| The objective of this research is to evaluate the schemes for calculating the cloud-radiative parameters used in Regional Climate Models (ReCM) for their further improvement. To facilitate the evaluation, the cloud radiative forcing (CRF), defined as the difference in the radiative fluxes between the cases with and without clouds, is adopted to analyze the SUNYA-ReCM simulated East Asia summer monsoon (EASM) focusing on the 1991 severe flood event over Yangtze-Huai river valley.; Three schemes are considered: Scheme-I uses diagnostic cloud water; Scheme-II uses prognostic cloud water; and Scheme-III is a hybrid scheme combining Scheme-I and -II. In general, the model simulated well the spatial and temporal patterns of CRF over the Eastern China, although biases exist in its magnitude. For example, for the domain and May-June-July averages, the model overestimated the cooling (compared to the observed value of −75.0 W/m2) by 5.7, 17.3, and 28.0 W/m2 for Scheme-I, -II, and -III, respectively. For all three schemes, the CRF biases are highly correlated to the surface temperature biases, thus suggesting that improving the CRF is most likely to improve the surface temperature. The role of CRF in EASM is studied by comparing the results of different simulations with and without CRF. The results indicate different circulation responses: CRF weakens the circulation by cooling the atmosphere over the land surface due to the surface heat flux reductions (∼90 to 120 W/m2), which are correspond to over 90% surface radiative flux reductions; in contrast, its direct warming (∼16 to 26 W/m2) on the atmosphere provides the secondary effects in strengthening the circulation.; Because Scheme-III is physically more comprehensive but results in larger biases, the necessity of modifying the cloud-radiative parameterizations is discussed and tested. Scheme-III is thus revised with three modifications, including lowering the threshold of activating the cloud water autoconversion, coupling the cloud droplet effective radius to the prognostic cloud water, and using the diagnostic cloud cover to adjust the prognostic cloud water. The revised Scheme-III, possessing larger cloud variability and more interactive cloud-radiative interaction, with all the modifications significantly reduces the CRF biases close to that of the empirically based Scheme-I. |
