Improving estimation of a record breaking East Asian dust storm emission with lagged aerosol Ångström Exponent observations

Abstract. A record-breaking East Asian dust storm over recent years occurred in March 2021. Ångström Exponent (AE) can resolve the particle size and is significantly sensitive to large aerosol such as dust. Due to lack of observation during dust storm and high uncertainty of satellite retrieved AE, it is crucial to estimate the dust storm emission using the lagged ground-based AE observations. In this study, the Aerosol Robotic Network (AERONET) observed hourly AEs are assimilated with the fixed-lag ensemble Kalman smoother and Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to optimize the simulated dust emission from 14 to 16 March 2021. The emission inversion results reveal that the dust emissions from the Gobi desert in the official WRF-Chem are significantly underestimated. Not only the temporal variation of simulated AE but also that of simulated aerosol optical thickness (AOT) can be improved through assimilating AE information. Compared to the assimilation with only AOT, the additional inclusion of AE doubles the dust emission and induces the extra 46.8 % improvement of root mean square error (RMSE) between the simulated AOTs and the AERONET and independent Skynet Observation NETwork (SONET) observations. The optimized dust emission from Mongolia Gobi and China Gobi reach the peak value about 441.65 kt/hour and 346.87 kt/hour at 08:00 UTC on 14 March and at 19:00 UTC on 15 March, respectively. The additional inclusion of AE also best captures the magnitude and variations of aerosol vertical extinctions both in the westward and eastward pathways of dust transport.