27ATCHEM Performance Evaluation of Mega Dust Storm Predictions Using Dust Emission and Land Surface Schemes in WRF-Chem over South Korea

This study evaluates the performance of the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) in predicting a mega Asian Dust Storm (ADS) event that impacted South Korea on March 28–29, 2021. Since the ADS crisis warning system was implemented in South Korea in 2015, a nationwide caution stage was issued for the first time in six years on March 29, 2021. In this study, we focused on evaluating a combination of parameterization schemes—five for dust emission and four for land surface processes—that are crucial for accurate numerical forecasting of dust storms. By utilizing both in-situ and remote sensing data, we conducted a comprehensive evaluation of meteorological and air quality variables across South Korea, including 2 m temperature, 2 m relative humidity, 10 m wind speed, PM10, and aerosol optical depth (AOD). Our findings suggest that the prediction accuracy of surface meteorological variables was influenced more by the land surface scheme than by the dust emission scheme, with scheme combinations based on Noah land surface model with Multiple Parameterization options (Noah-MP) generally showing good performance. In contrast, in predicting air quality variables, such as Particulate Matter 10 (PM10) and AOD, there was a significant difference in performance depending on the scheme combinations due to the influence of the dust emission scheme, which is directly related to the generation and amount of dust. Based on the evaluation of various dust emission and land surface scheme combinations, this study suggests optimal scheme combinations for the WRF-Chem model in cases of mega ADSs affecting Korea.