Testing hydrometeor particle type discrimination derived from CloudSat and CALIPSO

Abstract

We developed a test version of algorithm that discriminate cloud/precipitation phase and ice cloud particle shape (hereafter, hydrometeor particle type) from the synergy use of the cloud profiling radar (CPR) onboard CloudSat satellite and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. We used the CALIOP classification algorithm that was developed by Yoshida et al. (2010) and modified by Hirakata et al. (2014). The CPR algorithm mainly consisted of the following steps: (1) initial discrimination by the look-up-table derived from the match-up statistical analysis of the CPR radar reflectivity, CALIOP cloud particle type and Tropical Rainfall Measuring Mission (TRMM) precipitation, and (2) precipitation correction of initial discrimination by unattenuated surface radar reflectivity. Lastly, the CPR and CALIOP synergy particle type was discriminated, simply by selecting the hydrometeor type that was most reasonable. In this study, we showed two case studies of the CPR, the CALIOP and the synergy discrimination results. By taking the advantage of CPR’s capability to penetrate into thick cloud and observe light precipitation, and CALIOP’s sensitivity to detect thin ice clouds, the synergy algorithm gave seamless vertical profile from thin cloud to precipitation.