Evaluation of Tropical Convection and Radiation for 20th Century IPCC AR 4th and 5th Simulations using Multi-sensors

The realistic representation of tropical convection and its influence on radiation in global models remains a big challenge for both numerical weather prediction and climate projections across a wide range of temporal and spatial scales such as the ITCZ and ENSO, etc. Precipitating and convective core cloud hydrometeors and their radiative effects are generally ignored in global climate models (GCMs) such as those used in IPCC 4th and 5th Assessment Reports. However, remote sensors such as CloudSat and CERES/SRB are sensitive to all particles, including precipitating and suspended cloud hydrometeors and their radiation. We examine GCMs within CMIP3 and CMIP5 with respect to their representation of ice, liquid water, and radiation fields in both cloudy and precipitating forms in the ITCZ/SPCZ as well as convectively active regions over South America, Central Africa, and the Warm Pool. This includes cloud ice and cloud liquid comparisons and the development of estimates of falling vs suspended (i.e. precipitating vs cloudy) components of atmospheric water from A-Train satellite data – namely from CloudSat and CALIPSO, that can provide more direct and robust model-observation comparisons. Surface sensible and latent heat fluxes from ECMWF and MERRA reanalyses, as well as CERES and SRB radiation data, are used for model radiation evaluations. The comparison between CMIP3 and CMIP5 model fidelity using these measures shows no substantial improvement between the two successive CMIP archives in cloud hydrometeors and radiation simulations. A double ITCZ remains an issue in most CMIP5 simulations. Significant disparity is found in the magnitudes of cloud water content vertical (and cloud fraction/frequency) profiles over the ITCZ, Warm Pool, Central Africa, and South America among the CMIP5 models with a factor ranging from 10% (e.g., Inmcm4 CGCM) to 600% (two GISS CGCMs) compared to observed estimates. While the global energy budget is well in-balance at the TOA, the largest bias is found in the surface energy budget from the downward shortwave flux resulting from excessive net downward surface fluxes over the Warm Pool, ITCZ and convectively active regions compared to CERES/SRB data. This may be caused by not treating the interaction of precipitation with radiation in the models.