The Auto-Tuned Land Data Assimilation System (ATLAS)
Author:
Affiliation:
1. USDA Hydrology and Remote Sensing Laboratory; Beltsville Maryland USA
2. Civil Engineering Department; Middle East Technical University; Anakara Turkey
Publisher
American Geophysical Union (AGU)
Subject
Water Science and Technology
Reference26 articles.
1. Improved prediction of quasi-global veg etation conditions using remotely-sensed surface soil moisture;Bolten;Geophys. Res. Lett.,2012
2. Kalman Filtering
3. Comparison of adaptive filtering techniques for land surface data assimilation;Crow;Water Resour. Res.,2008
4. An improved approach for estimating observation and model error parameters for soil moisture data assimilation;Crow;Water Resour. Res.,2010
5. Impact of incorrect model error assumptions on the sequential assimilation of remotely sensed surface soil moisture;Crow;J. Hydrometerol.,2006
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