Rapid-Update Assimilation of All-Sky FY-4A/AGRI Radiances for the Analysis and Prediction of Severe Convective Weather

High spatiotemporal resolution infrared radiances from FY-4A/AGRI (Advanced Geostationary Radiation Imager) can provide crucial information for rapidly developing severe convective weather. This study established a symmetric observation error model that differentiates between land and sea for FY-4A/AGRI all-sky assimilation, developed an all-sky assimilation scheme for FY-4A/AGRI based on hydrometeor control variables, and investigated the impacts of all-sky FY-4A/AGRI water vapor channels at different altitudes and rapid-update assimilation at different frequencies on the assimilation and forecasting of a severe convective weather event. Results show that simultaneous assimilation of two water vapor channels can enhance precipitation forecasts compared to single-channel assimilation, which is mainly attributable to a more accurate analysis of water vapor and hydrometeor information. Experiments with different assimilation frequencies demonstrate that the hourly assimilation frequency, compared to other frequencies, incorporates the high-frequency information from AGRI while reducing the impact of spurious oscillations caused by excessively high-frequency assimilation. This hourly assimilation frequency reduces the incoordination among thermal, dynamical, and water vapor conditions caused by excessively fast or slow assimilation frequencies, thus improving the forecast accuracy compared to other frequencies.