2012
DOI: 10.1073/pnas.1205385109
|View full text |Cite
|
Sign up to set email alerts
|

Dynamics of the last glacial maximum Antarctic ice-sheet and its response to ocean forcing

Abstract: Retreat of the Last Glacial Maximum (LGM) Antarctic ice sheet is thought to have been initiated by changes in ocean heat and eustatic sea level propagated from the Northern Hemisphere (NH) as northern ice sheets melted under rising atmospheric temperatures. The extent to which spatial variability in ice dynamics may have modulated the resultant pattern and timing of decay of the Antarctic ice sheet has so far received little attention, however, despite the growing recognition that dynamic effects account for a… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

8
147
1

Year Published

2013
2013
2018
2018

Publication Types

Select...
8
1

Relationship

1
8

Authors

Journals

citations
Cited by 138 publications
(156 citation statements)
references
References 45 publications
8
147
1
Order By: Relevance
“…The resolution of the margin positions is determined by both the amount of data available, and the chosen level (scale) of generalisation, which may leave large gaps (uncertainties) in some areas. Filling these gaps will be important if empirically derived ice-margin reconstructions are to keep pace with numerically modelled margin positions at 5 km resolution (Golledge et al, 2012;Pattyn et al, 2012;Seddik et al, 2012). Quantifying uncertainty is particularly important for numerical models using Bayesian calibration to produce probability distributions of the results .…”
Section: Quantifying Uncertainties In Ice Margin Chronologiesmentioning
confidence: 99%
See 1 more Smart Citation
“…The resolution of the margin positions is determined by both the amount of data available, and the chosen level (scale) of generalisation, which may leave large gaps (uncertainties) in some areas. Filling these gaps will be important if empirically derived ice-margin reconstructions are to keep pace with numerically modelled margin positions at 5 km resolution (Golledge et al, 2012;Pattyn et al, 2012;Seddik et al, 2012). Quantifying uncertainty is particularly important for numerical models using Bayesian calibration to produce probability distributions of the results .…”
Section: Quantifying Uncertainties In Ice Margin Chronologiesmentioning
confidence: 99%
“…For large glacial cycle ensembles of continental ice sheets, this is typically in the range of 20 to 50 km. However, with parallelized models able to efficiently distribute the modelling of a single ice sheet over hundreds of processor cores, model runs down to 5 km grid resolution are now possible (Golledge et al, 2012;Seguinot et al, in review). In contrast, climate models are computationally much more expensive, with current Earth-system Models of Intermediate Complexity (EMICS) running at effective resolutions of ~500 km.…”
Section: Model Resolution Parameterisation and Uncertaintymentioning
confidence: 99%
“…Figure 3 shows LGM ice thickness relative to present day for three models: ICE-5G and the output of two recent and independent numerical ice model reconstructions. The latter two are an updated version of the model of Golledge et al (2012), denoted here as G13 (Golledge et al in review) and W12. Other forward models exist (Huybrechts 2002, Pollard and DeConto 2012, Briggs and Tarasov 2013, but these are shown as convenient and recent examples.…”
Section: Ice-sheet Modelsmentioning
confidence: 99%
“…Although marine-terminating glaciers cover only a small fraction of the entire GrIS, modifications at the ice-ocean boundaries due to oceanic changes may considerably affect the inland ice geometry. The effects induced by outlet-glacier acceleration are transferred onshore by ice-flow dynamics, causing adjustments to the entire inland ice-mass configuration (Nick et al, 2009;Fürst et al, 2013;Golledge et al, 2012). For this reason, a full understanding of the interaction between ice and ocean is crucial to assess the response of the GrIS to past and future climate changes.…”
Section: Introductionmentioning
confidence: 99%