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  A goal oriented error estimator and mesh adaptivity for sea ice simulations

Mehlmann, C., & Richter, T. (2020). A goal oriented error estimator and mesh adaptivity for sea ice simulations. Ocean Modelling, 154: 101684. doi:10.1016/j.ocemod.2020.101684.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0006-FEA5-2 Version Permalink: http://hdl.handle.net/21.11116/0000-0007-0AE6-B
Genre: Journal Article

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 Creators:
Mehlmann , Carolin1, Author
Richter, T., Author
Affiliations:
1Applied Mathematics and Computational Physics (AMCP), Scientific Computing Lab (ScLab), MPI for Meteorology, Max Planck Society, Bundesstraße 53, 20146 Hamburg, DE, ou_2129636              

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Free keywords: Adaptive algorithms; Mesh generation; Sea ice, Discretization errors; Dual weighted residuals; Error estimators; Functional outputs; Momentum equation; Numerical approximations; Splitting errors; Temporal discretization, Error analysis, algorithm; equation; error analysis; numerical method; numerical model; sea ice
 Abstract: For the first time we introduce an error estimator for the numerical approximation of the equations describing the dynamics of sea ice. The idea of the estimator is to identify different error contributions coming from spatial and temporal discretization as well as from the splitting in time of the ice momentum equations from further parts of the coupled system. The novelty of the error estimator lies in the consideration of the splitting error, which turns out to be dominant with increasing mesh resolution. Errors are measured in user specified functional outputs like the total sea ice extent. The error estimator is based on the dual weighted residual method that asks for the solution of an additional dual problem for obtaining sensitivity information. Estimated errors can be used to validate the accuracy of the solution and, more relevant, to reduce the discretization error by guiding an adaptive algorithm that optimally balances the mesh size and the time step size to increase the efficiency of the simulation. © 2020 Elsevier Ltd

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Language(s): eng - English
 Dates: 2020-10
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.ocemod.2020.101684
BibTex Citekey: Mehlmann2020
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Title: Ocean Modelling
Source Genre: Journal
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Publ. Info: Elsevier Ltd
Pages: - Volume / Issue: 154 Sequence Number: 101684 Start / End Page: - Identifier: ISSN: 14635003