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Abstract Surface melting and lakes are common to Antarctic ice shelves, and their existence and drainages have been invoked as a precursor for ice shelf collapse. Here, we present satellite observations over 2014–2020 of repeated, rapid drainages of a supraglacial lake at the grounding zone of Amery Ice Shelf, East Antarctica. Post‐drainage imagery in 2018 reveals lake bottom features characteristic of rapid, vertical lake drainage. Observed lake volumes indicate drainages are not associated with a threshold meltwater volume. Instead, drainages typically coincide with periods of high daily tidal amplitude, suggesting hydrofracture is assisted by tidally forced ice flexure inherent to the ice shelf grounding zone. Combined with observations of widespread grounding zone lake drainages on Amery, these findings indicate ice shelf meltwater accumulation may be inhibited by grounding zone drainage events, thus representing a potential stabilizing mechanism despite enhanced melting common to these regions.
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Diurnal lake-level cycles on ice shelves driven by meltwater input and ocean tidal tilt
Abstract Diurnal depth cycles of decimeter scale are observed in a supraglacial lake on the McMurdo Ice Shelf, Antarctica. We evaluate two possible causes: (1) tidal tilt of the ice shelf in response to the underlying ocean tide, and (2) meltwater input variation. We find the latter to be the most likely explanation of our observations. However, we do not rule out tidal tilt as a source of centimeter scale variations, and point to the possibility that other, larger supraglacial lake systems, particularly those on ice shelves that experience higher amplitude tidal tilts, such as in the Weddell Sea, may have depth cycles driven by ocean tide. The broader significance of diurnal cycles in meltwater depth is that, under circumstances where the ice shelf is thin, tidal-tilt amplitudes are high, and meltwater runoff rates are large, there may be associated flexure stresses that can contribute to ice-shelf fracture and destabilization. For the McMurdo Ice Shelf (~20–50 m thickness, ~ 1 m tidal amplitude and ~10 cm water-depth variations), these stresses amount to several 10's of kPa.
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- Award ID(s):
- 1841607
- PAR ID:
- 10141735
- Date Published:
- Journal Name:
- Journal of Glaciology
- Volume:
- 66
- Issue:
- 256
- ISSN:
- 0022-1430
- Page Range / eLocation ID:
- 231 to 247
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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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.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1017/jog.2019.98
