Data assimilation of FY-4A dust aerosol observations for the CUACE/dust forecasting system

A data assimilation system (DAS) was developed for the Chinese Unified Atmospheric Chemistry Environment– Dust (CUACE/Dust) forecast system and applied in the operational forecasts of sand and dust storm (SDS) in spring in Asia. The system is based on a three dimensional variational method (3D-Var) and uses extensively the measurements of surface visibility (phenomena) and dust loading retrieval from the Chinese geostationary satellite FY-2C. By a number of case studies, the DAS was found to provide corrections to both under- and over-estimates of SDS, presenting a major improvement to the forecasting capability of CUACE/Dust in the short-term variability in the spatial distribution and intensity of dust concentrations in both source regions and downwind areas.  By now The DAS was upgrade to assimilate FY-4A dust aerosol observations. The seasonal mean Threat Score (TS) over the East Asia in spring increased when DAS was used. The forecast results with DAS usually agree with the dust loading retrieved from FY and visibility distribution from surface meteorological stations, which indicates that the 3D-Var method is very powerful by the unification of observation and numerical model to improve the performance of forecast model.