Modeling the Relationship between Dust Storms and Extreme and Average Temperature Variables in the Western Half of Iran

The increase of dust storms occurrence in recent years in western and southwestern Iran has doubled the importance of prediction and communication of this phenomenon with climate variations. Analyzing and identifying of dust storms and its association with climatic parameters is one of the crucial approaches to reduce the caused damage of this phenomenon. Since besides determining the portion of each climate variables in intensifying the circumstances, it also can play a fundamental role in priorities, macro management policies, and upstream rules in order to control and prevent dust particles. The purpose of this study is to model the relationship of Frequency of Dust Stormy Days (FDSD) with extreme and average temperature variables in the western half of the country.

For this purpose, the hourly data of dust and codes of the World Meteorological Organization, as well as climatic data including average temperature, maximum temperature and minimum temperature on a monthly scale with a statistical period of 25 years (1990-2014) in 26 synoptic stations located in the western half of the country were used. After reviewing and controlling the quality of station statistics and eliminating statistical deficiencies, the homogeneity of the data was evaluated using the Run Test and the randomness of the data was accepted at a 95% confidence level. The Pearson and Spearman correlation coefficients as well as a multivariate linear regression method were used in communicate the frequency of days associated with dust storm with extreme and average temperature variables. In this study, the observational values of the frequency of days with dust storm were considered as dependent variables and the average temperature data and cardinal temperature variables were considered as independent variables. In order to analyze the correlation, the zoning map of the coefficients was prepared by IDW method in ArcGIS software.

The results showed that the highest correlation coefficient with FDSD index was related to the maximum temperature variable in Abadan station with 0.875 and the minimum temperature in Ahvaz station with 0.893. Also, with increasing FDSD index, correlation coefficient values increasedat Abadan and Ahvaz stations, the stations which had the highest number of dust days with 401 and 321 days, respectively, during the 25-year period. Multivariate regression modeling between FDSD and different temperature parameters in the western half of the country showed that the most important factors influencing dust events are the extreme temperature variables.In all 26 stations studied, there is a positive correlation between the minimum temperature and the frequency of days with dust storm, but this correlation is more significant in some stations and in Dehloran, Ilam, Kermanshah, Safi Abad and Sanandaj stations at 95% confidence level and also in Hamedan (Airport), Islamabad Gharb, Abadan, Ahvaz, Bandar Mahshahr and Bostan stations were significant at 99% confidence level. Meanwhile, the highest Spearman correlation coefficient between different temperature parameters and Frequency of Dust Stormy Days (FDSD) is related to the maximum temperature variable in Ahvaz, Abadan, Bostan and Bandar Mahshahr stations with correlation coefficients of 0.59, 0.57, 0.53 and 0.51, respectively, have been registered. The highest Pearson correlation coefficient between temperature parameters and frequency of days with dust storm is related to the minimum and maximum temperature variables, which were recorded in Ahvaz and Abadan stations with a correlation coefficient of 0.893 and 0.875, respectively. Regression models show that, in the best case scenario, the temperature variables of 81.2% (Abadan) and 79.3% (Bandar Mahshahr) determine the changes in the FDSD index.

The cardinal temperature variables are known as an important and influential factor in the formation of dust storms because increasing the values of Cardinal temperature parameters leads to excessive evaporation from the soil surface, which can provide a source of particles for the occurrence of such dust storms. It should be noted that the average temperature variable can also have an important effect on increasing dust events, but compared to the cardinal temperature variables, its effect is much less. The results of this study can be useful in managing the issues caused by dust storms and in the combating plans to desertification in the study regions. Also, the results of this research can be a new guide for predicting and modeling the phenomenon of dust storms in the country.