Based on the 1∶1 000 000 Vegetation Atlas and 1∶6 000 000 Vegetation Regionalization Map of China, a high resolution land cover dataset (VEG) with the CLM classification was developed, which can be used in CLM and RegCM4. Compared to the default land cover data (ORG), the VEG data produced a decreased coverage of bare ground and crop, but an increased coverage of shrub. With higher resolution, this new data can represent the local characteristics of land cover more accurately. A 3-yr continuous integral simulation was used to study the impact of land cover data on surface air temperature, precipitation, and surface energy budget. The results show that the simulation with the VEG data shows a general good performance in describing surface air temperature and precipitation in winter. Most of these improvements are located in South China, which can reduce the dry and cold biases. Using the VEG data not only changes the surface albedo and roughness but also the cloud fraction, and then consequently makes the surface energy budget change. Regional climate change differs by region, as does its mechanism. The temperature change in Tibet Plateau is the result of increasing turbulence flux and downward net long-wave radiation. The increase in surface roughness will enhance surface drag, leading to the increased turbulent heat exchange, and the cloud fraction variations will cause increased thermal warming. However, in Central and South China, the main factor affecting surface air temperature is surface short-wave radiation. It is hopeful that this high resolution land cover dataset will be widely applied in the CLM simulations over China.