عنوان مقاله [English]
Long term trend analysis of meteorological variables has a great importance in climate change detection studies. The purpose of this study was to assess changes in relative humidity and dew point temperature over the period 1973-2003. Monthly data of relative humidity and dew point temperature of 22 synoptic stations of Iran were obtained from Iran Meteorological Organization (IRIMO). These stations represent different climates of the country based on De Martonne climatic classification. All seasonal and annual series have been checked for normality with the Kolmogorov-Smirnov test. Time trends of both variables were analyzed using parametric and non-parametric techniques (Least square linear regression, Mann-Kendall and rho-Spearman correlation coefficient).Based on the results of Mann-Kendall test, the most significant increasing trend of both variables exists in summer season and the least trend of relative humidity was observed in winter season. The most and least increasing trend of dew point temperature was observed in spring and autumn respectively. Using rho-spearman correlation coefficient, the most significant decreasing trend of relative humidity was observed in annual and spring time series. Parametric test of regression analysis revealed no specific trend in dew point series, but all seasonal series of relative humidity showed trend. In general, the decreasing trend of series was more that increasing trend. The results indicated that no specific climatic pattern of trends can be suggested.