Based on MODIS NDVI, linear and nonlinear algorithms (hereafter referred as GI and CR algorithms respectively) are used to calculate vegetation fraction over China, and these data are used in Weather Research and Forecasting Model (WRF). The effect of different vegetation fraction data derived from GI and CR algorithms on WRF's simulation in July 2006 over China is investigated. The results show that large deviation of vegetation fraction calculated by GI and CR appears in semi-arid regions, and corresponding, WRF simulation has significant difference in these regions. In arid and humid regions, small deviation is found relatively, and not significant difference for WRF simulation. Utilizing vegetation fraction derived from GI algorithm, WRF have less biases in near surface average and maximum temperature compared with observations, while less biases in minimum temperature and good performance of hot weather for CR. Using vegetation fraction data derived from CR algorithm, WRF can better describe average, daily variation and spatial pattern of precipitation. There are some differences of WRF's performance in different regions between two vegetation fraction algorithms. Overall, the use of CR produces better performance on temperature and precipitation.
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