Based on historical runs,one of the core experiments of the fifth phase of the Coupled Model Intercomparison Project (CMIP5),the snow depth (SD) and snow cover fraction (SCF) simulated by two versions of the Flexible Global OceanAtmosphere-Land System (FGOALS) model,Grid-point Version 2 (g2) and Spectral Version 2 (s2),were validated against observational data.The results revealed that the spatial pattern of SD and SCF over the Northern Hemisphere (NH) are simulated well by both models,except over the Tibetan Plateau,with the average spatial correlation coefficient over all months being around 0.7 and 0.8 for SD and SCF,respectively.Although the onset of snow accumulation is captured wellby the two models in terms of the annual cycle of SD and SCF,g2 overestimates SD/SCF over most mid-and high-latitude areas of the NH.Analysis showed that g2 produces lower temperatures than s2 because it considers the indirect effects of aerosols in its atmospheric component,which is the primary driver for the SD/SCF difference between the two models.In addition,both models simulate the significant decreasing trend of SCF well over (30°-70°N) in winter during the period 1971-94.However,as g2 has a weak response to an increase in the concentration of CO2 and lower climate sensitivity,it presents weaker interannual variation compared to s2.
XIA KunWANG BinLI LijuanSHEN SiHUANG WenyuXU ShimingDONG LiLIU Li
Regional climate models often lack detailed description of ice sheet surface and, as a result, are limited in their capability to provide useful information for Antarctic climate research and field campaigns. In this study, an upgraded scheme of surface physics for Antarctic ice sheet(IST) is developed to improve the surface temperature simulations in Antarctica. Through stand-alone simulations, IST shows advantages over the Noah glacial module, a commonly utilized scheme in the widely used Weather Research and Forecasting(WRF) model. These improvements are mainly attributed to the incorporation of detailed snow physics and optimized surface layer parameterization, which results in better simulations of both the surface albedo in summer and the turbulent sensible heat flux in winter. When coupled with IST instead of Noah,WRF models show improved simulation of surface temperatures throughout the year. The bias and root-meansquare-error of annual mean surface temperatures are reduced from 5.7 and 6.0 to 0.2 and 2.7 K.