Trend Analysis of Dusty Days Frequency and its Correlation with Climatic Variables (Case Study: Lorestan Province)

In this research in order to find and investigate the trend of dusty day events and their relation to climatic variables (maximum temperature and maximum wind speed), hourly and daily dust data and also weather data of 10 synoptic stations with common period (2000-2014) in Lorestan province were studied. For this purpose, data normalization was examined by Kolmogorov-Smirnov test. The non-parametric Mann-Kendall and Spearman’s tests at 95 percent confidence level were used to investigate the trend of dusty events. Inverse distance weighting (IDW) method in Arc GIS software was employed for zoning Mann-Kendall indices of dust and climatic variables. In order to find a correlation between climatic variables and dust events, the weather data (as independent variables) and the frequency of dusty days (as a dependent variable) were analyzed by Pearson correlation method. Among ten series of seasonal data, Azna, Aligudarz and Kuhdasht stations had a high significant correlation between climatic variables and the frequency of dusty days. As in Azna station, the maximum wind speed variable (with 0.55 correlation coefficient), in Aligudarz station, the maximum temperature variable (with 0.78 correlation coefficient), and in Kuhdasht station, the maximum wind speed variable (with 0.82 correlation coefficient) had the highest correlation with dust events.