Publications

Wang, KY; Wang, F; Lu, QF; Liu, RX; Zheng, ZJ; Wang, ZW; Wu, CQ; Ni, ZY; Liu, XF (2024). Algorithm for Detecting Ice Overlaying Water Multilayer Clouds Using the Infrared Bands of FY-4A/AGRI. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 21, 1001205.

Abstract
Multilayer clouds have a significant importance on cloud climate effects and remote sensing retrieval. In this study, a multilayer cloud detection algorithm is developed for the Advanced Geostationary Radiation Imager (AGRI) onboard the FY-4A geostationary satellite. The algorithm is based on the basic physical assumptions that are also employed for Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imager Radiometer Suite (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 thresholds. The algorithm used the long-wave infrared bands (8.5 and 10.8 mu m ) to determine the phase of the upper layer cloud. Then, the difference between solar reflectance band pairs (1.375 and 1.61 mu m) 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 (7.1 mu m ) is applied to find misclassified multilayer clouds. The algorithm demonstrates a notable improvement of approximately 0.146 in the probability of detection (POD) compared to MODIS while using CALIOP products as a reference, specifically for cases when the cloud optical depth (COD) surpasses 4. Nevertheless, it does result in a slightly elevated false alarm 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).

DOI:
10.1109/LGRS.2024.3372150

ISSN:
1558-0571