A reasonable representation of orographic anisotropy in earth system models is vital for improving weather and climate modeling. In this study, we implemented the orographic drag scheme, including 3-D orographic anisotropy (3D-AFD), into the Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM 2.0). Three groups of simulations named sensitivity run, medium-range forecast, and seasonal forecast respectively were conducted using the updated CAS-ESM model together with the original 2-D isotropic scheme (2-D) and the 3-D orographic anisotropy for the eight-direction scheme (3D-8x) to validate its performance. Sensitivity runs indicated that the simulated drag using the original 2-D scheme did not change with the wind directions, while the simulated drag using the updated 3D-AFD showed a smoother transition than that using 3D-8x. The 3D-AFD and 3D-8x had also about 80% larger drag and smaller wind speed of 1m/s than that of the 2-D scheme. Enhanced drag in the medium range and seasonal forecast using the updated CAS-ESM both alleviated the bias of the overestimated wind speed and the cold bias over mountain regions in the 2-D scheme. This was more apparent in winter (0.4-0.5 m/s and ~1K) than that in summer (0.1 m/s and ~0.1K) for the northern hemisphere region, such as the Tibetan Plateau. The vertical wind profile was also improved in the seasonal forecast. The results suggested that a reasonable representation of the orographic anisotropy was important in climate modeling, and the updated model of CAS-ESM with 3D-AFD alleviated the bias of the mountain wind.

The land surface model of the Chinese Academy of Sciences (CAS-LSM), which includes lateral flow, water use, nitrogen discharge and river transport, soil freeze thaw front dynamics, and urban planning, was implemented into the Flexible Global Ocean-Atmosphere-Land System model grid-point version 3 (CAS-FGOALS-g3). Simulations were conducted using the land–atmosphere component setup of CAS-FGOALS-g3. The simulations showed reasonable distributions of the land surface variables when compared against observations (including reanalysis, merged data, remote sensing, etc). In terms of the new capabilities, it was shown that considering the groundwater lateral flow caused a deepening of the water table depth of around 25–50 mm in North India, central USA, and Sahel. Including the anthropogenic groundwater use also led to increased latent heat fluxes of about 20 W∙m-2 in the aforementioned three areas. Inclusion of the soil freeze thaw front (FTF) dynamics enabled seasonal-variation simulations of the freeze and thaw processes, and the FTF-derived permafrost extent was comparable to that seen in the observations. The simulations conducted using the riverine nitrogen transport and human activity schemes showed that major rivers around the globe, including western Europe, eastern China, and the Midwest of the USA experienced annual dissolved inorganic nitrogen (DIN) rates of 25–50 Gg∙N∙yr-1, which were accompanied by surface water regulation DIN losses of around 28 mg∙N∙m-2∙yr-1 and DIN retention of 200–500 mg∙N∙m-2∙yr-1. The results suggest that the model is a useful tool for studying the effects of land-surface processes on the global climate, especially those influenced by human interventions.