An ensemble-based assimilation system that used the MASINGAR mk-2 (Model of Aerosol Species IN the Global AtmospheRe Mark 2) dust forecasting model and satellite-derived aerosol optical thickness (AOT) data, processed in the JAXA (Japan Aerospace Exploration Agency) Satellite Monitoring for Environmental Studies (JASMES) system with MODIS (Moderate Resolution Imaging Spectroradiometer) observations, was used to quantify the impact of assimilation on forecasts of a severe Asian dust storm during May 10–13, 2011. The modeled bidirectional reflectance function and observed vegetation index employed in JASMES enable AOT retrievals in areas of high surface reflectance, making JASMES effective for dust forecasting and early warning by enabling assimilations in dust storm source regions. Forecasts both with and without assimilation were validated using PM10 observations from China, Korea, and Japan in the TEMM WG1 dataset. Only the forecast with assimilation successfully captured the contrast between the core and tail of the dust storm by increasing the AOT around the core by 70–150% and decreasing it around the tail by 20–30% in the 18-h forecast. The forecast with assimilation improved the agreement with observed PM10 concentrations, but the effect was limited at downwind sites in Korea and Japan because of the lack of observational constraints for a mis-forecasted dust storm due to cloud.
All Science Journal Classification (ASJC) codes
- Chemical Engineering(all)
- Materials Science(all)