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Original Research Papers

Conditioning of incremental variational data assimilation, with application to the Met Office system

Authors:

S. A. Haben,

Department of Mathematics and Statistics, P.O. Box 220, University of Reading, Reading, RG6 6AX, GB
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A. S. Lawless ,

Department of Mathematics and Statistics, P.O. Box 220, University of Reading, Reading, RG6 6AX, GB
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N. K. Nichols

Department of Mathematics and Statistics, P.O. Box 220, University of Reading, Reading, RG6 6AX, GB
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Abstract

Implementations of incremental variational data assimilation require the iterative minimization of a series of linear least-squares cost functions. The accuracy and speed with which these linear minimization problems can be solved is determined by the condition number of the Hessian of the problem. In this study, we examine how different components of the assimilation system influence this condition number. Theoretical bounds on the condition number for a single parameter system are presented and used to predict how the condition number is affected by the observation distribution and accuracy and by the specified lengthscales in the background error covariance matrix. The theoretical results are verified in the Met Office variational data assimilation system, using both pseudo-observations and real data.

How to Cite: Haben, S.A., Lawless, A.S. and Nichols, N.K., 2011. Conditioning of incremental variational data assimilation, with application to the Met Office system. Tellus A: Dynamic Meteorology and Oceanography, 63(4), pp.782–792. DOI: http://doi.org/10.1111/j.1600-0870.2011.00527.x
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  Published on 01 Jan 2011
 Accepted on 29 Mar 2011            Submitted on 22 Jul 2010

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