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

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 Series A: Dynamic Meteorology and Oceanography, 63 (4). pp. 782-792. ISSN 1600-0870

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To link to this article DOI: 10.1111/j.1600-0870.2011.00527.x

Abstract/Summary

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.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical and Physical Sciences > National Centre for Earth Observation (NCEO)
Faculty of Science > School of Mathematical and Physical Sciences > Department of Mathematics and Statistics
Faculty of Science > School of Mathematical and Physical Sciences > Department of Meteorology
ID Code:24142
Publisher:Wiley

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