast station was analyzed and studied and then the corresponding stations were compared and the process of temperature changes was discussed. The maximum short term term heat wave in the northern hillside belong terms to Gorgan, the long term heat wave belong terms to Qaem shahr and in the southern hillside, it belong terms to Semnan. The probability of the days, without the heat waves, after which a heat wave occurs, varies between 2% in Ramsar to 4% in Gorgan in the station located in the northern hillside; while in the stations located in the southern hillside, this amount varies between 4 to 5% (except Semnan, 80%). The results show that the frequency of 1 to 3 days is more than others in all the stations and also in all the seasons and the frequency of 1 to 5 days in the station of southern hillside are more obvious. In the ten days of return, Semnan shows a significant difference compared with other stations.