As climate warms and the transition from a perennial to a seasonal Arctic sea-ice cover is imminent, understanding melt ponding is central to understanding changes in the new Arctic. National Aeronautics and Space Administration (NASA)’s Ice, Cloud and land Elevation Satellite (ICESat-2) has the capacity to provide measurements and monitoring of the onset of melt in the Arctic and on melt progression. Yet ponds are currently not identified on the ICESat-2 standard sea-ice products, in which only a single surface is determined. The objective of this article is to introduce a mathematical algorithm that facilitates automated detection of melt ponds in the ICESat-2 Advanced Topographic Laser Altimeter System (ATLAS) data, retrieval of two surface heights, pond surface and bottom, and measurements of depth and width of melt ponds. With ATLAS, ICESat-2 carries the first spaceborne multibeam micropulse photon-counting laser altimeter system, operating at 532-nm frequency. ATLAS data are recorded as clouds of discrete photon points. The Density-Dimension Algorithm for bifurcating sea-ice reflectors (DDA-bifurcate-seaice) is an autoadaptive algorithm that solves the problem of pond detection near the 0.7-m nominal along-track spacing of ATLAS data, utilizing the radial basis function for calculation of a density field and a threshold function that automatically adapts to changes in the background, apparent surface reflectance, and some instrument effects. The DDA-bifurcate-seaice is applied to large ICESat-2 datasets from the 2019 and 2020 melt seasons in the multiyear Arctic sea-ice region. Results are evaluated by comparison with those from a manually forced algorithm.
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The 32-year record-high surface melt in 2019/2020 on the northern George VI Ice Shelf, Antarctic Peninsula
Abstract. In the 2019/2020 austral summer, the surface melt duration andextent on the northern George VI Ice Shelf (GVIIS) was exceptional comparedto the 31 previous summers of distinctly lower melt. This finding is basedon analysis of near-continuous 41-year satellite microwave radiometer andscatterometer data, which are sensitive to meltwater on the ice shelfsurface and in the near-surface snow. Using optical satellite imagery fromLandsat 8 (2013 to 2020) and Sentinel-2 (2017 to 2020), record volumes ofsurface meltwater ponding were also observed on the northern GVIIS in2019/2020, with 23 % of the surface area covered by 0.62 km3 of ponded meltwater on 19 January. These exceptional melt andsurface ponding conditions in 2019/2020 were driven by sustained airtemperatures ≥0 ∘C for anomalously long periods (55 to 90 h)from late November onwards, which limited meltwater refreezing.The sustained warm periods were likely driven by warm, low-speed (≤7.5 m s−1) northwesterly and northeasterly winds and not by foehn windconditions, which were only present for 9 h total in the 2019/2020 meltseason. Increased surface ponding on ice shelves may threaten theirstability through increased potential for hydrofracture initiation; a riskthat may increase due to firn air content depletion in response tonear-surface melting.
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- Award ID(s):
- 1841607
- NSF-PAR ID:
- 10220023
- Date Published:
- Journal Name:
- The Cryosphere
- Volume:
- 15
- Issue:
- 2
- ISSN:
- 1994-0424
- Page Range / eLocation ID:
- 909 to 925
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5194/tc-15-909-2021
