High-level Clouds Represented in a Global Cloud-system-resolving Model

Toshiro Inoue University of Tokyo

Category: Modeling

Working Group: Cloud Life Cycle

Vertical and horizontal distributions of high-level clouds (ice and snow) simulated in high-resolution global cloud-system-resolving simulations by the Non-hydrostatic Icosahedral Atmospheric Model (NICAM) are compared with satellite observations. Ice and snow data from a one-week experiment by the NICAM 3.5-km-grid mesh global simulation initiated at 00UTC 25 December 2006 are used in this study. The vertical structure of ice and snow represented by NICAM was compared with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat observations. High-level clouds (cumulonimbus- and cirrus-type clouds) classified by the split window (11 and 12 m) data onboard geostationary meteorological satellites (GMSs) were used for comparison of the horizontal distribution of ice and snow in NICAM. The vertical distribution of ice and snow simulated by NICAM qualitatively agree well with those of cloud signals observed by CALIPSO and CloudSat. We computed corresponding cloud lidar backscatter coefficients and cloud radar reflectivity signals from ice and snow data of NICAM using Cloud Feedback Model Intercomparison Project (CFMIP) observational simulator packages (COSP). The contoured frequency by altitude diagram (CFAD) for the cloud lidar backscatter coefficients shows lower frequency at higher altitude of 8–14 km by NICAM than CALIPSO observations. This suggests that the amount of ice is not well represented in NICAM. The simulated cloud radar reflectivity signals by NICAM indicated higher frequency at 8–10 km altitude than CloudSat observations, although there were some differences between over oceans and continents. This implies that the amount of snow is larger in NICAM simulations. The horizontal pattern of ice clouds (column-integrated ice and snow of greater than 0.01 kg/m2) in NICAM shows good agreement with that of high-level clouds identified by the split window analysis. During this one week simulation, 48–59% of ice clouds in NICAM matches with observed high-level clouds. The cross correlation between the spatial distributions of simulated ice clouds and satellite-observed high-level clouds is 0.40-0.51, and the equitable threat score is 0.31-0.45.

This poster will be displayed at ASR Science Team Meeting.