Journal
JOURNAL OF HYDROMETEOROLOGY
Volume 12, Issue 5, Pages 1040-1055Publisher
AMER METEOROLOGICAL SOC
DOI: 10.1175/2011JHM1346.1
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Funding
- NSF [0830068]
- National Oceanic and Atmospheric Administration [NA09OAR4310058]
- National Aeronautics and Space Administration [NNX09AN50G, NESSF 09-Earth09R-80]
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A weak constraint is introduced in ensemble Kalman filters to reduce the water budget imbalance that occurs in land data assimilation. Two versions of the weakly constrained filter, called the weakly constrained ensemble Kalman filter (WCEnKF) and the weakly constrained ensemble transform Kalman filter (WCETKF), are proposed. The strength of the weak constraint is adaptive in the sense that it depends on the statistical characteristics of the forecast ensemble. The resulting filters are applied to assimilate synthetic observations generated by the Noah land surface model over the Red Arkansas River basin. The data assimilation experiments demonstrate that, for all tested scenarios, the constrained filters produce analyses with nearly the same accuracy as unconstrained filters, but with much smaller water balance residuals than unconstrained filters.
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