Introducing Water Budget Constraint To Improve Land Data Assimilation Performance

2011-05-24
Yılmaz, Mustafa Tuğrul
Houser, Paul
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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 un-constrained filters.
https://hdl.handle.net/11511/80069
https://www.researchgate.net/publication/256496998_Introducing_water_budget_constraint_to_improve_land_data_assimilation_performance
JCSDA 9th Workshop on Satellite Data Assimilation, 24 - 25 May 2011
Department of Civil Engineering, Conference / Seminar

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Citation Formats
M. T. Yılmaz and P. Houser, “Introducing Water Budget Constraint To Improve Land Data Assimilation Performance,” presented at the JCSDA 9th Workshop on Satellite Data Assimilation, 24 - 25 May 2011, 2011, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/80069.
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