عنوان مقاله [English]
The air temperature trend has been increasing during recent decades, especially in the regions such as Iran which is located in dry and semi-dry world belt. In this research we used Markov chain to obtain probabilities of heat waves with different continues in Kerman province using 20 years daily maximum air temperature data during 1986-2005. We analyzed daily maximum air temperature data of 5 synoptic stations that had at least 20 years daily data. To obtain a statistical index for determination of heat wave events in every station, the days in which the maximum temperature exceeds from this index were defined as heat weave event. After determining heat events, we classified the heat waves to short and long heat waves events and the statistical trends of these events were calculated separately. Finally, the return period and continuation period of these events were determined and analyzed using Markov chain. Maximum temperature trend analysis in the Province Kerman indicated that most heat waves occurred in April and May, that this change has been an increasing trend during the period have been statistically, especially in 2000 reached its maximum height and then again the previous trend is growing. Finally, we estimated the probabilities of occurrence of 1 to 9-day heat waves in all studied stations.