摘要
Because of China's large size, satellite observations are necessary for estimation of the land surface latent heat flux (LE). We describe here a satellite-driven Priestley-Taylor (PT)-based algorithm constrained by the Normalized Difference Vegetation Index (NDVI) and Apparent Thermal Inertia (ATI) derived from temperature change over time. We compare to the satellite-driven PT-based approach, PT-JPL, and validate both models using data collected from 16 eddy covariance flux towers in China. Like PT-JPL, our proposed algorithm avoids the computational complexities of aerodynamic resistance parameters. We run the algorithms with monthly Moderate Resolution Imaging Spectroradiometer (MODIS) products (0.05¡ã resolution), including albedo, Land Surface Temperature (LST), surface emissivity, and NDVI; and, Insolation from the Japan Aerospace Exploration Agency (JAXA). We find good agreement between our estimates of monthly LE and field-measured LE, with respective Root Mean Square Error (RMSE) and bias differences of 12.5 W m?2 and ?6.4 W m?2. As compared with PT-JPL, our proposed algorithm has higher correlations with ground-measurements. Between 2001 and 2010, LE shows generally negative trends in most regions of China, though positive LE trends occur over 39 % of the region, primarily in Northeast, North and South China. Our results indicate that the variations of terrestrial LE are responding to large-scale droughts and afforestation caused by human activity with direct links to terrestrial energy exchange, both spatially and temporally.