We assimilated radiance observations from the Geostationary Interferometric Infrared Sounder (GIIRS) onboard the FengYun-4A geostationary satellite to evaluate their impact on the forecast of Typhoon Bavi using WRFDA. The temperature channels with high information content, representing 90% of the information content of all temperature channels, were selected for assimilation. All radiance observations above the cloud-top were assimilated by comparing the channel height to the cloud-top height coming from the product of the Advanced Geosynchronous Radiation Imager (AGRI). The assimilation of the GIIRS observations decreased the root-mean-square error of the temperature by 2% and improved the precipitation forecast. The rain band in southeast China was reproduced well, thus showing that infrared hyperspectral radiance observations have added value in improving the circulation around typhoons and, therefore, provide better forecasts. The increased relative humidity in the upper layer and stronger typhoon outflow were found to related to the intensify of typhoon in the analysis compared with the control experiment.

Multilayer clouds have a significant importance on cloud climate effects and remote sensing retrieval. In this study, a multilayer clouds detection algorithm is developed for the Advanced Geostationary Radiation Imagers (AGRI) onboard the FY-4A geostationary satellite. The algorithm is based on basic physical assumptions that are also employed for MODIS and VIIRS to identify ice overlaying water multilayer clouds. Synchronous observation of Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) has been collected and acknowledged as a reliable reference dataset for determination of the thresholds. The algorithm used the longwave infrared bands (8.5μm and 10.8μm) to determine the phase of the upper layer cloud. Then difference between solar reflectance band pairs (1.375μm and 1.61μm) is used to identify ice overlayer water multilayer clouds when the upper layer is ice cloud. When the upper layer cloud is water, the infrared band(7.1μm) is applied to find out misclassified multilayer clouds. The algorithm demonstrates a notable improvement of approximately 0.146 in the probability of detection (POD) as compared to MODIS, while using CALIOP products as reference, specifically for cases when the cloud optical depth surpasses 4. Nevertheless, it does result in a slightly elevated false alarms rate (FAR), around 0.042. In the future, it is necessary to conduct a more comprehensive validation of the algorithm, with particular emphasis on its limits in scenarios where the upper cloud layer is too thin(thick).

HIRAS II onboard in Fengyun-3E (FY-3E) early-morning-orbit meteorological satellite is the second generation hyperspectral infrared (IR) sounder of Chinese Meteorological Administration. HIRAS II has three consecutive spectral bands named long-wave (LW), medium-wave (MW) and short-wave (SW) band with 1671 more channels than its predecessor HIRAS I. Channel selection is implemented to get the optimal subset for application in numerical weather prediction (NWP) and to explore the contribution of each spectral band. The iterative channel selection method using information content (IC) is applied in temperature and water vapor channel selection based on temperature and humidity sampled profiles respectively. In total, 150 channels were chosen, consisting of 35 LW temperature channels, 65 MW temperature channels, and 50 MW water vapor channels. The temperature channel selection shows the selected channels in LW band present most information in upper troposphere, while the selected channels in MW band present most information in the mid and lower troposphere. It’s found that the humidity of atmosphere profile has large impact on the water vapor channel selection. As the increase of profile humidity, the maximum contribution layer of channel IC shift upward and the degrees of freedom for signal (DFS) profile become sharper and narrower, which results in the variation of channel selection.