Dynamic Spatial Fusion of Cloud Vertical Phase from CALIPSO and CloudSat Satellite Data

Abstract

Cloud phase is a core parameter of inversion of cloud characteristics. The accuracy of cloud phase affects the results of cloud optical and microphysical characteristics. In this study, we obtain the cloud vertical phase (CVP ) products of CALIPSO and CloudSat satellites, then we put forward a dynamic spatial fusion algorithm for the fusion of the two products. A series of spatial optimal CVP fusion rules are presented for dual-source data, and we realize CVP fusion using these rules. We took Typhoon Lupit in the Pacific Ocean as an experimental object. The results show that the total cloud pixel amount increased by 124.09% and 10.54%, respectively, compared to those of CALIPSO and CloudSat. The recognition of different CVP is 7.97% and 1.37%. The results show that this method can improve the accuracy of multi-source CVP inversion effectively, and provide new ways for the synergy of multi-sensor satellites.