Predictions of Saturation Ratio for Cloud Microphysical Models

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  • 1 Center for Clouds, Chemistry and Climate, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California
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Abstract

The saturation development equation is solved analytically to give a solution that is more general than the existing analytical solution. This analytical solution provides accurate predictions of the saturation ratio and allows the use of relatively large time steps for the simulation of condensation processes. A statistical method that is nonanalytical in nature is also introduced for the prediction of saturation ratio. The performances of these prediction methods are compared for the simulation of drop growth in clouds under idealized situations. It is shown that the more general analytical solution provides improved predictions of saturation ratio under subsaturated conditions. Furthermore, the statistical method is shown to be more efficient and accurate than the analytical methods.

Abstract

The saturation development equation is solved analytically to give a solution that is more general than the existing analytical solution. This analytical solution provides accurate predictions of the saturation ratio and allows the use of relatively large time steps for the simulation of condensation processes. A statistical method that is nonanalytical in nature is also introduced for the prediction of saturation ratio. The performances of these prediction methods are compared for the simulation of drop growth in clouds under idealized situations. It is shown that the more general analytical solution provides improved predictions of saturation ratio under subsaturated conditions. Furthermore, the statistical method is shown to be more efficient and accurate than the analytical methods.

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