Assimilation of FY-3D MWRI L1 Data in GSI Hybrid-4DEnVar

To address the gap in the assimilation function of the Fengyun satellite microwave imager in the CMA-RA V1.5 development system and enhance the application value of domestic satellite observation resources, this study conducted observation preprocessing for L1 data of the FY-3D Microwave Radiation Imager (MWRI), constructed an assimilation module based on the GSI system, and performed a one-month batch experiment and evaluation using the Hybrid-4DEnVar method. The results show that the adopted quality control and bias correction schemes are reasonable and reliable, which can effectively screen high-quality clear-sky over-ocean observations and correct systematic biases. After MWRI assimilation, the quality of specific humidity analysis is improved: the root mean square error (RMSE) of 800hPa specific humidity analysis is reduced by up to 1.05% (passing the significance test), and the dry bias near 800hPa in the tropics and the wet bias below 700hPa in the Southern Hemisphere are corrected. The 0–72 h specific humidity forecasts show significant improvements in the lower and middle troposphere (600–950hPa), with particularly notable improvements in forecasts within 24 h near 800hPa (the maximum error reduction reaches 8.74 mg/kg). The RMSE of 3/6/9 h forecasts is reduced by up to 1.4%, and the anomaly correlation coefficient (ACC) of 700hPa specific humidity forecasts is increased by 0.001–0.01. The forecasts of wind and temperature fields exhibit a neutral-to-positive effect, and the geopotential height is improved at certain time steps of medium-range forecasts. The core contribution of FY-3D MWRI data assimilation focuses on the improvement of humidity analysis and forecasts, while its overall impact on other meteorological elements is relatively neutral.