Description
This talk discusses the practical use of the saddle variational formulationfor 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.
Period | 13 Oct 2017 |
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Held at | Alma Mater Studiorum Università di Bologna, Italy |
Degree of Recognition | National |
Keywords
- Data assimilation
- numerical linear algebra
- optimization
Related content
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Activities
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Institut National Polytechnique de Toulouse
Activity: Visiting an external institution types › Research/Teaching in a external institution
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ENSEEIHT (Joint Laboratory CERFACS-IRIT)
Activity: Visiting an external institution types › Research/Teaching in a external institution
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Parallelizing Weak Constraint 4DVAR?
Activity: Talk or presentation types › Invited talk
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Institut National Polytechnique de Toulouse (External organisation)
Activity: Membership types › Membership of committee
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CERFACS
Activity: Visiting an external institution types › Research/Teaching in a external institution
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Institut National Polytechnique de Toulouse
Activity: Visiting an external institution types › Research/Teaching in a external institution
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CERFACS
Activity: Visiting an external institution types › Research/Teaching in a external institution
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Projects
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ADALGOPT - Advanced algorithms in nonlinear optimization
Project: Research Axis
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Research output
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A note on preconditioning weighted linear least-squares with consequences for weakly constrained variational data assimilation
Research output: Contribution to journal › Article › peer-review
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On the use of the saddle formulation in weakly-constrained 4D-VAR data assimilation
Research output: Working paper
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Linearizing the Method of Conjugate Gradients
Research output: Contribution to journal › Article › peer-review
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Observations Thinning In Data Assimilation Computations
Research output: Contribution to journal › Article › peer-review