عنوان مقاله [English]
Some characters of time series probability distribution are described by shape and scale parameters. These parameters show skewness and kurtosis of probability distribution. Suitable fitting of probability distribution on climatic elements e.g. precipitation can estimate the related scale and shape parameters. In this paper based on daily data from 51 synoptic, climatologic, and rain gage stations in the Golestan province in the north of Iran, the suitable probability distribution have fitted and the shape and the scale parameters were estimated. In the next step the spatial distribution of these parameters were statistically-graphically analyzed. Results of this paper show that in the wet months (October to March) the probability distributions of precipitation are best described with the Gamma distribution. While in the dry months (April to September) the precipitation are fitted to Half Normal and Exponential distributions. Based on the common methods the shape and the scale parameters have been calculated. The positive skewness is the main character of the probability distribution shape both in wet and dry regions of the province. The wet regions however get their high precipitation from the frequent precipitation. In spite of this, the coefficient of precipitation and the shape parameter is low and about 19%. The scale parameter has a stronger relation with precipitation. Their common variance is about 40%.
Based on the best fitted probability distribution and based on the precipitation quintiles, the 25 and 75 percentiles and their anomaly have been estimated. The results show a high range in extreme precipitation in the southern area of the Golestan province.