Evaluation of Frost Days Continuity Using Markov Chain Model: Case Study of Zabol city in Iran

Extreme temperature events can impose serious impacts on environment and societies. Since the outbreak of cold and frost are one of the important factors of climate in many parts of Iran, utilization of a new model for predicting the continuity of these factors is necessary.
This paper uses high-order categorical non-stationary Markov chains to study the occurrence of extreme cold temperature events by transition and probabilities matrixes in Zabol, southeast of Iran. The occurrence of frost days, homogeneity, continuity and spatial duration were analyzed for 30 years (April 1982- April 2012). The multivariate regression was used to modeling and mapping the statistical characteristics of frost and Kriging interpolation method in Arc/GIS was applied for its relationship.
The occurrence of frost days in Zabol was in conformity with Markov model characteristic that showed the continuation of frost days depended on the weather of preceding days.
Discussion and Heavy frost in Zabol is expected to occur in Jan and Feb. Thus, frost-free day cycle duration was more than frost cycle and occurrences of frost in short term were more than long term in the studied period.