The Impact of Assimilating Cirrus‐Effected Infrared Satellite Radiance From the FY‐4A AGRI on Water Vapor Analysis and Rainstorm Forecasting.

In this study, a method for assimilating FY4A advanced geostationary radiance imager (AGRI) cirrus‐effected radiances (CER) is investigated, and the impact of this method on water vapor analysis and rainstorm forecasting is examined through observing system simulation experiments and actual case experiments. The high proportion of inverted humidity profiles in the cirrus‐effected pixels is the main reason for the negative effect of assimilation in the mid‐to‐lower troposphere. To address this, relevant constraint conditions are incorporated into the cost function. The statistical results reveal that the addition of a CER assimilation improves the analysis increment of water vapor, with pattern correlation coefficients of 0.33, 0.35, and 0.20 at 200, 300, and 400 hPa, respectively, which are greater than those of a clear‐sky radiance assimilation (0.28, 0.33, and 0.17, respectively). Moreover, the inclusion of a CER assimilation greatly improves data utilization, and has a neutral to positive effect on precipitation forecasting. Plain Language Summary: Infrared all‐sky radiance assimilation is an attractive but challenging problem in satellite data assimilation. Is there an alternative approach to achieve the assimilation of infrared radiance for a certain type of cloud? It is found that cirrus clouds, which are loose ice clouds composed of ice crystals, can partially transmit infrared radiance and are large in number. Considering these advantages, a new direct assimilation method for FY4A advanced geostationary radiance imager (AGRI) cirrus‐effected radiances is proposed in this paper. The method addresses the uncertainty in the assimilation of cirrus‐effected radiances by adding weak constraints of inverse humidity. This research highlights the substantial increase in AGRI data usage when incorporating cirrus‐effected radiance data, as well as the neutral‐to‐positive impact on water vapor analysis and precipitation forecasting. This study also suggests that future endeavors could combine infrared channels with lower‐level microwave channels, which may have a more significant contribution to infrared radiance assimilation. Key Points: A high percentage of inverse humidity exists in the atmospheric profile corresponding to cirrus cloud fields of view over landThe assimilation of cirrus cloud pixels greatly improves the utilization rateAssimilating advanced geostationary radiance imager cirrus‐effected radiances has a neutral to positive effect on water vapor analysis and precipitation forecasting [ABSTRACT FROM AUTHOR]