HR: 11:00h
AN: H32B-03    [Abstracts]
TI: Potential of Satellite-Based Models for Land Surface Evapotranspiration Estimation
AU: * Jiang, L
EM: Le.Jiang@noaa.gov
AF: IMSG at NOAA/NESDIS, NOAA Science Center, 5200 Auth Rd., Rm 810, Camp Springs, MD 20746 United States
AU: Islam, S
EM: Shafiqul.Islam@tufts.edu
AF: Department of Civil and Environmental Engineering, 113 Anderson Hall, 200 College Ave., Tufts University, Medford, MA 02155
AU: Bisht, G
EM: gbisht@mit.edu
AF: Massachussetts Institute of Technology, Ralph M. Parsons Laboratory, 48-217-33, Cambridge, MA 02139 United States
AU: Venturini, V
EM: venturva@email.uc.edu
AF: Department of Civil and Environmental Engineering, P.O. Box 210071, University of Cincinnati, Cincinnati, OH 45221 United States
AU: Carlson, T N
EM: tnc@essc.psu.edu
AF: Department of Meteorology, 619 Walker Building, University Park, PA 16802
AU: Guo, W
EM: Wei.Guo@noaa.gov
AF: IMSG at NOAA/NESDIS, NOAA Science Center, 5200 Auth Rd., Rm 810, Camp Springs, MD 20746 United States
AU: Tarpley, D
EM: Dan.Tarpley@noaa.gov
AF: NOAA/NESDIS/ORA, 5200 Auth Rd., Rm 711, Camp Springs, MD 20746 United States
AB: Use of satellite remote sensing data for the estimation of surface evapotranspiration (ET) is emerging as a promising approach with a range of application potentials. Unlike traditional point-based approaches, some of these satellite-based approaches have been shown to have bounded error. This is a significant advantage of such ET estimation approaches compared to ground-based or hybrid (i.e. combining ground and remote sensing data) approaches, particularly over large heterogeneous domain where representation of key distributed parameters from ground-based observations are questionable. For clear days, main components relevant to surface ET estimation such as evaporative fraction (EF) and net radiation (Rn) can be derived using data from AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) sensors. Use of temporal stability of EF and a mathematically convenient and physically realistic, at least for clear sky days, diurnal model for Rn may allow us to get a reasonably accurate estimates of daily ET over large heterogeneous areas. Extension of these results for cloudy days and related challenges will be discussed with particular examples from South Florida and Southern Great Plains using data from MODIS and AVHRR.
DE: 1640 Remote sensing
DE: 1655 Water cycles (1836)
DE: 1800 HYDROLOGY
DE: 1818 Evapotranspiration
DE: 1842 Irrigation
SC: Hydrology [H]
MN: 2005 Joint Assembly