Variational data assimilation for parameter estimation: application to a simple morphodynamic model

Smith, P. ORCID: https://orcid.org/0000-0003-4570-4127, Dance, S. L. ORCID: https://orcid.org/0000-0003-1690-3338, Baines, M. J., Nichols, N. K. ORCID: https://orcid.org/0000-0003-1133-5220 and Scott, T. R. (2009) Variational data assimilation for parameter estimation: application to a simple morphodynamic model. Ocean Dynamics, 59 (5). pp. 697-708. ISSN 1616-7341 doi: 10.1007/s10236-009-0205-6

Abstract/Summary

Data assimilation is a sophisticated mathematical technique for combining observational data with model predictions to produce state and parameter estimates that most accurately approximate the current and future states of the true system. The technique is commonly used in atmospheric and oceanic modelling, combining empirical observations with model predictions to produce more accurate and well-calibrated forecasts. Here, we consider a novel application within a coastal environment and describe how the method can also be used to deliver improved estimates of uncertain morphodynamic model parameters. This is achieved using a technique known as state augmentation. Earlier applications of state augmentation have typically employed the 4D-Var, Kalman filter or ensemble Kalman filter assimilation schemes. Our new method is based on a computationally inexpensive 3D-Var scheme, where the specification of the error covariance matrices is crucial for success. A simple 1D model of bed-form propagation is used to demonstrate the method. The scheme is capable of recovering near-perfect parameter values and, therefore, improves the capability of our model to predict future bathymetry. Such positive results suggest the potential for application to more complex morphodynamic models.

Additional Information	Conference Information: 14th International Biennial Conference on Physics of Estuaries and Coastal Seas Liverpool, ENGLAND, AUG 15-29, 2008
Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/1702
Item Type	Article
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics Science > School of Mathematical, Physical and Computational Sciences > Environmental Systems Science Centre
Uncontrolled Keywords	Data assimilation - Morphodynamic modelling - Parameter estimation - State augmentation
Additional Information	Conference Information: 14th International Biennial Conference on Physics of Estuaries and Coastal Seas Liverpool, ENGLAND, AUG 15-29, 2008
Publisher	Springer
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