A Speed Limit on Ice Shelf Collapse Through Hydrofracture

Robel, Alexander; Banwell, Alison F.

doi:10.1029/2019gl084397

Cited by 83 publications

(82 citation statements)

References 46 publications

(56 reference statements)

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“…Whether this constitutes an emerging consensus between ice sheet models remains to be seen, but it nonetheless illustrates that there is reasonable agreement between models that use traditional ice flow schemes. Since new studies investigating ice shelf hydrofracture (Robel & Banwell, ) and the structural stability of vertical ice cliffs (Clerc et al, ) now appear to show that both processes tend to proceed much less catastrophically, if at all, than initially proposed (Pollard et al, ), the role either of these mechanisms may play in AIS dynamics remains far from well understood.…”

Section: Near‐term Ice Sheet Contributions To Sea‐level Risementioning

confidence: 98%

“…Furthermore, while it is clear that both ice shelf hydrofracture and tidewater glacier calving do occur, they have never been observed at the scale and for the length of time proposed by DeConto and Pollard (). Since their simulations therefore represent a “no‐analogue” state that also requires unrealistically fast ice shelf collapse (Clerc, Minchew, & Behn, ; Robel & Banwell, ), it makes predictions based on these mechanisms very difficult to verify. Equilibrium ice sheet responses and the associated SLR during periods of past warmth (in particular, the mid‐Pliocene warm period, ca.…”

Section: Near‐term Ice Sheet Contributions To Sea‐level Risementioning

confidence: 99%

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Long‐term projections of sea‐level rise from ice sheets

Golledge

2020

WIREs Climate Change

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Under future climate change scenarios it is virtually certain that global mean sea level will continue to rise. But the rate at which this occurs, and the height and time at which it might stabilize, are uncertain. The largest potential contributors to sea level are the Greenland and Antarctic ice sheets, but these may take thousands of years to fully adjust to environmental changes. Modeled projections of how these ice masses will evolve in the future are numerous, but vary both in complexity and projection timescale. Typically, there is greater agreement between models in the present century than over the next millennium. This reflects uncertainty in the physical processes that dominate icesheet change and also feedbacks in the ice-atmosphere-ocean system, and how these might lead to nonlinear behavior. Satellite observations help constrain short-term projections of ice-sheet change but these records are still too short to capture the full ice-sheet response. Conversely, geological records can be used to inform long-term ice-sheet simulations but are prone to large uncertainties, meaning that they are often unable to adequately confirm or refute the operation of particular processes. Because of these limitations there is a clear need to more accurately reconstruct sea level changes during periods of the past, to improve the spatial and temporal extent of current ice sheet observations, and to robustly attribute observed changes to driving mechanisms. Improved future projections will require models that capture a more extensive suite of physical processes than are presently incorporated, and which better quantify the associated uncertainties. This article is categorized under: Climate Models and Modeling > Knowledge Generation with Models K E Y W O R D S Antarctic, climate change, commitment, Greenland, ice sheet

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Section: Near‐term Ice Sheet Contributions To Sea‐level Risementioning

confidence: 98%

Section: Near‐term Ice Sheet Contributions To Sea‐level Risementioning

confidence: 99%

Long‐term projections of sea‐level rise from ice sheets

Golledge

2020

WIREs Climate Change

View full text Add to dashboard Cite

show abstract

“…When used to drive ice sheet models, these climate anomalies are not sufficient to remove the floating ice shelves that buttress ice flow from central Antarctica (20). In an attempt to bypass these problems, ice sheet models have been driven by a wide range of prescribed climate scenarios; however, these suggest widely different sensitivities dependent on model physics and parameterization (21,22), with >2°C (and in some instances >4°C) ocean warming required for the loss of the WAIS, exceeding paleoclimate estimates (3,9,20,23) and different sensitivities of Antarctic ice sheet sectors (18,24,25).…”

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confidence: 99%

Early Last Interglacial ocean warming drove substantial ice mass loss from Antarctica

Turney

Fogwill

Golledge

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

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The future response of the Antarctic ice sheet to rising temperatures remains highly uncertain. A useful period for assessing the sensitivity of Antarctica to warming is the Last Interglacial (LIG) (129 to 116 ky), which experienced warmer polar temperatures and higher global mean sea level (GMSL) (+6 to 9 m) relative to present day. LIG sea level cannot be fully explained by Greenland Ice Sheet melt (∼2 m), ocean thermal expansion, and melting mountain glaciers (∼1 m), suggesting substantial Antarctic mass loss was initiated by warming of Southern Ocean waters, resulting from a weakening Atlantic meridional overturning circulation in response to North Atlantic surface freshening. Here, we report a blue-ice record of ice sheet and environmental change from the Weddell Sea Embayment at the periphery of the marine-based West Antarctic Ice Sheet (WAIS), which is underlain by major methane hydrate reserves. Constrained by a widespread volcanic horizon and supported by ancient microbial DNA analyses, we provide evidence for substantial mass loss across the Weddell Sea Embayment during the LIG, most likely driven by ocean warming and associated with destabilization of subglacial hydrates. Ice sheet modeling supports this interpretation and suggests that millennial-scale warming of the Southern Ocean could have triggered a multimeter rise in global sea levels. Our data indicate that Antarctica is highly vulnerable to projected increases in ocean temperatures and may drive ice–climate feedbacks that further amplify warming.

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“…Supraglacial lakes are of particular importance in Antarctica, where their presence has been shown to induce ice-shelf collapse [29][30][31][32][33], which impacts the flow of upstream ice (e.g., [34][35][36][37][38]) and can trigger dynamic instabilities [39][40][41][42][43]. As Antarctic air temperatures increase, supraglacial lakes will become an increasingly important component of ice sheet mass balance through both direct export via drainage by surface streams [44,45] and meltwater-induced hydrofracturing that can trigger ice-shelf collapse and rapid sea-level rise due to associated dynamic acceleration of interior ice [13].…”

mentioning

confidence: 99%

Antarctic Supraglacial Lake Identification Using Landsat-8 Image Classification

et al. 2020

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Surface meltwater generated on ice shelves fringing the Antarctic Ice Sheet can drive ice-shelf collapse, leading to ice sheet mass loss and contributing to global sea level rise. A quantitative assessment of supraglacial lake evolution is required to understand the influence of Antarctic surface meltwater on ice-sheet and ice-shelf stability. Cloud computing platforms have made the required remote sensing analysis computationally trivial, yet a careful evaluation of image processing techniques for pan-Antarctic lake mapping has yet to be performed. This work paves the way for automating lake identification at a continental scale throughout the satellite observational record via a thorough methodological analysis. We deploy a suite of different trained supervised classifiers to map and quantify supraglacial lake areas from multispectral Landsat-8 scenes, using training data generated via manual interpretation of the results from k-means clustering. Best results are obtained using training datasets that comprise spectrally diverse unsupervised clusters from multiple regions and that include rock and cloud shadow classes. We successfully apply our trained supervised classifiers across two ice shelves with different supraglacial lake characteristics above a threshold sun elevation of 20 • , achieving classification accuracies of over 90% when compared to manually generated validation datasets. The application of our trained classifiers produces a seasonal pattern of lake evolution. Cloud shadowed areas hinder large-scale application of our classifiers, as in previous work. Our results show that caution is required before deploying 'off the shelf' algorithms for lake mapping in Antarctica, and suggest that careful scrutiny of training data and desired output classes is essential for accurate results. Our supervised classification technique provides an alternative and independent method of lake identification to inform the development of a continent-wide supraglacial lake mapping product.

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A Speed Limit on Ice Shelf Collapse Through Hydrofracture

Cited by 83 publications

References 46 publications

Long‐term projections of sea‐level rise from ice sheets

Long‐term projections of sea‐level rise from ice sheets

Early Last Interglacial ocean warming drove substantial ice mass loss from Antarctica

Antarctic Supraglacial Lake Identification Using Landsat-8 Image Classification

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