A Supercooled Water Cloud Detection Algorithm Using Himawari-8 Satellite Measurements

Abstract

The detection of supercooled water clouds (SWCs) is essential for artificial rain enhancement, the prevention of aircraft ice accretion, and better understanding of radiative energy balance. However, it is challenging to identify SWCs using only passive satellite measurements. We adopt measurements from the Advanced Himawari Imager, which is onboard the new-generation, high temporal, spatial, and spectral resolution geostationary Himawari-8 satellite, to develop a time-continuous Himawari-8 SWC (HSWC) algorithm. The HSWC algorithm includes a group of tests using comprehensive cloud properties (e.g., cloud phase [CPH], cloud top temperature, cloud optical thickness, and cloud effective radius [CER]). Unlike previous SWC detection algorithms, which are based on cloud top temperature and cloud optical thickness properties, we introduce CER and CPH information into the HSWC algorithm because the distribution of SWCs is sensitive to CER values, and SWCs may appear in mixed-phase clouds identified by satellites. Our analyses indicate that the additions of the CER and CPH tests could improve the performance of SWC detection by 15.07% and 4.75%, respectively. The full disk SWC detection results identified by the HSWC algorithm in January, May, August, and October of 2017 are validated using lidar measurements. The hit rate and false alarm rate are 93.52% and 25.27%, respectively. Our study provides potential SWC regions for the implementation of artificial rain enhancement.