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, INPG - Institut National Polytechnique de Grenoble
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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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, European Geosciences Union (EGU), 2014, 21 (2), pp.569-582. ⟨10.5194/npg-21-569-2014⟩. ⟨hal-01066882⟩

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