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

Bonan, B.; Nodet, M.; Ritz, C.; Peyaud, V.

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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Bonan, B. / Nodet, M. / Ritz, C. / et al: An ETKF approach for initial state and parameter estimation in ice sheet modelling. 2014. Copernicus Publications.

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