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An ETKF approach for initial state and parameter estimation in ice sheet modelling

Bertrand Bonan 1 Maëlle Nodet 1 Catherine Ritz 2 Vincent Peyaud 3 
1 MOISE - Modelling, Observations, Identification for Environmental Sciences
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
2 EDGe
LGGE - Laboratoire de glaciologie et géophysique de l'environnement
Abstract : Estimating the contribution of Antarctica and Greenland to sea-level rise is a hot topic in glaciology. Good estimates rely on our ability to run a precisely calibrated ice sheet evolution model starting from a reliable initial state. Data assimilation aims to provide an answer to this problem by combining the model equations with observations. In this paper we aim to study a state-of-the-art ensemble Kalman filter (ETKF) to address this problem. This method is implemented and validated in the twin experiments framework for a shallow ice flowline model of ice dynamics. The results are very encouraging, as they show a good convergence of the ETKF (with localisation and inflation), even for small-sized ensembles.
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Submitted on : Monday, September 22, 2014 - 3:32:58 PM
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Bertrand Bonan, Maëlle Nodet, Catherine Ritz, Vincent Peyaud. An ETKF approach for initial state and parameter estimation in ice sheet modelling. Nonlinear Processes in Geophysics, 2014, 21 (2), pp.569-582. ⟨10.5194/npg-21-569-2014⟩. ⟨hal-01066882⟩



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