Résumé
for the weakly-constrained 4D-VAR method in data assimilation. It is shown
that the method, in its original form, may produce erratic results or diverge
because of the inherent lack of monotonicity of the produced objective
function values. Convergent, variationaly coherent variants of the algorithm
are then proposed whose practical performance is compared to that of other
formulations. This comparison is conducted on two data assimilation instances
(Burgers equation and the Quasi-Geostrophic model), using two different
assumptions on parallel computing environment. Because these
variants essentially retain the parallelization advantages of the original
proposal, they often --- but not always --- perform best, even for moderate
numbers of computing processes.
| langue originale | Anglais |
|---|---|
| Éditeur | Arxiv |
| Volume | 1709.06383 |
| état | Soumis - 20 sept. 2017 |
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On the use of the saddle formulation in weakly-constrained 4D-VAR data assimilation. / Gratton, Serge; Gürol, Selime; Simon, Ehouarn; Toint, Philippe.
Arxiv, 2017.Résultats de recherche: Papier de travail › Article de travail
TY - UNPB
T1 - On the use of the saddle formulation in weakly-constrained 4D-VAR data assimilation
AU - Gratton, Serge
AU - Gürol, Selime
AU - Simon, Ehouarn
AU - Toint, Philippe
PY - 2017/9/20
Y1 - 2017/9/20
N2 - This paper discusses the practical use of the saddle variational formulationfor the weakly-constrained 4D-VAR method in data assimilation. It is shownthat the method, in its original form, may produce erratic results or divergebecause of the inherent lack of monotonicity of the produced objectivefunction values. Convergent, variationaly coherent variants of the algorithmare then proposed whose practical performance is compared to that of otherformulations. This comparison is conducted on two data assimilation instances(Burgers equation and the Quasi-Geostrophic model), using two differentassumptions on parallel computing environment. Because thesevariants essentially retain the parallelization advantages of the originalproposal, they often --- but not always --- perform best, even for moderatenumbers of computing processes.
AB - This paper discusses the practical use of the saddle variational formulationfor the weakly-constrained 4D-VAR method in data assimilation. It is shownthat the method, in its original form, may produce erratic results or divergebecause of the inherent lack of monotonicity of the produced objectivefunction values. Convergent, variationaly coherent variants of the algorithmare then proposed whose practical performance is compared to that of otherformulations. This comparison is conducted on two data assimilation instances(Burgers equation and the Quasi-Geostrophic model), using two differentassumptions on parallel computing environment. Because thesevariants essentially retain the parallelization advantages of the originalproposal, they often --- but not always --- perform best, even for moderatenumbers of computing processes.
KW - data assimilation
KW - weather forecasting
KW - Numerical optimization
KW - Least-squares problems
M3 - Working paper
VL - 1709.06383
BT - On the use of the saddle formulation in weakly-constrained 4D-VAR data assimilation
PB - Arxiv
ER -