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Climate Models Do Not Simulate Real-World Cloud Structures Well

Zhang, Y., Klein, S.A., Boyle, J. and Mace, G.G. 2010. Evaluation of tropical cloud and precipitation statistics of Community Atmosphere Model version 3 using CloudSat and CALIPSO data. Journal of Geophysical Research 115: doi:10.1029/2009JD012006.
Clouds are key determinants of earth's surface energy balance. They can reflect incoming shortwave radiation back to space and absorb outgoing longwave radiation and reradiate it back to earth, depending on their altitude and thickness. And in this regard, authors Zhang et al. (2010) note that the different representations of clouds and their feedback processes in Global Climate Models (GCMs) have been identified as major sources of differences in model climate sensitivities, stating that "contemporary GCMs cannot resolve clouds and highly simplified parameterizations are used to represent the interactions between clouds and radiation."

In this study, cloud profiling radar data from the CloudSat satellite were combined with lidar data from the CALIPSO satellite to obtain 3D profiles of clouds and precipitation regimes across the tropics. Some of these profiles corresponded to well-known weather features, such as low clouds, thin cirrus, cirrus anvils, etc.; and they were compared to output obtained from the Community Atmosphere Model version 3 (CAM3.1), which exercise revealed that the model "overestimates the area coverage of high clouds and underestimates the area coverage of low clouds in subsidence regions." And what was particularly striking, in the words of Zhang et al., was "the model overestimate of the occurrence frequency of deep convection and the complete absence of cirrus anvils," plus the fact that "the modeled clouds are too reflective in all regimes."

Since incoming and outgoing radiation are strongly affected by the 3D spatial pattern of clouds of various types, a model that gets the "right" current global temperature with the wrong pattern of clouds must have errors in its radiation and/or heat transfer parameterizations. In addition, the manner in which future climate scenarios achieve amplification of the direct radiative effect of increased greenhouse gases (the assumed positive feedback) is also not likely to be correct if the 3D pattern of simulated clouds is as far off as shown in this study. What is more, the pattern of clouds also reflects convective processes that distribute heat and water vapor in the atmosphere; and the results of Zhang et al. point to deficiencies in the handling of this aspect of atmospheric dynamics as well.

The results of this study thus suggest that climate modelers' claims of physical realism in their models are not supported by detailed comparisons with the real world, and that the basic radiative physics they employ, as parameterized at the grid scale, is probably faulty.

Archived 26 August 2010