Articles | Volume 11, issue 11
https://doi.org/10.5194/gmd-11-4563-2018
https://doi.org/10.5194/gmd-11-4563-2018
Development and technical paper
 | 
16 Nov 2018
Development and technical paper |  | 16 Nov 2018

Dynamically coupling full Stokes and shallow shelf approximation for marine ice sheet flow using Elmer/Ice (v8.3)

Eef C. H. van Dongen, Nina Kirchner, Martin B. van Gijzen, Roderik S. W. van de Wal, Thomas Zwinger, Gong Cheng, Per Lötstedt, and Lina von Sydow

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Cited articles

Ahlkrona, J., Lötstedt, P., Kirchner, N., and Zwinger, T.: Dynamically coupling the non-linear Stokes equations with the shallow ice approximation in glaciology: Description and first applications of the ISCAL method, J. Comput. Phys., 308, 1–19, 2016.
Alley, R. B., Clark, P. U., Huybrechts, P., and Joughin, I.: Ice-sheet and sea-level changes, Science, 310, 456–460, 2005.
Asay-Davis, X. S., Cornford, S. L., Durand, G., Galton-Fenzi, B. K., Gladstone, R. M., Gudmundsson, G. H., Hattermann, T., Holland, D. M., Holland, D., Holland, P. R., Martin, D. F., Mathiot, P., Pattyn, F., and Seroussi, H.: Experimental design for three interrelated marine ice sheet and ocean model intercomparison projects: MISMIP v. 3 (MISMIP +), ISOMIP v. 2 (ISOMIP +) and MISOMIP v. 1 (MISOMIP1), Geosci. Model Dev., 9, 2471–2497, https://doi.org/10.5194/gmd-9-2471-2016, 2016.
Baiocchi, C., Brezzi, F., and Franca, L. P.: Virtual bubbles and Galerkin-least-squares type methods, Comp. Meths. Appl. Mech. Engrg., 105, 125–141, 1993.
Benzi, M., Golub, G. H., and Liesen, J.: Numerical solution of saddle point problems, Acta Numer., 14, 1–137, 2005.
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Short summary
Ice flow forced by gravity is governed by the full Stokes (FS) equations, which are computationally expensive to solve. Therefore, approximations to the FS equations are used, especially when modeling an ice sheet on long time spans. Here, we report a combination of an approximation with the FS equations that allows simulating the dynamics of ice sheets over long time spans without introducing artifacts caused by application of approximations in parts of the domain where they are not valid.
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