Further development and application of the WRFDA-Chem three-dimensional variational (3DVAR) system: Joint assimilation of satellite AOD retrievals and surface observations

The capability to assimilate Aerosol Optical Depth (AOD) is developed within the WRFDA system in this study using the three-dimensional variational (3DVar) algorithm, based on the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosol scheme of the Weather Research and Forecasting model coupled with online Chemistry (WRF-Chem). Experiments assimilating Himawari-8 satellite AOD retrievals along with surface observations (PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO) are conducted over China for the period from 25 December 2016 to 9 January 2017. The performances of data assimilation for both analyses and forecasts are evaluated against various datasets, including the surface PM_2.5 and PM₁₀ measurements, the Himawari-8 AOD and aerosol extinction coefficient (AEC) profile data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The DA experiments exhibit positive effects on the analyses and forecasts of surface PM_2.5 and PM₁₀, AOD, and aerosol vertical extinction coefficient to different degrees. Compared to the assimilation of ground-based observations, which is highly effective in improving surface aerosol forecasts, the Himawari-8 AOD assimilation exhibits a greater improvement on the AOD and AEC profile. The experiment assimilating the Himawari-8 AOD and surface observations simultaneously performs the best, in terms of both the horizontal and vertical distributions of aerosols. Results reveal the potential of the combined assimilation of satellite retrievals and surface observations, especially in generating a better aerosol structure for both analyses and forecasts.