Accessibility navigation


Data Assimilation and Inverse Methods in Terms of a Probabilistic Formulation

Van Leeuwen, P. J. and Evensen, G. (1996) Data Assimilation and Inverse Methods in Terms of a Probabilistic Formulation. Monthly Weather Review, 124 (12). pp. 2898-2913. ISSN 0027-0644

[img] Text - Published Version
· Restricted to Repository staff only
· The Copyright of this document has not been checked yet. This may affect its availability.

1MB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1175/1520-0493(1996)124<2898:DAAIMI>2.0.CO;2

Abstract/Summary

The weak-constraint inverse for nonlinear dynamical models is discussed and derived in terms of a probabilistic formulation. The well-known result that for Gaussian error statistics the minimum of the weak-constraint inverse is equal to the maximum-likelihood estimate is rederived. Then several methods based on ensemble statistics that can be used to find the smoother (as opposed to the filter) solution are introduced and compared to traditional methods. A strong point of the new methods is that they avoid the integration of adjoint equations, which is a complex task for real oceanographic or atmospheric applications. they also avoid iterative searches in a Hilbert space, and error estimates can be obtained without much additional computational effort. the feasibility of the new methods is illustrated in a two-layer quasigeostrophic model.

Item Type:Article
Refereed:Yes
Divisions:No Reading authors. Back catalogue items
ID Code:49822

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation