Computationally Efficient Approximations to Stratiform Cloud Microphysics Parameterization

Abstract

Bulk cloud microphysics parameterizations typically employ time steps of a few tens of seconds. Although the computational burden of these parameterizations is acceptable for the 1-day mesoscale cloud simulations for which they were designed, the time steps are unacceptably short for direct application of them parameterizations to global-climate simulation. To increase the computational efficiency of bulk cloud microphysics parameterizations, we introduce two approximations that are appropriate for stratiform clouds. By diagnosing rather than predicting rain and snow concentrations and by assuming instantaneous melting of snow, we have found that the permissible time step is increased tenfold (to 2?6 min) with little loss in accuracy for vertical motions and time scales characteristic of those resolved by general circulation models (GCMs). Such time steps are sufficiently long to permit application of bulk cloud microphysical parameterizations to GCMs for multiyear global simulations. However, we also find that the vertical resolution must be considerably finer (100?200 m) than that currently employed in GCMs.