Applying CloudSat/A-Train and ECMWF analyses to constrain and evaluate cloud, convection and radiation processes in climate/forecast models

Representing clouds, convections and their radiative effects in numerical weather and global climate models remains a challenge. A CloudSat-centric, multi-parameter A-Train and high-resolution ECMWF analyses data set is being developed to characterize dynamic, radiative and micro-physical processes associated with clouds and convection. The data set includes parameters from CloudSat, CALIPSO, AIRS, AMSR, MODIS, CERES etc and the ECMWF analyses. We apply a subset of the above data in the context of an analysis of the ECMWF, NASA GEOS5, and NASA fvMMF models to evaluate key model physical parameters/processes associated with clouds and convection. The aim of our analysis is to more effectively develop and constrain model representations of clouds and convection and their radiative properties, including considerations of cloud regimes from PBL stratocumulus to deep convection. In this presentation, we will present results from 1) the comparisons between cloud, convection, precipitation and radiation statistics, 2) the evaluation of the assumptions concerning convective cloud entrainment in the convection parameterizations and 3) the errors in the estimated TOA radiative fluxes associated with a relatively common GCM procedure of ignoring convective/precipitating ice.