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

Haben, S. A., Lawless, A. S. ORCID: https://orcid.org/0000-0002-3016-6568 and Nichols, N. K. ORCID: https://orcid.org/0000-0003-1133-5220 (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 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
URI	https://reading-clone.eprints-hosting.org/id/eprint/24142
Item Type	Article
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO) Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Wiley
Download/View statistics	View download statistics for this item