Using statistical models to identify the phenomenon of climate change Case study : Kerman and Bam stations

Subject Areas : Geopolitic

هوشمند Ataei ¹ , راضیه Fanaei ² , M.A Rajaei ³ , مهدیه Fatehi ⁴

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Received: 2015-01-31 Accepted : 2015-01-31 Published : 2013-10-23

Keywords: Autocorrelation function test, Climate Change, Humidity, Mann–Kendall test, temperature, Trend,

Abstract :

This study investigated the process of climate change both Kerman and Bam stations as, Kerman province has been selected stations. Was used in this base the parameterthe average bulb temperature, minimum temperature, maximum temperature, daily temperature, absolute minimum temperature, absolute maximum temperature, mean relative humidity, maximum relative humidity, minimum relative humidity and total precipitation of scale Monthly and annual during the period 1957-2005. In start was examined  the normal and homogeneity used data use Anderson-Darling and Chi-square test. Then, was employed for data with normal distribution and the autocorrelation function test and abnormal distribution of the data, statistical-graphics tests Mann-Kendall. In outrance was performed the trend analytical model the least squares method on normally distributed data. The results of this study indicate that in Kerman station trends were observed in the months that followed of trend patterns; average bulb temperature of decrease trend, the mean absolute maximum temperature without trend and the other elements have been increased trend. The damping of the mean relative humidity and maximum relative humidity increases trend and minimum relative humidity have been decrease trend. Was confirmed there are an increase trend in temperature elements and decrease in humidity elements Bam station during the study period.