Assimilation de données pour l'initialisation et l'estimation de paramètres d'un modèle d'évolution de calotte polaire

Bertrand Bonan 1
1 MOISE - Modelling, Observations, Identification for Environmental Sciences
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : Ice sheet evolution is both driven by complex flow dynamics and by physical mechanisms such as basal sliding, ice temperature or surface mass balance. In addition to those, many feedback loops are observed between the different implicated phenomena. This explains how complex is to model this evolution. However several models have been developed. These models depend on influent parameters, which often are unfortunately poorly known. So they need to be correctly specified. Data assimilation can give a better estimation of these parameters thanks to observations which are quite rare in glaciology. During this thesis, we work with a simplified ice sheet evolution model called Winnie in order to focus on the setup. Nevertheless Winnie depicted the main complex processes of ice dynamics and can be used for studies with different time scales. The first part of the thesis focuses on on developping a 4D-Var approach in order to retrieve the evolution of a climatic parameter for a typical time scale of 20 000 years. This approach requires the implementation of the adjoint code of the evolution model. In a second part, we focus on the spin-up problem. This calibration problem for short term (maximum 100 years) simulations involve retrieving jointly the initial state, the bedrock topography and basal sliding parameters. In order to solve this problem we develop an Ensemble Kalman Filter approach.
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Bertrand Bonan. Assimilation de données pour l'initialisation et l'estimation de paramètres d'un modèle d'évolution de calotte polaire. Optimisation et contrôle [math.OC]. Université de Grenoble, 2013. Français. 〈tel-00930097v1〉

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