Satellite data play an irreplaceable role in global observation data systems. Effective comprehensive application of satellite products will inevitably improve numerical weather prediction. FengYun-4 (FY-4) series satellites can provide not only radiance data but also retrieval data with high temporal and spatial resolutions. To evaluate the potential benefits of the combination application of FY-4 Advanced Geostationary Radiance Imager (AGRI) products on Typhoon Saola analysis and forecast, two group of experiments are set up with the Weather Research and Forecasting model (WRF). Compared with the benchmark experiment, whose sea surface temperature (SST) is from the National Centers for Environmental Prediction (NCEP) reanalysis data, the SST replacement experiments with FY-4 A/B SST products significantly improve the track and precipitation forecast, especially with the FY-4B SST product. Based on the above results, AGRI clear-sky and all-sky assimilations with FY-4B SST are implemented with a self-constructed AGRI assimilation module. The results show that the AGRI all-sky assimilation experiment can obtain better analyses and forecasts. Furthermore, it is proven that the combination application of AGRI radiance and SST products is beneficial for typhoon prediction.

In the first attempt to configure the Fengyun-3B satellite’s Microwave Radiation Imager (MWRI) radiance data in the Weather Research Forecast (WRF) model’s Data Assimilation system (WRFDA), the impact of MWRI data assimilation on the analysis and forecast of Typhoon Son-Tinh in 2012 was evaluated with WRFDA’s three-dimensional variational (3DVAR) data-assimilation scheme. Compared to a benchmark experiment with no MWRI data, assimilating MWRI radiances improved the analyses of typhoon central sea level pressure (CSLP), warm core structure, and wind speed. Moreover, verified with European Center for Medium-Range Weather Forecasts (ECMWF) analysis data, significant improvements in model variable forecast, such as geopotential height and specific humidity, were produced. Substantial error reductions in track, CSLP, and maximum-wind-speed forecasts with MWRI assimilation was also obtained from analysis time to 48 h forecast.

Sea surface temperature (SST) plays an important role in the typhoon forecast. By comparison, satellite retrieval products can provide more accurate SST data than reanalysis data in typhoon simulations. However, the effect of SST data from Chinese Fengyun-3 (FY-3) satellites on typhoon simulation hasn’t been evaluated yet. In this paper, the impact of FY-3D SST retrieval data with ascending and descending orbits on the forecast of typhoon In-Fa, 2021, is investigated with the Weather Research Forecast (WRF) model. Compared to the control experiments with SST data from Global Data Assimilation System (GDAS) data, the replacement experiments with FY-3D SST data significantly improve the forecast of typhoon central sea level pressure, track, and precipitation. Especially, the SST from the descending orbit satellite data provides the optimal track and intensity forecast, which are verified against the best track data from the Japan Meteorological Agency.