Improving land data assimilation performance with a water budget constraint

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2011-10-01

Author

Yılmaz, Mustafa Tuğrul
Houser, Paul R.

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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.

Subject Keywords

Atmospheric Science

URI

https://hdl.handle.net/11511/40810

Journal

Journal of Hydrometeorology

DOI

https://doi.org/10.1175/2011jhm1346.1

Collections

Department of Civil Engineering, Article

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Citation Formats

M. T. Yılmaz and P. R. Houser, “Improving land data assimilation performance with a water budget constraint,” Journal of Hydrometeorology, pp. 1040–1055, 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/40810.