HR: 10:50h
AN: H32A-03 INVITED     [Abstracts]
TI: Enhancement of Satellite Observations of the Land Surface Via Data Assimilation
AU: * Rodell, M
EM: Matthew.Rodell@nasa.gov
AF: NASA Goddard Space Flight Center, Hydrological Sciences Branch Code 614.3, Greenbelt, MD 20771, United States
AU: Zaitchik, B
EM: bzaitchik@hsb.gsfc.nasa.gov
AF: NASA Goddard Space Flight Center, Hydrological Sciences Branch Code 614.3, Greenbelt, MD 20771, United States
AU: Zaitchik, B
EM: bzaitchik@hsb.gsfc.nasa.gov
AF: Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20742, United States
AU: Kato, H
EM: hkato@hsb.gsfc.nasa.gov
AF: NASA Goddard Space Flight Center, Hydrological Sciences Branch Code 614.3, Greenbelt, MD 20771, United States
AU: Kato, H
EM: hkato@hsb.gsfc.nasa.gov
AF: Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20742, United States
AU: Reichle, R
EM: reichle@gmao.gsfc.nasa.gov
AF: NASA Goddard Space Flight Center, Hydrological Sciences Branch Code 614.3, Greenbelt, MD 20771, United States
AU: Reichle, R
EM: reichle@gmao.gsfc.nasa.gov
AF: Goddard Earth Science and Technology Center, University of Maryland, Baltimore County, Baltimore, MD 21228, United States
AU: van der Velde, R
EM: velde@itc.nl
AF: International Institute for Geo-Information Science and Earth Observation (ITC), Hengelosestraat 99 P.O. Box 6 7500 AA Enschede, Netherlands
AB: Satellite based observation of land surface conditions has transformed the field of hydrology, enabling water cycle studies which span local to global scales. However, such studies are limited by errors in the retrieval algorithms, data gaps, and sometimes low resolutions. Land surface models (LSMs) simulate the redistribution of water and energy incident on the land surface based on our understanding of physical processes, but with limited accuracy. The advantages of each can be harnessed by data assimilation. Here we present examples of how data assimilation can be used for spatial, temporal, and vertical interpolation and downscaling of observations from GRACE, MODIS, and other sources, thus enhancing their value for water resources applications and hydroclimatological investigations.
DE: 1217 Time variable gravity (7223, 7230)
DE: 1836 Hydrological cycles and budgets (1218, 1655)
DE: 1847 Modeling
DE: 1855 Remote sensing (1640)
DE: 3315 Data assimilation
SC: Hydrology [H]
MN: 2007 Joint Assembly