EVALUATION OF STATISTICALLY BASED CLOUDINESS PARAMETERIZATIONS USED IN CLIMATE MODELS

Existing cloudiness parameterizations based on specified probability d istribution functions (PDFs) and large-scale relative humidity (RH) in climate models are evaluated with data produced from explicit simulat ions of observed tropical cloud systems and subtropical stratocumuli. PDF-based parameterizations were originally intended for use in cloud- resolving models, where fractional cloudiness is only associated with turbulence-scale motion. It is demonstrated with simulated data that m ost PDF-based parameterizations are not adequate for predicting fracti onal cloudiness in climate models because their performance is depende nt upon the cloud regimes. Modifications to some PDF-based formulation s are suggested especially with regard to the inclusion of skewness of conservative variables. The skewness factors are found to be highly d ependent upon which scales of motion coexist within a grid cell. RH-ba sed parameterizations are not readily supported due to a wide range of variations of clear-region averaged RHs with height and the grid size of climate models, as well as their wide range of-variations at a giv en height.