HR: 14:25h
AN: G23A-04 INVITED     [Abstracts]
TI: Synthesis of GRACE Based Hydrology With Other Data Products and Land Surface Models
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
AB: Time series of terrestrial water storage variations are now being derived from GRACE satellite gravity observations. These could be extremely valuable for water cycle research, water resources and natural hazards, and other applications, because GRACE provides information on water stored at depths not resolvable using space-borne radar or radiometers. However, interpreting and utilizing GRACE data is challenging to hydrologists due to three issues: 1) their spatial and temporal resolutions are low relative to other observations, 2) there is a tradeoff between resolution and accuracy for which optimization varies based on the application and region of interest, and 3) auxiliary information is required in order to disaggregate the terrestrial water storage variations into changes in ground water, soil moisture, snow, surface water, and vegetation mass. Addressing those issues through the synthesis of GRACE data with other hydrological products and tools will be crucial for maximizing the value of these data for terrestrial hydrological research and applications. Land surface models (LSMs) simulate the redistribution of water and energy incident on the land surface, but their accuracy is limited by the quality of the input data used to parameterize and force the models, the model developers' understanding of the physics involved, and the simplifications necessary to depict the Earth system economically. Remote sensing observations are generally preferable, but they have their own problems, including data gaps, errors from multiple sources, and low resolutions. The advantages of each can be harnessed by data assimilation, which integrates discontinuous and imperfect observations with our knowledge of physical processes, as represented in LSMs. Models fill observational gaps, provide quality control, and enable data from disparate measurement systems to be merged, while the observations anchor the results in reality. Hence data assimilation may be the best hope for reliable and consistent horizontal, vertical, and temporal disaggregation of GRACE derived terrestrial water storage variations.
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: Geodesy [G]
MN: Fall Meeting 2005