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Advanced Data Assimilation for GeosciencesLecture Notes of the Les Houches School of Physics: Special Issue, June 2012$
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Éric Blayo, Marc Bocquet, Emmanuel Cosme, and Leticia F. Cugliandolo

Print publication date: 2014

Print ISBN-13: 9780198723844

Published to Oxford Scholarship Online: March 2015

DOI: 10.1093/acprof:oso/9780198723844.001.0001

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Multigrid algorithms and local mesh refinement methods in the context of variational data assimilation

Multigrid algorithms and local mesh refinement methods in the context of variational data assimilation

Chapter:
(p.395) 17 Multigrid algorithms and local mesh refinement methods in the context of variational data assimilation
Source:
Advanced Data Assimilation for Geosciences
Author(s):

L. Debreu

E. Neveu

E. Simon

F.-X. Le Dimet

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198723844.003.0017

This chapter looks at the use of multigrid methods and local mesh refinement algorithms in the context of the variational data assimilation method. Firstly, the chapter looks back at basic properties of the traditional variational data assimilation method and considers on the role of the background error covariance matrix. The next section shows how multigrid algorithms can efficiently solve the resulting system. Then the chapter deals with local mesh refinements and the final part of the chapter gives some ideas on how to couple the two approaches in the view of local multigrid algorithms.

Keywords:   multigrid methods, mesh refinement, variational data, data assimilation method, background error covariance matrix

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