Abstract

Accurate estimation of wind direction and speed is essential for enhancing the simulation and prediction of dust storms. Being highly susceptible to dust storms, Western Iran necessitates a detailed evaluation of dust concentration and wind fields. This study employs the WRF-Chem model to simulate these parameters over the period from April 7 to 26, 2022. Four different model configurations were tested, involving the Yonsei University (YSU) and Mellor-Yamada-Janjic (MYJ) boundary layer schemes, as well as the Lin and WRF Single-Moment 6-Class (WSM6) microphysics schemes. The results indicate that during the selected period, different synoptic systems led to the release of dust from Iraq and Saudi Arabia and its transport to western Iran. The mid-level southerly and southwesterly wind directions have a significant impact on dust transport to the northwestern regions of Iran by high and complex mountainous terrain. The horizontal and vertical distribution of simulated dust demonstrates good agreement with TERRA satellite imagery, MERRA-2 dust surface concentration, and CALIPSO, respectively. The daily dust concentration of the WRF-Chem model has a correlation of −0.32 to −0.96 with visibility and 0.68 to 0.86 with MERRA-2 data in Western Iran. The simulated dust concentration relation with visibility and AERONET AOD (Aerosol Optical Depth at 500 nm) was calculated at −0.78 and 0.29, respectively in Zanjan station. The horizontal and vertical distribution, temporal series, and statistical indices of the wind field show that the WRF-Chem model performs well in the Iran West boundary, especially in the west and northwest, where the 10-m wind speed increased to 14 m s−1. The boundary layer scheme in the WRF-Chem model has a more significant impact than the microphysics scheme in simulated 10-m wind speed and dust concentration. The final result shows that the combination of the YSU boundary layer and WSM6 microphysics schemes performs very well in simulating wind fields and dust in western Iran under various weather conditions.

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