Modeling Asian dust storms using the WRF-Chem model constrained by the GOCI, MI, and SMAP satellite observations

Asian dusts occur year-round and substantially influence air quality as well as weather and climate. It is important to forecast dust storms as a part of air quality modeling to protect public health and minimize the disruption to essential daily routines. However, current models are not able to accurately stimulate Asian dust storms, and often underestimate the magnitude of these storms. In this study, we simulate the dust episodes during the DRAGON-Asia field campaign in 2012 using WRF-Chem with the GOCART option. All available dust parameterizations in the model fail to simulate dust abundances measured by the geostationary satellite instruments, CALIPSO, AERONET, ground-based lidar and in-situ monitors. The model constrained by the Korean geostationary satellite Geostationary Ocean Color Imager (GOCI) and Meteorological Imager (MI) aerosol optical depth data accurately predicts the vertical distributions of dust concentration as well as the vertically-integrated aerosol loadings. This is critical in assessing the impact of remote dust emissions on the receptor area, South Korea. We extend our method to simulate the dust events observed during KORUS-AQ in 2016 by utilizing the SMAP satellite soil moisture data. This study highlights the shortcomings of Asian dust modeling and demonstrates the potential benefits of incorporating satellite data into current dust models.