Algorithm for Detecting Ice Overlaying Water Multilayer Clouds Using the Infrared Bands of FY-4A/AGRI

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).