An improved approach for estimating observation and model error parameters in soil moisture data assimilation-Reference-Cited by-同舟云学术

An improved approach for estimating observation and model error parameters in soil moisture data assimilation

Published:2010-12 Issue:12 Volume:46 Page:
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resour. Res.

Author:

Crow W. T.¹,van den Berg M. J.¹

Affiliation:

1. Hydrology and Remote Sensing Laboratory; USDA Agricultural Research Service; Beltsville Maryland USA

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1029/2010WR009402/fullpdf

Reference33 articles.

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2. Evaluating the utility of remotely sensed soil moisture retrievals for operational agricultural drought monitoring;Bolten;IEEE J. Sel. Top. Earth Obs. Appl. Remote Sens.,2010

3. Precipitation, soil moisture, and climate database, Little River Experimental Watershed, Georgia, United States;Bosch;Water Resour. Res.,2007

4. Chui , C. K. G. Chen 1991 Kalman filtering with Real-Time Applications ColKF Springer New York

5. Real-time and retrospective forcing in the North American Land Data Assimilation System (NLDAS) project;Cosgrove;J. Geophys. Res.,2003

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