Estimation of Evaporative Fraction from a Combination of Day and Night Land Surface Temperatures and NDVI: A New Method to Determine the Priestly-Taylor Parameter
Kaicun
Wang, Institute of Atmospheric Physics, Chinese Academy of Sciences, kcwang@umd.edu
(Presenting)
Zhanqing
Li, Earth System Science Interdisciplinary Center (ESSIC) and Department of Atmospheric and Oceanic Science, University of Maryland, zli@atmos.umd.edu
M.
Cribb, Earth System Science Interdisciplinary Center (ESSIC) and Department of Atmospheric and Oceanic Science, University of Maryland, mcribb@essic.umd.edu
Satellite remote sensing is a promising technique to estimate global or regional evapotranspiration (ET) or evaporative fraction (EF) of the surface total net radiation budget. The current methods of estimating the ET (or EF) from the gradient between land surface temperature (LST) and near surface air temperature are very sensitive to the retrieval errors of LST and the interpolation errors of air temperature from the ground-based point measurements. Two types of methods have been proposed to reduce this sensitivity: the thermal inertia method and the LST- Normalized Difference Vegetation Index (NDVI) (LST-NDVI) spatial variation method. The former is based on the temporal difference between LST retrievals, and the latter uses the spatial information of LST. Another approach is proposed here that combines the advantages of the two types of methods and uses day-night LST difference- NDVI (delt LST-NDVI). Ground-based measurements collected by Energy Balance Bowen Ratio systems at the 11 enhanced facilities located at the Southern Great Plains of the United States from April 2001 to May 2005 were analyzed to identify parameterization of EF. delt LST-NDVI spatial variations from the Aqua and Terra MODerate-resolution Imaging Spectroradiometer (MODIS) global daily products, at 1 km resolution were used to estimate EF. Ground-based measurements taken during 16 days in 2004 were used to validate the MODIS EF retrievals. The EFs retrieved from the spatial variations of delt LST-NDVI show a distinct improvement over that retrieved from the LST-NDVI. The EF can be retrieved with a mean relative accuracy of about 17% with the proposed delt LST-NDVI spatial variations.