Comparison of adjoint and nudging methods to initialise ice sheet model basal conditions

Ice flow models are now routinely used to forecast the ice sheets' contribution to 21st century sea-level rise. For such short term simulations, the model response is greatly affected by the initial conditions. Data assimilation algorithms have been developed to invert for the friction of the i...

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Bibliographic Details
Published in:Geoscientific Model Development
Main Authors: C. Mosbeux, F. Gillet-Chaulet, O. Gagliardini
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2016
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Online Access:https://doi.org/10.5194/gmd-9-2549-2016
https://doaj.org/article/2daeb9379f1a4fed90a8bc1cddc828eb
Description
Summary:Ice flow models are now routinely used to forecast the ice sheets' contribution to 21st century sea-level rise. For such short term simulations, the model response is greatly affected by the initial conditions. Data assimilation algorithms have been developed to invert for the friction of the ice on its bedrock using observed surface velocities. A drawback of these methods is that remaining uncertainties, especially in the bedrock elevation, lead to non-physical ice flux divergence anomalies resulting in undesirable transient effects. In this study, we compare two different assimilation algorithms based on adjoints and nudging to constrain both bedrock friction and elevation. Using synthetic twin experiments with realistic observation errors, we show that the two algorithms lead to similar performances in reconstructing both variables and allow the flux divergence anomalies to be significantly reduced.