A Statistically-Based Low-Level Cloud Scheme and Its Tentative Application in a General Circulation Model

In this study, a statistical cloud scheme is first introduced and coupled with a first-order turbulence scheme with second-order turbulence moments parameterized by the timescale of the turbulence dissipation and the vertical turbulent diffusion coefficient. Then the ability of the scheme to simulate cloud fraction at different relative humidity, vertical temperature profile, and the timescale of the turbulent dissipation is examined by numerical simulation. It is found that the simulated cloud fraction is sensitive to the parameter used in the statistical cloud scheme and the timescale of the turbulent dissipation. Based on the analyses, the introduced statistical cloud scheme is modified. By combining the modified statistical cloud scheme with a boundary layer cumulus scheme, a new statistically-based low-level cloud scheme is proposed and tentatively applied in NCAR (National Center for Atmospheric Research) CCM3 (Community Climate Model version 3). It is found that the simulation of low-level cloud fraction is markedly improved and the centers with maximum low-level cloud fractions are well simulated in the cold oceans off the western coasts with the statistically-based low-level cloud scheme applied in CCM3. It suggests that the new statistically-based low-level cloud scheme has a great potential in the general circulation model for improving the low-level cloud parameterization.