A Prognostic Cloud Water Parameterization for Global Climate Models

Anthony D. Del Genio NASA Goddard Institute for Space Studies, New York, New York

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Mao-Sung Yao Science Systems and Applications, Inc., Institute for Space Studies, New York, New York

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William Kovari Science Systems and Applications, Inc., Institute for Space Studies, New York, New York

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Kenneth K-W. Lo Science Systems and Applications, Inc., Institute for Space Studies, New York, New York

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Abstract

An efficient new prognostic cloud water parameterization designed for use in global climate models is described. The scheme allows for life cycle effects in stratiform clouds and permits cloud optical properties to be determined interactively. The parameterization contains representations of all important microphysical processes, including autoconversion, accretion, Bergeron–Findeisen diffusional growth, and cloud/rain water evaporation. Small-scale dynamical processes, including detrainment of convective condensate, cloud-top entrainment instability, and stability-dependent cloud physical thickness variations, are also taken into account. Cloud optical thickness is calculated from the predicted liquid/ice water path and a variable droplet effective radius estimated by assuming constant droplet number concentration. Microphysical and radiative properties are assumed to be different for liquid and ice clouds, and for liquid clouds over land and ocean.

The parameterization is validated in several simulations using the Goddard Institute for Space Studies (GISS) general circulation model (GCM). Comparisons are made with a variety of datasets, including ERBE radiative fluxes and cloud forcing, ISCCP and surface-observed cloud properties, SSM/I liquid water path, and SAGE II thin cirrus cover. Validation is judged on the basis of the model's depiction of both the mean state; diurnal, seasonal, and interannual variability; and the temperature dependence of cloud properties. Relative to the diagnostic cloud scheme used in the previous GISS GCM, the prognostic parameterization strengthens the model's hydrologic cycle and general circulation, both directly and indirectly (via increased cumulus heating). Sea surface temperature (SST) perturbation experiments produce low climate sensitivity and slightly negative cloud feedback for globally uniform SST changes, but high sensitivity and positive cloud feedback when tropical Pacific SST gradients weaken with warming. Changes in the extent and optical thickness of tropical cumulus anvils appear to be the primary factor determining the sensitivity. This suggests that correct simulations of upward transport of convective condensate and of Walker circulation changes are of the highest priority for a realistic estimate of cloud feedback in actual greenhouse gas increase scenarios.

Abstract

An efficient new prognostic cloud water parameterization designed for use in global climate models is described. The scheme allows for life cycle effects in stratiform clouds and permits cloud optical properties to be determined interactively. The parameterization contains representations of all important microphysical processes, including autoconversion, accretion, Bergeron–Findeisen diffusional growth, and cloud/rain water evaporation. Small-scale dynamical processes, including detrainment of convective condensate, cloud-top entrainment instability, and stability-dependent cloud physical thickness variations, are also taken into account. Cloud optical thickness is calculated from the predicted liquid/ice water path and a variable droplet effective radius estimated by assuming constant droplet number concentration. Microphysical and radiative properties are assumed to be different for liquid and ice clouds, and for liquid clouds over land and ocean.

The parameterization is validated in several simulations using the Goddard Institute for Space Studies (GISS) general circulation model (GCM). Comparisons are made with a variety of datasets, including ERBE radiative fluxes and cloud forcing, ISCCP and surface-observed cloud properties, SSM/I liquid water path, and SAGE II thin cirrus cover. Validation is judged on the basis of the model's depiction of both the mean state; diurnal, seasonal, and interannual variability; and the temperature dependence of cloud properties. Relative to the diagnostic cloud scheme used in the previous GISS GCM, the prognostic parameterization strengthens the model's hydrologic cycle and general circulation, both directly and indirectly (via increased cumulus heating). Sea surface temperature (SST) perturbation experiments produce low climate sensitivity and slightly negative cloud feedback for globally uniform SST changes, but high sensitivity and positive cloud feedback when tropical Pacific SST gradients weaken with warming. Changes in the extent and optical thickness of tropical cumulus anvils appear to be the primary factor determining the sensitivity. This suggests that correct simulations of upward transport of convective condensate and of Walker circulation changes are of the highest priority for a realistic estimate of cloud feedback in actual greenhouse gas increase scenarios.

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