The improvements and validation of several parameterization schemes in the second version of the Beijing Climate Center Atmosphere–Vegetation Interaction Model(BCC_AVIM2.0) are introduced in this study. The main upda...The improvements and validation of several parameterization schemes in the second version of the Beijing Climate Center Atmosphere–Vegetation Interaction Model(BCC_AVIM2.0) are introduced in this study. The main updates include a replacement of the water-only lake module by the common land model lake module(Co LM-lake) with a more realistic snow–ice–water–soil framework, a parameterization scheme for rice paddies added in the vegetation module, renewed parameterizations of snow cover fraction and snow surface albedo to accommodate the varied snow aging effect during different stages of a snow season, a revised parameterization to calculate the threshold temperature to initiate freeze(thaw) of soil water(ice) rather than being fixed at 0°C in BCC_AVIM1.0, a prognostic phenology scheme for vegetation growth instead of empirically prescribed dates for leaf onset/fall, and a renewed scheme to depict solar radiation transfer through the vegetation canopy. The above updates have been implemented in BCC_AVIM2.0 to serve as the land component of the BCC Climate System Model(BCC_CSM). Preliminary results of BCC_AVIM in the ongoing Land Surface, Snow, and Soil Moisture Model Intercomparison Project(LS3 MIP) of the Coupled Model Intercomparison Project Phase 6(CMIP6) show that the overall performance of BCC_AVIM2.0 is better than that of BCC_AVIM1.0 in the simulation of surface energy budgets at the seasonal timescale. Comparing the simulations of annual global land average before and after the updates in BCC_AVIM2.0 reveals that the bias of net surface radiation is reduced from-12.0 to-11.7 W m-2 and the root mean square error(RMSE) is reduced from 20.6 to 19.0 W m-2;the bias and RMSE of latent heat flux are reduced from 2.3 to-0.1 W m-2 and from 15.4 to14.3 W m-2, respectively;the bias of sensible heat flux is increased from 2.5 to 5.1 W m-2 but the RMSE is reduced from 18.4 to 17.0 W m-2.展开更多
基金Supported by the National Key Research and Development Program of China(2017YFA0604300,2016YFA0602100,and2016YFA0602602)National Natural Science Foundation of China(41275075 and 91437219)
文摘The improvements and validation of several parameterization schemes in the second version of the Beijing Climate Center Atmosphere–Vegetation Interaction Model(BCC_AVIM2.0) are introduced in this study. The main updates include a replacement of the water-only lake module by the common land model lake module(Co LM-lake) with a more realistic snow–ice–water–soil framework, a parameterization scheme for rice paddies added in the vegetation module, renewed parameterizations of snow cover fraction and snow surface albedo to accommodate the varied snow aging effect during different stages of a snow season, a revised parameterization to calculate the threshold temperature to initiate freeze(thaw) of soil water(ice) rather than being fixed at 0°C in BCC_AVIM1.0, a prognostic phenology scheme for vegetation growth instead of empirically prescribed dates for leaf onset/fall, and a renewed scheme to depict solar radiation transfer through the vegetation canopy. The above updates have been implemented in BCC_AVIM2.0 to serve as the land component of the BCC Climate System Model(BCC_CSM). Preliminary results of BCC_AVIM in the ongoing Land Surface, Snow, and Soil Moisture Model Intercomparison Project(LS3 MIP) of the Coupled Model Intercomparison Project Phase 6(CMIP6) show that the overall performance of BCC_AVIM2.0 is better than that of BCC_AVIM1.0 in the simulation of surface energy budgets at the seasonal timescale. Comparing the simulations of annual global land average before and after the updates in BCC_AVIM2.0 reveals that the bias of net surface radiation is reduced from-12.0 to-11.7 W m-2 and the root mean square error(RMSE) is reduced from 20.6 to 19.0 W m-2;the bias and RMSE of latent heat flux are reduced from 2.3 to-0.1 W m-2 and from 15.4 to14.3 W m-2, respectively;the bias of sensible heat flux is increased from 2.5 to 5.1 W m-2 but the RMSE is reduced from 18.4 to 17.0 W m-2.
