On the use of the saddle formulation in weakly-constrained 4D-VAR data assimilation

Serge Gratton; Selime Gürol; Ehouarn Simon; Philippe Toint

On the use of the saddle formulation in weakly-constrained 4D-VAR data assimilation

Serge Gratton, Selime Gürol, Ehouarn Simon, Philippe Toint

Namur Institute for Complex Systems

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Résumé

This paper discusses the practical use of the saddle variational formulation
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
Etat de la publication	Soumis - 20 sept. 2017

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6 Article

A data assimilation algorithm for predicting rain
Janjić, T., Ruckstuhl, Y. & Toint, P. L., avr. 2021, Dans: Quarterly Journal of the Royal Meteorological Society. 147, 736, p. 1949-1963 15 p.
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A note on preconditioning weighted linear least-squares with consequences for weakly constrained variational data assimilation
Gratton, S., Selime, G., Simon, E. & Toint, P., avr. 2018, Dans: Quarterly Journal of the Royal Meteorological Society. 144, 712, p. 934-940 7 p.
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BFO, a trainable derivative-free Brute Force Optimizer for nonlinear bound-constrained optimization and equilibrium computations with continuous and discrete variables
Porcelli, M. & Toint, P., 30 juin 2017, Dans: Transactions of the American Methematical Society on Mathematical Software. 44, 1, 28 p., 6.
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1 Actif

ADALGOPT: ADALGOPT - Algorithmes avancés en optimisation non-linéaire
Sartenaer, A. & TOINT, P.
1/01/87 → …
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A primal-dual approach of weak-constrained variational data assimilation: (Iterate) History matters
Philippe Toint (Orateur)
13 oct. 2017
Activité: Discours ou présentation › Discours invité

Contient cette citation

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title = "On the use of the saddle formulation in weakly-constrained 4D-VAR data assimilation",

abstract = "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.",

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AU - Gratton, Serge

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AU - Simon, Ehouarn

AU - Toint, Philippe

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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

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BT - On the use of the saddle formulation in weakly-constrained 4D-VAR data assimilation

PB - Arxiv

ER -

On the use of the saddle formulation in weakly-constrained 4D-VAR data assimilation

Résumé

Accès au document

Résultat de recherche

A data assimilation algorithm for predicting rain

A note on preconditioning weighted linear least-squares with consequences for weakly constrained variational data assimilation

BFO, a trainable derivative-free Brute Force Optimizer for nonlinear bound-constrained optimization and equilibrium computations with continuous and discrete variables

Projets

ADALGOPT: ADALGOPT - Algorithmes avancés en optimisation non-linéaire

Activités

A primal-dual approach of weak-constrained variational data assimilation: (Iterate) History matters

Contient cette citation