HR: 1340h
AN: A53D-1447    [Abstracts]
TI: Preparation for Evaluating Cloud Simulations from GCMs Using the A-Train Data
AU: * Zhang, Y
EM: zhang24@llnl.gov
AF: Lawrence Livermore National Lab, 7000 East Avenue, L-103, Livermore, CA 94550, United States
AU: Klein, S
EM: klein21@llnl.gov
AF: Lawrence Livermore National Lab, 7000 East Avenue, L-103, Livermore, CA 94550, United States
AU: Mace, G G
EM: mace@met.utah.edu
AF: University of Utah, Rm819 WBB 135S 1460E, Salt Lake City, UT 84112, United States
AU: Boyle, J
EM: boyle5@llnl.gov
AF: Lawrence Livermore National Lab, 7000 East Avenue, L-103, Livermore, CA 94550, United States
AU: Xie, S
EM: xie2@llnl.gov
AF: Lawrence Livermore National Lab, 7000 East Avenue, L-103, Livermore, CA 94550, United States
AB: The launch of CloudSat and CALIPSO provides significant opportunities to properly evaluate the vertical structures of cloud macro- and micro-physical properties from model simulations. The new observational datasets will lead to the improvement of the representation of clouds and precipitation in climate models. The vertical distribution of cloud fraction combining CloudSat and CALIPSO measurements is sorted by dynamical regime using the monthly mean pressure velocity at 500 hPa from 30S to 30N. The simulations from two leading U.S. GCMs are grouped by the different dynamical regimes and compared to the observations. In this preliminary study, it has been shown that the two models underestimate the occurrence of low-level clouds in regimes of strong subsidence and overestimate that of high clouds in the ascent regime, while the satellite observations show a reasonable circulation with the basic atmospheric features in tropical regions. This result will help to analyze the regional distributions of different cloud regimes and their effects on the energy and hydrological field. In order to widely evaluate the cloud simulations from GCMs using the observations from A-Train and other satellites, a combined CFMIP ISCCP/CloudSat/CALIPSO simulator is under development. The CloudSat simulator will convert model clouds into radar reflectivity similar to the observations, and the early results from the CloudSat simulator are presented. A vertical subgrid precipitation overlap module and a statistical summary module are proposed with the least input and the fewest assumptions.
DE: 3319 General circulation (1223)
DE: 3337 Global climate models (1626, 4928)
DE: 3360 Remote sensing
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting