Adaptive mesh, finite volume modeling of marine ice sheets

Cornford, Stephen; Martín, Daniel; Graves, Daniel; Ranken, D. F.; Brocq, A. M. Le; Gladstone, Rupert; Payne, Antony J.; Ng, Esmond G.; Lipscomb, William H.

doi:10.1016/j.jcp.2012.08.037

Cited by 231 publications

(316 citation statements)

References 54 publications

(92 reference statements)

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“…They also demonstrate that moving grid models explicitly tracking grounding line position are able to reduce the dependency of results on mesh resolution. Analyses on 2-D plan-view or 3-D models confirm these results (Goldberg et al, 2009;Cornford et al, 2013). Recent results using plan-view shallow models and finite differences (Feldmann et al, 2014) also show that including grounding line sub-grid parameterization in shallow models allows to capture grounding line reversibility at low resolutions without including a flux correction.…”

Section: H Seroussi Et Al: Grounding Line Parameterizationmentioning

confidence: 57%

“…Using sub-grid parameterization, which tracks the grounding line position within the element, improves models based on hydrostatic equilibrium condition and reduces their dependency on grid size (Pattyn et al, 2006;Gladstone et al, 2010a;Winkelmann et al, 2011). Another alternative is to use moving grid or adaptive mesh refinement, so that the mesh or grid resolution follows the grounding line transition zone (Goldberg et al, 2009;Cornford et al, 2013). These methods overcome the difficulties associated to grounding line discretization but lead to more complicated frameworks and remain difficult to implement in parallelized architectures.…”

Section: H Seroussi Et Al: Grounding Line Parameterizationmentioning

confidence: 99%

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Hydrostatic grounding line parameterization in ice sheet models

et al. 2014

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Abstract. Modeling of grounding line migration is essential to accurately simulate the behavior of marine ice sheets and investigate their stability. Here, we assess the sensitivity of numerical models to the parameterization of the grounding line position. We run the MISMIP3D benchmark experiments using the Ice Sheet System Model (ISSM) and a two-dimensional shelfy-stream approximation (SSA) model with different mesh resolutions and different sub-element parameterizations of grounding line position. Results show that different grounding line parameterizations lead to different steady state grounding line positions as well as different retreat/advance rates. Our simulations explain why some vertically depth-averaged model simulations deviate significantly from the vast majority of simulations based on SSA in the MISMIP3D benchmark. The results reveal that differences between simulations performed with and without sub-element parameterization are as large as those performed with different approximations of the stress balance equations in this configuration. They also demonstrate that the reversibility test is passed at relatively coarse resolution while much finer resolutions are needed to accurately capture the steady-state grounding line position. We conclude that fixed grid SSA models that do not employ such a parameterization should be avoided, as they do not provide accurate estimates of grounding line dynamics, even at high spatial resolution. For models that include sub-element grounding line parameterization, in the MISMIP3D configuration, a mesh resolution finer than 2 km should be employed.

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Section: H Seroussi Et Al: Grounding Line Parameterizationmentioning

confidence: 57%

Section: H Seroussi Et Al: Grounding Line Parameterizationmentioning

confidence: 99%

Hydrostatic grounding line parameterization in ice sheet models

et al. 2014

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“…The BISICLES adaptive mesh ice sheet model used in this study is described in detail in Cornford et al (2013). It employs a vertically integrated model based on Schoof and Hindmarsh (2010) which includes longitudinal and lateral strains and a simplified treatment of vertical shear strain and is best suited to ice shelves and fast flowing ice streams.…”

Section: Ice Sheet Modelmentioning

confidence: 99%

“…As the resolution of the mesh evolves with time to follow the grounding line (Cornford et al, 2013), this model is well suited to studying grounding line migration and dynamic thinning in the region of the Amery Ice Shelf. In order to assess the response of the drainage system to uncertain climate forcing in 21st and 22nd centuries we consider 1. ice thickness and velocity change and grounding line migration 2. contribution to global sea level change 3. and the differing roles of accumulation and sub ice-shelf melting as well as the influence of topographic features on the dynamics of the system.…”

Section: Introductionmentioning

confidence: 99%

Modelling the response of the Lambert Glacier–Amery Ice Shelf system, East Antarctica, to uncertain climate forcing over the 21st and 22nd centuries

2014

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Abstract. The interaction between the climate system and the large polar ice sheet regions is a key process in global environmental change. We carried out dynamic ice simulations of one of the largest drainage systems in East Antarctica: the Lambert Glacier-Amery Ice Shelf system, with an adaptive mesh ice sheet model. The ice sheet model is driven by surface accumulation and basal melt rates computed by the FESOM (Finite-Element Sea-Ice Ocean Model) ocean model and the RACMO2 (Regional Atmospheric Climate Model) and LMDZ4 (Laboratoire de Météorologie Dynamique Zoom) atmosphere models. The change of ice thickness and velocity in the ice shelf is mainly influenced by the basal melt distribution, but, although the ice shelf thins in most of the simulations, there is little grounding line retreat. We find that the Lambert Glacier grounding line can retreat as much as 40 km if there is sufficient thinning of the ice shelf south of Clemence Massif, but the ocean model does not provide sufficiently high melt rates in that region. Overall, the increased accumulation computed by the atmosphere models outweighs ice stream acceleration so that the net contribution to sea level rise is negative.

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“…The alternative to their approach is to solve the equation in the boundary layer numerically, which must account for the much greater accuracy required there. This requires more advanced techniques, such as adaptive nested grids (Gladstone et al, 2010;Cornford et al, 2013;Feldmann et al, 2014) or higher-order methods. These methods have yet to be published in full, but results of an initial inter-comparison can be found in Pattyn et al (2012).…”

mentioning

confidence: 99%