Comparison of high‐level clouds represented in a global cloud system–resolving model with CALIPSO/CloudSat and geostationary satellite observations

Abstract

[1] Vertical and horizontal distributions of high-level clouds (ice and snow) simulated in high-resolution global cloud system-resolving simulations by the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) are compared with satellite observations. Ice and snow data in a 1 week experiment by the NICAM 3.5 km grid mesh global simulation initiated at 0000 UTC 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 mm) data on board geostationary meteorological satellites (GMSs) were used for comparison of the horizontal distributions of ice and snow in NICAM. The vertical distributions 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. The contoured frequency by altitude diagram for the cloud lidar backscatter coefficients shows lower frequency at higher altitude of 8-14 km by NICAM than CALIOP 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/m 2 ) in NICAM shows good agreement with that of high-level clouds identified by the split window analysis. During this 1 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. Furthermore, temporal variations of column-integrated ice clouds in NICAM are compared with high-level clouds classified by the split window at the decaying stage of deep convection over the tropics. The results indicate that the mean decaying speed of ice clouds of NICAM and high-level clouds by satellite observations agrees well for this analysis area and period, although the variances are larger in NICAM. This implies that the fall speed of snow in this NICAM experiment is appropriate to depict the decay of anvil clouds by compensating for the excess of snow in NICAM simulations, when we assume that the decay of anvil clouds is largely controlled by the evaporation of ice and snow.

Evaluation of ice and snow content in the global numerical weather prediction model GME with CloudSat

“…A likely explanation for the underestimation is that while CloudSat can not distinguish between cloud ice and snow, precipitating ice is diagnostic in many climate models and therefore does not contribute to IWP. This is typically not the case for high resolution ( x < 10 km) models (e.g., Inoue et al, 2010), that treat snow as a prognostic variable, meaning it can interact with cloudy and dry environment during sedimentation. The comparison between model cloud ice and snow with retrieved total ice (observation-to-model approach) still has limitations due to assumptions in the retrieval, e.g., particle size distribution.…”

A global non-hydrostatic model study of a downward coupling through the tropical tropopause layer during a stratospheric sudden warming

“…The cloud properties in the upper troposphere (UT) have been evaluated in comparison with satellite observations (e.g. Inoue et al, 2010;Kodama et al, 2012).…”

The Intra-Seasonal Oscillation and its control of tropical cyclones simulated by high-resolution global atmospheric models

“…A global high-resolution simulation with a mesh size of approximately 3.5 km using the Nonhydrostatic Icosahedral Atmospheric Model (NICAM; Sato et al 2009;Tomita and Satoh 2004) showed realistic behavior of tropical cloud systems associated with diurnal to intra-seasonal variability Sato et al 2009;Inoue et al 2010). An interesting result from the NICAM simulations is that the behavior of the ISO/MJO bears some similarity with the observations, even as the mesh size is coarsened to approximately 7 and 14 km Masunaga et al 2008;Taniguchi et al 2010), although such resolutions are not generally used for nonhydrostatic models.…”