Variational data assimilation for very large environmental problems

Lawless, A. ORCID: https://orcid.org/0000-0002-3016-6568 (2013) Variational data assimilation for very large environmental problems. In: Cullen, M., Freitag, M.A., Kindermann, S. and Scheichl, R. (eds.) Large Scale Inverse Problems: Computational Methods and Applications in the Earth Sciences. Radon Series on Computational and Applied Mathematics, 2 (13). De Gruyter, Berlin, pp. 55-90. ISBN 9783110282269

Abstract/Summary

Variational data assimilation is commonly used in environmental forecasting to estimate the current state of the system from a model forecast and observational data. The assimilation problem can be written simply in the form of a nonlinear least squares optimization problem. However the practical solution of the problem in large systems requires many careful choices to be made in the implementation. In this article we present the theory of variational data assimilation and then discuss in detail how it is implemented in practice. Current solutions and open questions are discussed.

Item Type	Book or Report Section
URI	https://reading-clone.eprints-hosting.org/id/eprint/37707
Item Type	Book or Report Section
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
Uncontrolled Keywords	Review article on variational data assimilation methods.
Publisher	De Gruyter
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