Are Climate Models Sensitive to the Microphysics of Clouds?

Parameterization transplant experiments with general circulation models (GCMs) demonstrate that details of cloud-radiation interactions can have large potential effects on the simulated climate. However, in order to determine which aspects of sub-grid physics are important and which parameterizations are most realistic, detailed comparisons with observations are essential. One useful diagnostic tool for making such comparisons is the single-column model (SCM), which consists of one isolated column of an atmospheric GCM. When an SCM is forced with observed horizontal advection terms, the parameterizations within the SCM produce time-dependent vertical profiles of fields which can be compared directly with measurements. In the case of cloud microphysical schemes, these fields include cloud altitude, cloud amount, liquid and ice content, particle size spectra, and radiative fluxes at the surface and the top of the atmosphere. Comparisons with data from the Atmospheric Radiation Measurement (ARM) Program show conclusively that prognostic cloud algorithms with detailed microphysics are far more realistic than simpler diagnostic approaches. These results also demonstrate the critical need for more and better in situ observations of cloud microphysical variables.