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Sensitivity of the Simulated Climate to a Diagnostic Formulation for Cloud Liquid Water

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  • 1 National Center for Atmospheric Research,* Boulder, Colorado
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Abstract

The accurate treatment of clouds and their radiative properties is widely regarded to be among the most important problems facing global climate modeling. A number of the more serious systematic simulation biases in the NCAR Community Climate Model (CCM2) appear to be related to deficiencies in the treatment of cloud optical properties. In this paper, a simple diagnostic parameterization for cloud liquid water is presented. The sensitivity of the simulated climate to this alternative formulation, both in terms of mean climate metrics and measures of the climate system response, is illustrated. Resulting simulations show significant reductions in CCM2 systematic biases, particularly with respect to surface temperature, precipitation, and extratropical geopotential height-field anomalies. Many aspects of the simulated response to ENSO forcing are also substantially improved.

Corresponding author address: Dr. James J. Hack, NCAR/CGD, P.O. Box 3000, Boulder, CO 80307-3000.

Email: jhack@ncar.ucar.edu

Abstract

The accurate treatment of clouds and their radiative properties is widely regarded to be among the most important problems facing global climate modeling. A number of the more serious systematic simulation biases in the NCAR Community Climate Model (CCM2) appear to be related to deficiencies in the treatment of cloud optical properties. In this paper, a simple diagnostic parameterization for cloud liquid water is presented. The sensitivity of the simulated climate to this alternative formulation, both in terms of mean climate metrics and measures of the climate system response, is illustrated. Resulting simulations show significant reductions in CCM2 systematic biases, particularly with respect to surface temperature, precipitation, and extratropical geopotential height-field anomalies. Many aspects of the simulated response to ENSO forcing are also substantially improved.

Corresponding author address: Dr. James J. Hack, NCAR/CGD, P.O. Box 3000, Boulder, CO 80307-3000.

Email: jhack@ncar.ucar.edu

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