Abstract
East Asia summer monsoon (EASM) simulations are conducted to evaluate three schemes which determine cloud properties used in the radiation calculation of the State University of New York at Albany (SUNYA) regional climate model (RCM). Scheme-Ⅰ uses diagnostic cloud cover and cloud water while Scheme-Ⅱ uses prognostic cloud water along with overcast sky; both schemes are commonly employed in RCMs. In Scheme-Ⅲ, cloud cover is determined by diagnostic formula, but the cloud water is calculated by the weighted means of its diagnosed and prognosed values. Therefore, Scheme-Ⅲ considers the subgrid-scale clouds as Scheme-Ⅰ and maintains consistent cloud properties in radiation calculation and microphysical processes as Scheme-Ⅱ. Cloud radiative forcing (CRF) which provides a quantification of the cloud-radiation-climate interaction is adopted to compare the three schemes in simulating the 1991 EASM, characterized by large amounts of cloud and persistent rainfall over Yangtze-Huai River valley. With these three cloud schemes, the SUNYA RCM is capable of simulating the intra-seasonal variations of observed cloud cover and longwave CRF. The transition of shortwave CRF is not properly simulated due to the constantly presented low-level clouds. Mostly the magnitude of CRF is overestimated by 13-22 W m^(-2) for shortwave CRF and by 12-16 W m^(-2) for longwave CRF. It is also found that the surface temperature biases are highly correlated (with correlation coefficient greater than 0.8) to the shortwave CRF biases. Therefore, Scheme-Ⅲ resulting in less low-level cloud water and the least shortwave CRF biases simulates surface temperatures in better agreement with observations. Analyses of surface energy balance components indicate that the CRF changes dominate the surface temperature responses and the consequent surface latent heat and sensible heat flux feedbacks significantly offset them. Finally, comparisons of the diurnal variations of simulated cloud water among the three schemes show that Scheme-Ⅲ provides consistency between cloud microphysics and radiation.
Highlights
Cloud parameterization determining the heating/cooling of the atmosphere through latent heat release and cloud radiative forcing (CRF) is an important element in climate simulations
The cloud formation/dissipation depends on cloud microphysics processes in response to atmospheric thermodynamic states while the CRF depends on number density, size, optical properties, temperature, and vertical association of clouds
Because the cloud microphysical processes in prognostic equations directly respond to the thermodynamic state, using prognostic clouds in all physical processes is an ideal approach to treat cloud-climate interaction
Summary
Cloud parameterization determining the heating/cooling of the atmosphere through latent heat release and cloud radiative forcing (CRF) is an important element in climate simulations. To minimize the aforementioned drawbacks of merely using diagnostic and prognostic clouds alone, a cloud hybrid scheme is proposed and applied in a regional climate model (RCM) with horizontal resolution of 60 km. Both subgrid- and grid-scale clouds can be represented without remarkably modifying the microphysics of prognostic clouds. The hybrid scheme considers both the grid-scale and subgrid-scale clouds and has direct interaction and coupling between radiation and thermodynamics We evaluate these schemes by analyzing the CRF, surface temperatures, surface energy balance, and diurnal variations of the low-level clouds of simulations.
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