Spatio-temporal variability of processes across Antarctic ice-bed–ocean interfaces

Understanding how the Antarctic ice sheet will respond to global warming relies on knowledge of how it has behaved in the past. The use of numerical models, the only means to quantitatively predict the future, is hindered by limitations to topographic data both now and in the past, and in knowledge...

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Vydáno v:Nature communications Ročník 9; číslo 1; s. 2289 - 14
Hlavní autoři: Colleoni, Florence, De Santis, Laura, Siddoway, Christine S., Bergamasco, Andrea, Golledge, Nicholas R., Lohmann, Gerrit, Passchier, Sandra, Siegert, Martin J.
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Nature Publishing Group UK 18.06.2018
Nature Publishing Group
Nature Portfolio
Témata:
704/106/125
704/106/2738
704/106/413
704/2151/210
Aquifers
Climate change
Deformation
Global warming
Humanities and Social Sciences
Hydrologic models
Hydrology
Ice sheets
Ice shelves
Interfaces
Mathematical models
Morphology
multidisciplinary
Review
Review Article
Science
Science (multidisciplinary)
Sediments
Topography
ISSN:2041-1723, 2041-1723
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Popis
Shrnutí:Understanding how the Antarctic ice sheet will respond to global warming relies on knowledge of how it has behaved in the past. The use of numerical models, the only means to quantitatively predict the future, is hindered by limitations to topographic data both now and in the past, and in knowledge of how subsurface oceanic, glaciological and hydrological processes interact. Incorporating the variety and interplay of such processes, operating at multiple spatio-temporal scales, is critical to modeling the Antarctic’s system evolution and requires direct observations in challenging locations. As these processes do not observe disciplinary boundaries neither should our future research. Understudied in the Antarctic system are the subsurface interfaces between ice-sheet, ocean and geological substrate. Here, the authors review our understanding of these components and propose new avenues of holistic dynamic modeling to achieve a unified understanding of past, present and future polar climate.
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ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-018-04583-0