A Land Cover Dataset Based on Chinese Vegetation Data and Its Impact on Land Surface Simulations

The authors develop a new land cover dataset (CLCV) based on the 1:1000000 Vegetation Atlas of China, the AVHRR (Advanced Very High Resolution Radiometer) Continuous Fields Tree Cover of UMD (University of Maryland), and the precipitation and temperature data of 753 weather stations in China, and investigate its effects on the energy and water balance over continental China. Compared to the MODIS data, the CLCV data have a decrease of 14.5% in bare soil fraction, which is realized through increased tree, shrub, grass, crop, glacier, lake, and wet land at 3.3%, 4.8%, 4.4%, 0.3%, 0.4%, 0.8%, and 0.6%, respectively. Compared to the statistic data and land use data, the CLCV data is much closer to them than the MODIS data. The simulation results show that the simulated evapotranspiration increases about 7.7 mm/a, and the simulated surface albedo, heat flux, and runoff decrease about 0.7%, 0.3 W/m2, and 7.6 mm/a, respectively; compared to the MODIS albedo data and the GRDC runoff data, the simulated surface albedo and runoff by the CLM with CLCV data get much closer to the observed data than that with the MODIS data.