Nonlinear Processes in Geophysics (Apr 2014)

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

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

DOI
https://doi.org/10.5194/npg-21-569-2014
Journal volume & issue
Vol. 21, no. 2
pp. 569 – 582

Abstract

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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.