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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Volume 24, issue 3
Nonlin. Processes Geophys., 24, 515–534, 2017
https://doi.org/10.5194/npg-24-515-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Nonlin. Processes Geophys., 24, 515–534, 2017
https://doi.org/10.5194/npg-24-515-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 05 Sep 2017

Research article | 05 Sep 2017

Data assimilation for moving mesh methods with an application to ice sheet modelling

Bertrand Bonan, Nancy K. Nichols, Michael J. Baines, and Dale Partridge Bertrand Bonan et al.
  • School of Mathematical, Physical and Computational Sciences, University of Reading, Reading, UK

Abstract. We develop data assimilation techniques for non-linear dynamical systems modelled by moving mesh methods. Such techniques are valuable for explicitly tracking interfaces and boundaries in evolving systems. The unique aspect of these assimilation techniques is that both the states of the system and the positions of the mesh points are updated simultaneously using physical observations. Covariances between states and mesh points are generated either by a correlation structure function in a variational context or by ensemble methods. The application of the techniques is demonstrated on a one-dimensional model of a grounded shallow ice sheet. It is shown, using observations of surface elevation and/or surface ice velocities, that the techniques predict the evolution of the ice sheet margin and the ice thickness accurately and efficiently. This approach also allows the straightforward assimilation of observations of the position of the ice sheet margin.

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Short summary
We develop data assimilation techniques for numerical models using moving mesh methods. Moving meshes are valuable for explicitly tracking interfaces and boundaries in evolving systems. The application of the techniques is demonstrated on a one-dimensional model of an ice sheet. It is shown, using various types of observations, that the techniques predict the evolution of the edges of the ice sheet and its height accurately and efficiently.
We develop data assimilation techniques for numerical models using moving mesh methods. Moving...
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