Super-cooled and mixed-phased cloud properties from space-borne active sensors

A Numerically effective physical model for analyzing space-borne lidar signals from water and mixed-phased clouds are developed and implemented into the standard water cloud retrieval algorithm for the EarthCARE satellite mission (JAXA-ESA). With the algorithm, retrieval of global water cloud microphysics from space-borne active sensor synergy is carried out using A-train data. Improved estimates of particle size and water content from CALIOP are expected by analyzing both backscattering coefficient and depolarization ratio. Furthermore, cloud particle-drizzle mass ratio are estimated from combined CloudSat and CALIOP data, and evaluation by ground-based lidar/cloud radar observations were performed. The derived statistics of cloud microphysical properties in high latitudes are investigated to link their relation to sea ice concentration and the Arctic climate.