HR: 09:15h
AN: H31I-06    [Abstracts]
TI: The NASA Earth Observing System (EOS) Evapotranspiration Product: the New MOD16
AU: * Wood, E F
EM: efwood@princeton.edu
AF: Princeton University, Department of Civil and Environmental Engineering, Princeton, NJ 08540, United States
AU: Vinukollu, R K
EM: rvinukol@princeton.edu
AF: Princeton University, Department of Civil and Environmental Engineering, Princeton, NJ 08540, United States
AU: Ferguson, C
EM: cferguso@princeton.edu
AF: Princeton University, Department of Civil and Environmental Engineering, Princeton, NJ 08540, United States
AU: Pinker, R T
EM: pinker@atmos.umd.edu
AF: University of Maryland, CMPS-Atmospheric & Oceanic Science, College Park, MD 20742, United States
AU: Running, S W
EM: swr@ntsg.umt.edu
AF: University of Montana, College of Forestry and Conservation, Missoula, MT 59812, United States
AU: Wang, H
EM: hmwang@umd.edu
AF: University of Maryland, CMPS-Atmospheric & Oceanic Science, College Park, MD 20742, United States
AB: A multi-sensor Earth Observing System evapotranspiration (ET) algorithm and product, referred to as MOD16, will be presented here. The original MOD16 algorithms were based on remote sensing data solely from the Moderate Resolution Imaging Spectroradiometer (MODIS) and evolved first from an empirical relationship between MODIS vegetation surface temperature and ET to a Penman-Monteith type approach driven by the NASA GMAO global model output and MODIS vegetation parameters. An alternative MOD16 algorithm is based on the Surface Energy Budget System (SEBS) scheme of Su (2002) followed. This latter algorithm depends on a surface temperature – air temperature gradient as a core parameterization of the surface heat flux. The low temporal resolution of the MODIS land surface temperature (MOD11) product, coupled with the lack of a consistent MODIS-based surface radiation product made the use of advanced algorithms using only MODIS data to generate a MOD16 product quite challenging. In this study, we use a blended approach that utilizes both SEBS and the Penman-Monteith (PM) ET algorithms (depending on available information) to generate the "NASA Earth Observing System (EOS) Evapotranspiration Product". The algorithms use multi-sensor datasets from AQUA and TERRA that include CERES coarse resolution (20 km) surface radiation, AIRS surface meteorology and surface temperature, and MODIS vegetation and land surface temperature, when available. To evaluate the impact of using the CERES coarse resolution surface radiation, a high spatial resolution MODIS-based radiation product has been developed by the University of Maryland. The extensively validated SEBS algorithm serves as the primary ET estimator. When SEBS required inputs (primarily surface temperature) are not available, the secondary PM approach is implemented. To assure consistency and accuracy of the mixed-model ET output, the PM approach is calibrated to best-fit the climatology of the SEBS retrievals. This combined approach is used to generate daily ET estimates over North America for 2003. Regional and site-scale comparisons with observations, including the point-scale FLUXNET sites, demonstrate the potential of this approach to monitor land surface ET on a global basis at daily time scale.
DE: 1818 Evapotranspiration
DE: 1836 Hydrological cycles and budgets (1218, 1655)
DE: 1855 Remote sensing (1640)
SC: Hydrology [H]
MN: 2007 Fall Meeting