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Four-dimensional variational data assimilation for high resolution nested models

Baxter, G.M., Dance, S.L., Lawless, A.S. and Nichols, N.K. (2011) Four-dimensional variational data assimilation for high resolution nested models. Computers & Fluids, 46 (1). pp. 137-141. ISSN 0045-7930

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To link to this article DOI: 10.1016/j.compfluid.2011.01.023

Abstract/Summary

Four-dimensional variational data assimilation (4D-Var) is used in environmental prediction to estimate the state of a system from measurements. When 4D-Var is applied in the context of high resolution nested models, problems may arise in the representation of spatial scales longer than the domain of the model. In this paper we study how well 4D-Var is able to estimate the whole range of spatial scales present in one-way nested models. Using a model of the one-dimensional advection–diffusion equation we show that small spatial scales that are observed can be captured by a 4D-Var assimilation, but that information in the larger scales may be degraded. We propose a modification to 4D-Var which allows a better representation of these larger scales.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical and Physical Sciences > Department of Meteorology
Faculty of Science > School of Mathematical and Physical Sciences > Department of Mathematics and Statistics
ID Code:18905
Publisher:Elsevier

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