Joint Session 1 Advances in Land Data Assimilation Part I

Tuesday, 8 January 2013: 1:30 PM-3:00 PM
Room 10A (Austin Convention Center)
Hosts: (Joint between the 27th Conference on Hydrology; and the 17th Conference on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS) )
Michael B. Ek, NOAA/NWS/NCEP/EMC, College Park, MD and Rolf H. Reichle, NASA/GSFC and Univ. of Maryland, Code 974, Greenbelt, MD

This session highlights advances in development and applications of land data assimilation systems (LDAS), which merge ground- or satellite-based land surface observations with estimates from coupled or “off-line” land surface models, and can be used to initialize weather and seasonal climate forecasts, monitor and predict extreme events, provide improved background information for atmospheric data assimilation, improve process understanding, and support model development. Contributions may include studies that evaluate or improve land DA methods, assess LDAS impact on state estimates, or use LDAS for the above-mentioned applications. Contributions may address the simultaneous assimilation of multiple observation types, and use of current and planned hydrology satellite missions (e.g. SMOS, SMAP and SWOT). Contact(s): Mike Ek (, Youlong Xia (, Rolf Reichle (, and Susan Steele-Dunne (

1:30 PM
Assimilation of GlobSnow snow water equivalent in the Canadian Land Data Assimilation System
Stéphane Bélair, EC, Dorval, QC, Canada; and C. Derksen, B. Bilodeau, M. Carrera, S. Dyck, D. charpentier, N. Gauthier, and L. Wang

1:45 PM
2:15 PM
Evaluation of Multi-Model Simulated Products in NLDAS-2
Youlong Xia, NOAA/NCEP/EMC, IMSG, College Park, MD; and M. B. Ek, J. Sheffield, E. F. Wood, D. Mocko, C. D. Peters-Lidard, and D. P. Lettenmaier
2:30 PM
Evaluation of New and Upgraded Land-Surface Models in the North American Land Data Assimilation System (NLDAS)
David M. Mocko, SAIC at NASA/GSFC, Greenbelt, MD; and C. D. Peters-Lidard, S. V. Kumar, Y. Xia, M. B. Ek, and J. Dong

2:45 PM
China Land Soil Moisture EnKF Data Assimilation Based on Satellite Remote Sensing Data
Chunxiang Shi, China Meteorological Administration, Beijing, China; and Z. Xie, X. Tian, M. Liang, and X. Yang
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