Séminaire de Mécanique d'Orsay

Le Jeudi 31 mai 2018 à 14h00 - Salle de conférences du LIMSI

Surrogate based approaches to parameter inference in ocean models

Omar Knio
King Abdullah University of Science and Technology, Thuwal, KSA

This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer wind drag, bottom drag, and internal mixing coefficients.

Accès Salle de conférences du LIMSI