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United States Department of Agriculture

Agricultural Research Service


item Crow, Wade
item Entekhabi, Dara
item Reichle, Rolf
item Koster, Randal

Submitted to: Earth Observatory Systems
Publication Type: Literature review
Publication Acceptance Date: 1/30/2006
Publication Date: 4/11/2006
Citation: Crow, W.T., Entekahabi, D., Reichle, R., Koster, R., 2006. Multiple spaceborne water cycle observations would aid modeling. Earth Observing Systems (EOS). 87(15).

Interpretive Summary:

Technical Abstract: Land data assimilation systems (LDAS) are designed to provide continental-scale estimates of surface moisture and temperature states - and water and energy flux exchanges with the atmosphere - by propagating land surface models using observations of micrometeorological forcing data (e.g. surface precipitation, incoming radiation, winds, air temperature and humidity). When measurements of land system states are available, data assimilation approaches can be used to optimally update model states based on the assumed magnitude of modeling and observational errors (see e.g. Reichle et al., 2002). LDAS estimates have value for studies of water, energy, and biogeochemical cycles, Numerical Weather Prediction (NWP), and seasonal climate forecasts. Obtaining high-quality global LDAS products for these applications, however, will require new remote sensing measurements from several water cycle missions such as the Global Precipitation Measurement satellite constellation (GPM; see Flaming, 2005) and The Hydrosphere State Mission (Hydros; see Entekhabi et al., 2004). In particular, exploiting the complementary nature of multiple types of water cycle measurements significantly enhances the accuracy of LDAS system outputs.

Last Modified: 8/24/2016
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