Cloud-Resolving Model Simulation and Mosaic Treatment of Subgrid Cloud-Radiation Interaction

Improving the representation of cloud-radiation interaction is a major challenge for the global climate simulation. The development of cloud-resolving models (CRMs) and the extensive Atmospheric Radiation Measurements (ARMs) provide a unique opportunity for shading some lights on this problem. Current general circulation models (GCMs) predict cloud cover fractions and hydrometeor concentrations only in individual model layers, where clouds are assumed to be horizontally homogeneous in a coarse grid. They do not explicitly specify geometric associations or optical variations. Subsequently, clouds within a GCM grid are represented as a single effective volume that impacts radiation using various overlap assumptions (Liang and Wang 1997). On the other hand, the CRMs explicitly resolve convection and mesoscale organization, where cloud microphysical processes and cloud-radiation interactions directly respond to the cloud-scale dynamics (Grabowski et al. 1996, Wu et al. 1999, Wu and Moncrieff 2001). In particular, the fine spatial resolution allows the CRM to more realistically represent the detailed structure of cloud systems, including cloud geometric and radiative properties. The CRM simulations in combination with the ARM measurements thus provide comprehensive datasets, based on which a more realistic GCM parameterization of sub-grid cloud-radiation interactions can be developed.