Improving land data assimilation performance with a water budget constraint

Download
2011-10-01
Yılmaz, Mustafa Tuğrul
Houser, Paul R.
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.
Journal of Hydrometeorology

Suggestions

Optimally merging precipitation to minimize land surface modeling errors
Yılmaz, Mustafa Tuğrul; Shrestha, Roshan; Anantharaj, Valentine G. (American Meteorological Society, 2010-03-01)
This paper introduces a new method to improve land surface model skill by merging different available precipitation datasets, given that an accurate land surface parameter ground truth is available. Precipitation datasets are merged with the objective of improving terrestrial water and energy cycle simulation skill, unlike most common methods in which the merging skills are evaluated by comparing the results with gauge data or selected reference data. The optimal merging method developed in this study minim...
Introducing Water Budget Constraint To Improve Land Data Assimilation Performance
Yılmaz, Mustafa Tuğrul; Houser, Paul (null; 2011-05-24)
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 assimilat...
Reducing water imbalance in land data assimilation: Ensemble filtering without perturbed observations
Yılmaz, Mustafa Tuğrul; Yilmaz, M. Tugrul (American Meteorological Society, 2012-02-01)
It is well known that the ensemble Kalman filter (EnKF) requires updating each ensemble member with perturbed observations in order to produce the proper analysis-error covariances. While increased accuracy in a mean square sense may be preferable in many applications, less accuracy might be preferable in other applications, especially if the variables being assimilated obey certain conservation laws. In land data assimilation, for instance, the update in soil moisture often produces a water balance residua...
Evaluation of Multiple Satellite-Based Precipitation Products over Complex Topography
DERIN, Yagmur; Yılmaz, Koray Kamil (American Meteorological Society, 2014-08-01)
This study evaluates the performance of four satellite-based precipitation (SBP) products over the western Black Sea region of Turkey, a region characterized by complex topography that exerts strong controls on the precipitation regime. The four SBP products include the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis version 7 experimental near-real-time product (TMPA-7RT) and post-real-time research-quality product (TMPA-7A), the Climate Prediction Center morphing technique...
Evaluation of Assumptions in Soil Moisture Triple Collocation Analysis
Yılmaz, Mustafa Tuğrul (American Meteorological Society, 2014-06-01)
Triple collocation analysis (TCA) enables estimation of error variances for three or more products that retrieve or estimate the same geophysical variable using mutually independent methods. Several statistical assumptions regarding the statistical nature of errors (e.g., mutual independence and orthogonality with respect to the truth) are required for TCA estimates to be unbiased. Even though soil moisture studies commonly acknowledge that these assumptions are required for an unbiased TCA, no study has sp...
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.