A moving-point approach to model shallow ice sheets: a study case with radially symmetrical ice sheets

Bonan, Bertrand; Baines, M. J.; Nichols, Nancy K.; Partridge, Dale

doi:10.5194/tc-10-1-2016

Cited by 12 publications

(37 citation statements)

References 32 publications

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“…One of the points is dedicated to the static ice divide at r = 0, while another point tracks the position of the margin r l (t), which moves at the velocity (Bonan et al, 2016) dr…”

Section: Moving Point Methodsmentioning

confidence: 99%

“…2.2, a finite difference algorithm is derived (see Bonan et al, 2016 for the full algorithm). The mesh consists of n r moving nodes with the positions 0 =r 1 <r 2 < .…”

Section: Numerical Modelmentioning

confidence: 99%

“…The major advantage of our moving mesh method is that only a small number of mesh steps are needed to accurately determine the positions of the boundaries, unlike fixed or adaptive mesh methods (Berger and Oliger, 1984;Li et al, 2014;Cornford et al, 2013Cornford et al, , 2016Gladstone et al, 2010). Our moving mesh method has been successfully applied to a number of moving boundary problems, including one-and two-dimensional models of ice sheet flow, tumour growth and chemical spreading (Partridge, 2013;Bonan et al, 2016;Lukyanov et al, 2012;Lee et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Lorenc, 1986;Nichols, 2010) and an ensemble transform Kalman filter (ETKF; see Bishop et al, 2001;Hunt et al, 2007), to estimate the state of an ice sheet modelled by our moving mesh method (Bonan et al, 2016). The approach is validated by twin experiments using available classical surface observations (surface elevation and surface velocity; see Vaughan et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Our moving mesh numerical method for ice flow has already been validated for both 1-D and 2-D models of ice sheets (Partridge, 2013;Bonan et al, 2016). In this paper, we describe the application of data assimilation to the moving mesh method and demonstrate the combined techniques using a one-dimensional moving mesh model of a grounded shallow ice sheet as described in Bonan et al (2016). Although the model is relatively simple, there is no reason that these techniques cannot be extended to much more complex problems.…”

Section: Introductionmentioning

confidence: 99%

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

Bonan

Nichols

Baines

et al. 2017

Nonlin. Processes Geophys.

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Abstract. We develop data assimilation techniques for nonlinear 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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“…One of the points is dedicated to the static ice divide at r = 0, while another point tracks the position of the margin r l (t), which moves at the velocity (Bonan et al, 2016) dr…”

Section: Moving Point Methodsmentioning

confidence: 99%

“…2.2, a finite difference algorithm is derived (see Bonan et al, 2016 for the full algorithm). The mesh consists of n r moving nodes with the positions 0 =r 1 <r 2 < .…”

Section: Numerical Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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

Bonan

Nichols

Baines

et al. 2017

Nonlin. Processes Geophys.

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Influences and interactions of inundation, peat, and snow on active layer thickness

Atchley

Coon

Painter

et al. 2016

Geophysical Research Letters

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Active layer thickness (ALT), the uppermost layer of soil that thaws on an annual basis, is a direct control on the amount of organic carbon potentially available for decomposition and release to the atmosphere as carbon‐rich Arctic permafrost soils thaw in a warming climate. We investigate how key site characteristics affect ALT using an integrated surface/subsurface permafrost thermal hydrology model. ALT is most sensitive to organic layer thickness followed by snow depth but is relatively insensitive to the amount of water on the landscape with other conditions held fixed. The weak ALT sensitivity to subsurface saturation suggests that changes in Arctic landscape hydrology may only have a minor effect on future ALT. However, surface inundation amplifies the sensitivities to the other parameters and under large snowpacks can trigger the formation of near‐surface taliks.

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Are polar bear habitat resource selection functions developed from 1985–1995 data still useful?

Durner

Douglas

Atwood

2019

Ecology and Evolution

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Greenhouse‐gas‐induced warming in the Arctic has caused declines in sea ice extent and changed its composition, raising concerns by all circumpolar nations for polar bear conservation. Negative impacts have been observed in three well‐studied polar bear subpopulations. Most subpopulations, however, receive little or no direct monitoring, hence, resource selection functions (RSF) may provide a useful proxy of polar bear distributions. However, the efficacy of RSFs constructed from past data, that is, reference RSFs, may be degraded under contemporary conditions, especially in a rapidly changing environment. We assessed published Arctic‐wide reference RSFs using tracking data from adult female polar bears captured in the Beaufort Sea. We compared telemetry‐derived seasonal distributions of polar bears to RSF‐defined optimal sea ice habitat during the period of RSF model development, 1985–1995, and two subsequent periods with diminished sea ice: 1996–2006 and 2007–2016. From these comparisons, we assessed the applicability of the reference RSFs for contemporary polar bear conservation. In the two decades following the 1985–1995 reference period, use and availability of optimal habitat by polar bears declined during the ice melt, ice minimum, and ice growth seasons. During the ice maximum season (i.e., winter), polar bears used the best habitat available, which changed relatively little across the three decades of study. During the ice melt, ice minimum, and ice growth seasons, optimal habitat in areas used by polar bears decreased and was displaced north and east of the Alaska Beaufort Sea coast. As optimal habitat diminished in these seasons, polar bears expanded their range and occupied greater areas of suboptimal habitat. Synthesis and applications: Sea ice declines due to climate change continue to challenge polar bears and their conservation. The distribution of Southern Beaufort Sea polar bears remained similar during the ice maximum season, so the reference RSFs developed from data collected >20 years ago continue to accurately model their winter distribution. In contrast, reference RSFs for the ice transitional and minimum seasons showed diminished predictive efficacy but were useful in revealing that contemporary polar bears have been increasingly forced to use suboptimal habitats during those seasons.

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A moving-point approach to model shallow ice sheets: a study case with radially symmetrical ice sheets

Cited by 12 publications

References 32 publications

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

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

Influences and interactions of inundation, peat, and snow on active layer thickness

Are polar bear habitat resource selection functions developed from 1985–1995 data still useful?

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