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[NSB09] YAO: A Software for Variational Data Assimilation Using Numerical Models
Conférence Internationale avec comité de lecture : International Conference on Computational Science and its Applications, ICCSA 2009, Seul, South Korea, June 2009, pp.Part II, 621-636, Series LNCS 5593,Mots clés: data assimilation, numerical model, modular graph, adjoint model, automatic differentiation, backpropagation
Résumé:
Variational data assimilation consists in estimating control parameters of a numerical model in order to minimize the misï¬t between the forecast values and some actual observations. The gradient based minimization methods require the multiplication of the transpose jacobian matrix (adjoint model), which is of huge dimension, with the derivative vector of the cost function at the observation points. We present a method based on a modular graph concept and two algorithms to avoid these expensive multiplications. The ï¬rst step of the method is a propagation algorithm on the graph that allows computing the output of the numerical model and its linear tangent, the second is a backpropagation on the graph that allows the computation of the adjoint model. The YAO software implements these two steps using appropriate algorithms. We present a brief description of YAO functionalities.
Equipe:
msdma
Collaboration:
UPMC
BibTeX
| @inproceedings { | |||
| NSB09, | |||
| title | = | "{YAO: A Software for Variational Data Assimilation Using Numerical Models}", | |
| author | = | " L. Nardi and C. Sorror and F. Badran and S. Thiria ", | |
| booktitle | = | "{International Conference on Computational Science and its Applications, ICCSA 2009, Seul, South Korea}", | |
| year | = | 2009, | |
| month | = | "June", | |
| series | = | "LNCS 5593", | |
| pages | = | "Part II, 621-636", | |
| } | |||
