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Publications (10 of 120) Show all publications
Cheng, G. & Lötstedt, P. (2020). Parameter sensitivity analysis of dynamic ice sheet models: numerical computations. The Cryosphere, 14, 673-691
Open this publication in new window or tab >>Parameter sensitivity analysis of dynamic ice sheet models: numerical computations
2020 (English)In: The Cryosphere, ISSN 1994-0416, E-ISSN 1994-0424, Vol. 14, p. 673-691Article in journal (Refereed) Published
Abstract [en]

The friction coefficient and the base topography of a stationary and a dynamic ice sheet are perturbed in two models for the ice: the full Stokes equations and the shallow shelf approximation. The sensitivity to the perturbations of the velocity and the height at the surface is quantified by solving the adjoint equations of the stress and the height equations providing weights for the perturbed data. The adjoint equations are solved numerically and the sensitivity is computed in several examples in two dimensions. A transfer matrix couples the perturbations at the base with the perturbations at the top. Comparisons are made with analytical solutions to simplified problems. The sensitivity to perturbations depends on their wavelengths and the distance to the grounding line. A perturbation in the topography has a direct effect at the ice surface above it, while a change in the friction coefficient is less visible there.

National Category
Computational Mathematics Geosciences, Multidisciplinary
Identifiers
urn:nbn:se:uu:diva-392146 (URN)10.5194/tc-14-673-2020 (DOI)000515168000001 ()
Projects
eSSENCE
Funder
Swedish Research Council Formas, 2017-00665eSSENCE - An eScience Collaboration
Available from: 2020-02-17 Created: 2019-08-29 Last updated: 2020-04-01Bibliographically approved
Cheng, G., Lötstedt, P. & von Sydow, L. (2019). A full Stokes subgrid model for simulation of grounding line migration in ice sheets using Elmer/ICE(v8.3). Geoscientific Model Development Discussions
Open this publication in new window or tab >>A full Stokes subgrid model for simulation of grounding line migration in ice sheets using Elmer/ICE(v8.3)
2019 (English)In: Geoscientific Model Development Discussions, ISSN 1991-9611, E-ISSN 1991-962XArticle in journal (Other academic) Submitted
National Category
Computational Mathematics Geosciences, Multidisciplinary
Identifiers
urn:nbn:se:uu:diva-392197 (URN)10.5194/gmd-2019-244 (DOI)
Projects
eSSENCE
Available from: 2019-09-16 Created: 2019-08-30 Last updated: 2019-10-02Bibliographically approved
Cheng, G. & Lötstedt, P. (2019). Parameter sensitivity analysis of dynamic ice sheet models. Computing Research Repository (1906.08197)
Open this publication in new window or tab >>Parameter sensitivity analysis of dynamic ice sheet models
2019 (English)In: Computing Research Repository, no 1906.08197Article in journal (Other academic) Submitted
National Category
Computational Mathematics Geosciences, Multidisciplinary
Identifiers
urn:nbn:se:uu:diva-392198 (URN)
Available from: 2019-06-19 Created: 2019-08-30 Last updated: 2019-09-03Bibliographically approved
Lötstedt, P. (2019). The linear noise approximation for spatially dependent biochemical networks. Bulletin of Mathematical Biology, 81, 2873-2901
Open this publication in new window or tab >>The linear noise approximation for spatially dependent biochemical networks
2019 (English)In: Bulletin of Mathematical Biology, ISSN 0092-8240, E-ISSN 1522-9602, Vol. 81, p. 2873-2901Article in journal (Refereed) Published
National Category
Computational Mathematics Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:uu:diva-351228 (URN)10.1007/s11538-018-0428-0 (DOI)000478772200004 ()29644520 (PubMedID)
Projects
eSSENCE
Available from: 2018-04-11 Created: 2018-05-21 Last updated: 2019-09-26Bibliographically approved
Marchenko, S., Cheng, G., Lötstedt, P., Pohjola, V., Pettersson, R., van Pelt, W. & Reijmer, C. (2019). Thermal conductivity of firn at Lomonosovfonna, Svalbard, derived from subsurface temperature measurements. The Cryosphere, 13, 1843-1859
Open this publication in new window or tab >>Thermal conductivity of firn at Lomonosovfonna, Svalbard, derived from subsurface temperature measurements
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2019 (English)In: The Cryosphere, ISSN 1994-0416, E-ISSN 1994-0424, Vol. 13, p. 1843-1859Article in journal (Refereed) Published
National Category
Physical Geography
Identifiers
urn:nbn:se:uu:diva-334156 (URN)10.5194/tc-13-1843-2019 (DOI)000474653300002 ()
Available from: 2019-07-09 Created: 2017-11-21 Last updated: 2019-09-01Bibliographically approved
van Dongen, E. C. H., Kirchner, N., van Gijzen, M. B., van de Wal, R. S. W., Zwinger, T., Cheng, G., . . . von Sydow, L. (2018). Dynamically coupling full Stokes and shallow shelf approximation for marine ice sheet flow using Elmer/Ice (v8.3). Geoscientific Model Development, 11, 4563-4576
Open this publication in new window or tab >>Dynamically coupling full Stokes and shallow shelf approximation for marine ice sheet flow using Elmer/Ice (v8.3)
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2018 (English)In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 11, p. 4563-4576Article in journal (Refereed) Published
National Category
Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-363123 (URN)10.5194/gmd-11-4563-2018 (DOI)000450295700001 ()
Projects
eSSENCE
Available from: 2018-11-16 Created: 2018-10-12 Last updated: 2019-01-24Bibliographically approved
Bashardanesh, Z. & Lötstedt, P. (2018). Efficient Green's function reaction dynamics (GFRD) simulations for diffusion-limited, reversible reactions. Journal of Computational Physics, 357, 78-99
Open this publication in new window or tab >>Efficient Green's function reaction dynamics (GFRD) simulations for diffusion-limited, reversible reactions
2018 (English)In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 357, p. 78-99Article in journal (Refereed) Published
National Category
Computational Mathematics Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:uu:diva-338758 (URN)10.1016/j.jcp.2017.12.025 (DOI)000427393800004 ()
Available from: 2017-12-21 Created: 2018-01-12 Last updated: 2019-10-14Bibliographically approved
Engblom, S., Lötstedt, P. & Meinecke, L. (2018). Mesoscopic modeling of random walk and reactions in crowded media. Physical Review E. Statistical, Nonlinear, and Soft Matter Physics, 98, 033304:1-16, Article ID 033304.
Open this publication in new window or tab >>Mesoscopic modeling of random walk and reactions in crowded media
2018 (English)In: Physical Review E. Statistical, Nonlinear, and Soft Matter Physics, ISSN 1539-3755, E-ISSN 1550-2376, Vol. 98, p. 033304:1-16, article id 033304Article in journal (Refereed) Published
National Category
Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-360450 (URN)10.1103/PhysRevE.98.033304 (DOI)000444574600010 ()
Projects
UPMARCeSSENCE
Available from: 2018-09-11 Created: 2018-09-13 Last updated: 2018-11-15Bibliographically approved
Cheng, G., Lötstedt, P. & von Sydow, L. (2017). Accurate and stable time stepping in ice sheet modeling. Journal of Computational Physics, 329, 29-47
Open this publication in new window or tab >>Accurate and stable time stepping in ice sheet modeling
2017 (English)In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 329, p. 29-47Article in journal (Refereed) Published
National Category
Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-309278 (URN)10.1016/j.jcp.2016.10.060 (DOI)000390511500003 ()
Projects
eSSENCE
Available from: 2016-11-02 Created: 2016-12-02 Last updated: 2019-09-01Bibliographically approved
Engblom, S., Hellander, A. & Lötstedt, P. (2017). Multiscale simulation of stochastic reaction–diffusion networks. In: Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology: (pp. 55-79). Springer
Open this publication in new window or tab >>Multiscale simulation of stochastic reaction–diffusion networks
2017 (English)In: Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology, Springer, 2017, p. 55-79Chapter in book (Refereed)
Place, publisher, year, edition, pages
Springer, 2017
National Category
Computational Mathematics Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:uu:diva-331828 (URN)10.1007/978-3-319-62627-7_3 (DOI)978-3-319-62626-0 (ISBN)
Projects
eSSENCE
Available from: 2017-10-05 Created: 2017-10-18 Last updated: 2018-11-12Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-2143-3078

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