A three-dimensional variational data assimilation system for aerosol optical properties based on WRF-Chem v4.0: design, development, and application of assimilating Himawari-8 aerosol observations

Abstract. This paper presents a three-dimensional variational (3DVAR) data assimilation (DA) system for aerosol optical properties, including thickness (AOT) retrievals and lidar-based profiles, developed the Model Simulating Aerosol Interactions Chemistry (MOSAIC) within Weather Research Forecasting model coupled to (WRF-Chem) model. For computational efficiency, 32 variables in MOSAIC_4bin scheme are lumped into 20 state that representative of mass concentrations DA system. To directly assimilate an observation operator based on Mie scattering theory was employed, which obtained by simplifying module WRF-Chem. The tangent linear (TL) adjoint (AD) operators were then established passed TL/AD sensitivity test. Himawari-8 derived AOT assimilated validate investigate effects both PM2.5 simulations. Two comparative experiments performed with cycle 24 h from 23 29 November 2018, during heavy air pollution event occurred northern China. performances simulation evaluated against independent observations, Robotic Network (AERONET) surface measurements. results show can significantly improve analyses forecasts. Generally, control without seriously underestimated AOTs compared observed values therefore unable describe real pollution. analysis fields closer observations improved simulations, indicating successfully In terms statistical metrics, assimilating only limitedly inner domain (D02); however, positive effect last over h. Assimilation effectively enlarged be distribution China, is great value studying events.