Statistical modeling of dust storms using poison regression model in Isfahan Province
Iran is frequently exposed to local and synoptically dust storm due to the geographical location of Iran. In recent years, dust storm frequencies and intensities have been increased significantly in Iran and especially in Isfahan Province, seriously disrupting human life and affecting the quality of life. This phenomenon is particularly increased in the spring and summer. Climate factors play an important role in dust storms. In this research, spatiotemporal changes of climate factors and dust storms were studied. Therefore, we analyzed climate factors (precipitation, temperature, wind speed and humidity) and dust storms frequency during 1992 to 2016. Poisson regression model was used for statistical modeling of temporal and spatial variations of dust and climatic parameters. According to the models, there was conformity between the results and the predicted values throughout the months. In addition, the results showed that wind speed played a major role in the occurrence of dust storms and had the highest coefficient. The results also showed that most of the dusty days are in the spring and then in the eastern part of the province, which is related to the local centers in the eastern part of the province and summer winds.
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