Evaluations of cloud properties of global and local cloud system resolving models using CALIPSO and CloudSat simulators

This study proposes a method of using a local-area cloud system resolving model (LCRM) to evaluate and improve cloud properties simulated by a global cloud system resolving model (GCRM). We study the sensitivity to cloud microphysics schemes by comparing the simulated data of LCRM with CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) using satellite simulators. In particular, the impacts of the improved cloud microphysics scheme, which is more comprehensive than the scheme used for the GCRM experiment, with six water categories are studied. We focus on the active convective phase over the maritime continent. During the 4 day integration period of LCRM, 11 tracks of A-Train satellite observations are available. Cloud properties along the cross sections of these tracks are first examined to find the bias of the simulated data compared to the CloudSat and CALIPSO observations. The improved cloud microphysics scheme used in the LCRM reproduces the overall characteristics of the observed contoured frequency by altitude diagrams (CFADs) well, although biases are still present in the upper layers. We find that the simulated domain-averaged cloud properties can be evaluated using the observed track data. The comparison of the CFADs between LCRM and GCRM clarifies the bias in GCRM, and the new cloud microphysics scheme improves this bias. Using LCRM, sensitivities to cloud microphysics parameters are examined, and the CFADs are further improved if the ice sedimentation speed is increased. These results indicate that introduction of the graupel category or faster sedimentation of ice clouds reduces the total amount of hydrometeors and leads to more efficiency of precipitation.