%0 Journal Article %T Statistical Analysis and Prediction of Short-term Stormy Periods of Sabzevar by Markov Chain Model %J Geographical Space %V 15 %N 50 %U http://geographical-space.iau-ahar.ac.ir/article-1-1897-en.html %R %D 2015 %K Sabzevar, Markov Chain Model, Short-term Stormy Periods., %X About 90 percent of the world's natural disasters occur in relationship between climate factors and among them, the storm accounts for about 30% shares of this disaster. Thus, given the importance of this issue, in this paper two-state Markov chain was used to analyze and forecast of stormy days in Sabzevar city. For this purpose, the daily wind in Sabzevar station during the period (1390-1350) was obtained. The days of storm (code 1) and non- storm (code 0) were divided into two groups. The results of data processing show that the maximum frequency of stormy days 79 days occurred in 1385. During the study period, April with 113 days of stormy, had the highest frequency, and on the contrary, November with 19 days of stormy, had the lowest frequency. In other words Spring was stormy and Autumn was calm season is in Sabzevar. Seasonal results of Markov probability matrix showed that the occurrence of two consecutive stormy days in all seasons is not more than 20%. The minimum (10%) and maximum (19%) probability occurred in autumn and Spring, respectively. However, the probability of two consecutive non- stormy days in all seasons is not less than 90 percent. Later determined the shortest air cycle with approximate duration of 16 days in Spring and also the largest with approximate duration of 45 days in Autumn have been observed. Also, throughout the investigated period, the one-day and two-day stormy sequences had the highest frequency. %> http://geographical-space.iau-ahar.ac.ir/article-1-1897-en.pdf %P 233-250 %& 233 %! %9 Research %L A-10-567-4 %+ %G eng %@ 1735322X %[ 2015