Identification of Supercooled Cloud Water by FY-4A Satellite and Validation by CALIPSO and Airborne Detection

Cold clouds are the main operation target of artificial precipitation enhancement, and its key is to find a supercooled cloud water area where catalyst can be seeded promote formation particles increase ground. Based on multi-spectral characteristics Fengyun-4A (FY-4A) satellite, methodology for identifying developed. Superimposed by top brightness temperature 10.8 µm, combination 0.46 1.6 2.2 µm red–green–blue (RGB) composites used identify phase obtain real-time distribution every 5 min in 2 km resolution whole coverage China. RGB composition, supervised machine learning method K-mean clustering was applied classify phase. The results were validated extensively with Cloud–Aerosol Lidar Orthogonal Polarization (CALIOP). It worthwhile highlight that corresponding hit rate reached 87% over full disk domain both summer winter seasons. Furthermore, 29 November 2019, microphysical properties measured, data droplets ice crystals obtained using YUN-12 transport aircraft Taiyuan. After simultaneously matching satellite an airborne track, particle image near within during climb descending stages flight. from compared identified FY-4A Moderate Resolution Imaging Spectroradiometer (MODIS) products. case study comparison show (1) good agreement those measurement at (2) positions shapes correspond well MODIS However, there small deviation extent clouds, which mainly located transition between clouds. slightly larger than Combined detection, shows consistent detection. meet needs operational enhancement cold improve effectiveness, application technology weather modification.