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

• Published in: Nonlinear Processes in Geophysics
• Main Authors: Bonan, B., Nodet, M., Ritz, C., Peyaud, V.
• Format: Text
• Language: English
• Published: 2018
• Subjects: Greenland; Antarc*; Antarctica; Ice Sheet
• Online Access: https://doi.org/10.5194/npg-21-569-2014; https://npg.copernicus.org/articles/21/569/2014/

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.