Document Type : Original Article
Authors
1
Department of Climatology, Hakim Sabzevari University, Sabzevar, Iran
2
Iran-Khorasan Razavi - Sabzevar - Tohid Shahr-Hakim Sobzavari University- Faculty of Geography and Environmental Sciences - Weather Group
Abstract
The purpose of this study is to investigate the dust and predict the best time series models for the cities of Khuzestan province during the years 2019-2023. The statistical method of the library and using the annual data, eight cities selected from Khuzestan province to identify and predict the best time series models using the software Minitab17, spss19 Excel 2013. For this purpose, annual dust data from eight meteorological stations of Khuzestan province during the period of 1990-2010 were collected and analyzed using the ridge test of homogeneity of dust data. Using time series models of dust walnuts and the best model for identifying fitted dust, the accuracy and accuracy of the models were based on absolute error (MAE), absolute error (MAPE), root mean square error (RMSE average), and The BIAS standard has been approved. The results of the most suitable models of Dust Time Series for the cities of Masjed Soleyman and Behbahan are Halt Winters forecast model, Dezful city alone in the model of Arima (1.0.1) and Ahwaz, Ramhormoz, Aghajari, Abadan and Omidieh models Nemo is smoothly achieved. Also, the results of the dust show that the city of Omidieh with the highest difference of dust increases to 79 days and the city of Dezful reaches the lowest number with 9 days. And the rest of the cities are Abadan, Aghajari, Ramhormoz, Ahvaz, Masjed Soleyman and Behbahan, respectively, 75, 45, 45, 41, 36 and 25 days a year.
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