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A hybrid data assimilation scheme for model parameter estimation: application to morphodynamic modelling

Smith, P. J. ORCID: https://orcid.org/0000-0003-4570-4127, Dance, S. L. ORCID: https://orcid.org/0000-0003-1690-3338 and Nichols, N. K. ORCID: https://orcid.org/0000-0003-1133-5220 (2011) A hybrid data assimilation scheme for model parameter estimation: application to morphodynamic modelling. Computers & Fluids, 46 (1). pp. 436-441. ISSN 0045-7930

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To link to this item DOI: 10.1016/j.compfluid.2011.01.010

Abstract/Summary

We present a novel algorithm for joint state-parameter estimation using sequential three dimensional variational data assimilation (3D Var) and demonstrate its application in the context of morphodynamic modelling using an idealised two parameter 1D sediment transport model. The new scheme combines a static representation of the state background error covariances with a flow dependent approximation of the state-parameter cross-covariances. For the case presented here, this involves calculating a local finite difference approximation of the gradient of the model with respect to the parameters. The new method is easy to implement and computationally inexpensive to run. Experimental results are positive with the scheme able to recover the model parameters to a high level of accuracy. We expect that there is potential for successful application of this new methodology to larger, more realistic models with more complex parameterisations.

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
ID Code:18906
Uncontrolled Keywords:Data assimilation, Morphodynamics, Parameter estimation, State augmentation
Additional Information:10th ICFD Conference Series on Numerical Methods for Fluid Dynamics (ICFD 2010)
Publisher:Elsevier

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