A singular vector perspective of 4DVAR: The spatial structure and evolution of baroclinic weather systems

Johnson, C., Hoskins, B. J., Nichols, N. K. ORCID: https://orcid.org/0000-0003-1133-5220 and Ballard, S. P. (2006) A singular vector perspective of 4DVAR: The spatial structure and evolution of baroclinic weather systems. Monthly Weather Review, 134 (11). pp. 3436-3455. ISSN 0027-0644 doi: 10.1175/MWR3243.1

Abstract/Summary

The extent to which the four-dimensional variational data assimilation (4DVAR) is able to use information about the time evolution of the atmosphere to infer the vertical spatial structure of baroclinic weather systems is investigated. The singular value decomposition (SVD) of the 4DVAR observability matrix is introduced as a novel technique to examine the spatial structure of analysis increments. Specific results are illustrated using 4DVAR analyses and SVD within an idealized 2D Eady model setting. Three different aspects are investigated. The first aspect considers correcting errors that result in normal-mode growth or decay. The results show that 4DVAR performs well at correcting growing errors but not decaying errors. Although it is possible for 4DVAR to correct decaying errors, the assimilation of observations can be detrimental to a forecast because 4DVAR is likely to add growing errors instead of correcting decaying errors. The second aspect shows that the singular values of the observability matrix are a useful tool to identify the optimal spatial and temporal locations for the observations. The results show that the ability to extract the time-evolution information can be maximized by placing the observations far apart in time. The third aspect considers correcting errors that result in nonmodal rapid growth. 4DVAR is able to use the model dynamics to infer some of the vertical structure. However, the specification of the case-dependent background error variances plays a crucial role.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/4896
Item Type	Article
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
Uncontrolled Keywords	Data assimilation, Numerical studies, Baroclinic flows, Variational analysis
Publisher	American Meteorological Society
Download/View statistics	View download statistics for this item