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Evaluation of Statistically Based Cloudiness Parameterizations Used in Climate Models

Kuan-Man XuDepartment of atmospheric Science, Colorado State University, Fort Collins, Colorado

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David A. RandallDepartment of atmospheric Science, Colorado State University, Fort Collins, Colorado

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Abstract

Existing cloudiness parameterizations based on specified probability distribution functions (PDFs) and large-scale relative humidity (RH) in climate-models are evaluated with data produced from explicit simulations 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 most PDF-based parameterizations are not adequate for predicting fractional cloudiness in climate models because their performance is dependent upon the cloud regimes. Modifications to some PDF-based formulations are suggested, especially with regard to the inclusion of skewness of conservative variables. The skewness factors are found to be highly dependent upon which scales of motion coexist within a grid cell. RH-based 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 given height.

Abstract

Existing cloudiness parameterizations based on specified probability distribution functions (PDFs) and large-scale relative humidity (RH) in climate-models are evaluated with data produced from explicit simulations 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 most PDF-based parameterizations are not adequate for predicting fractional cloudiness in climate models because their performance is dependent upon the cloud regimes. Modifications to some PDF-based formulations are suggested, especially with regard to the inclusion of skewness of conservative variables. The skewness factors are found to be highly dependent upon which scales of motion coexist within a grid cell. RH-based 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 given height.

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