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 SchemeIII provides consistency between cloud microphysics and radiation.