HR: 15:25h
AN: H43H-08    [Abstracts]
TI: Estimating Regional Evapotranspiration over the Red-Arkansas Basin Using Satellite and In-situ Data
AU: Su, H
EM: hongbosu@princeton.edu
AF: Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544
AU: McCabe, M
EM: mmccabe@princeton.edu
AF: Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544
AU: Wojcik, R
EM: rwojcik@princeton.edu
AF: Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544
AU: * Wood, E F
EM: efwood@princeton.edu
AF: Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544
AU: Pinker, R T
EM: pinker@atmos.umd.edu
AF: Department of Meteorology, University of Maryland, College Park, MD 20742
AB: Using space-borne remote sensing measurements for estimating surface evapotranspiration (ET) at regional to continental scales using algorithms based on micrometeorological approaches presents a number of challenges. The main challenges are obtaining continuous fields of surface temperature due to clouds, errors in transferring the required surface meteorology from in-situ stations to pixels with retrieved surface temperatures, scale mismatches between the resolution of the remotely sensed observations (insolation, vegetation characteristics, surface temperature) and the landscape variability, and aggregating instantaneous ET estimates spatially and temporally across large domains. In this study, the Surface Energy Balance System (SEBS) model is employed to estimate the terrestrial evapotranspiration across the 645,000 sq km Red-Arkansas Basin. The remotely sensed data is based on the MODIS sensor on NASA's Terra and Aqua platforms. The work will utilize some recent MODIS-based products, including a daily instantaneous surface albedo derived from MODIS narrowband reflectance and a high spatial resolution surface solar insolation. The work will explore a number of strategies for obtaining continuous spatial fields of ET, including using SEBS to predict the evaporative fraction over operational meteorological stations, which is then interpolated across the domain; interpolating surface temperature across the domain through data assimilation into a land surface model; and using simplified approaches for cloud-covered areas. The strategies explored in this presentation form a baseline for MODIS-based evapotranspiration estimation at regional to continental scales.
DE: 1818 Evapotranspiration
DE: 1855 Remote sensing (1640)
SC: Hydrology [H]
MN: Fall Meeting 2005