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Record W7000682579

Glacier zonation and velocity estimations on Axel Heiberg Island using TerraSAR-X data

2021· other· en· W7000682579 on OpenAlexaboutno aff

Bibliographic record

Venueelib (German Aerospace Center) · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCryospherePermafrostGlacierSea iceArctic geoengineeringArcticArctic ice packAlbedo (alchemy)Ice-albedo feedbackArctic sea ice decline
DOInot available

Abstract

fetched live from OpenAlex

The cryosphere and particularly glaciers and ice sheets play a fundamental role in the global climate system and are strongly influenced by changes in the system itself. The cryosphere refers to frozen components of the Earth system that are at or below the land and ocean surface. These include snow, glaciers, ice sheets, ice shelves, icebergs, sea ice, lake ice, river ice, permafrost, and seasonally frozen ground. As integral parts of the Earth system, the Polar Regions interact with the rest of the world through shared ocean, atmosphere, ecological, and social systems; notably, they are key components of the global climate system. The spatial footprints of the Polar Regions include a vast share of the world’s ocean and cryosphere: they encompass surface areas equalling 20% of the global ocean and more than 90% of the world’s continuous and discontinuous permafrost area, 69% of the world’s glacier area including both of the world’s ice sheets, almost all of the world’s sea ice, and land areas with the most persistent winter snow cover (Meredith et al. 2019).
\nOver the past two decades, Arctic surface temperature has increased by more than twice the global average (Notz and Stroeve 2016; Richter-Menge et al. 2017). Attribution studies show the significant role of anthropogenic increases in greenhouse gases in the observable increase in Arctic surface temperature (Fyfe et al. 2013; Najafi et al. 2015), so there is high confidence in projections of further Arctic warming (Overland et al. 2019). The mechanisms for Arctic amplification are still under debate, but they include decreased albedo in summer due to loss of sea ice and snow cover, increase in total water vapour content in the Arctic atmosphere, changes in total cloud cover in summer, additional heat generated by newly formed sea ice over more extensive open water areas in the fall, transport of heat and moisture northward, and lower rate of heat loss to space from the Arctic (Pithan and Mauritsen 2014).
\nThe Canadian Arctic Archipelago (CAA), located off the north-western coast of Greenland, contains one-third of the global volume of land ice outside the ice sheets (Radić and Hock 2010), but its contribution to sea-level rise remains widely unknown. Gardner et al. (2011) however, suggested, that the CAA has recently lost 61 ±7 gigatons of ice per year (Gt yr-1), which contributes 0.17 ±0.02 mm yr-1 to sea-level rise. A high rate of surface melt in the Canadian Arctic (Gardner et al. 2013; van Wychen et al. 2016) due to persistently high summer air temperatures (Bezeau et al. 2015) was reported. Increased surface melt on Arctic glaciers has led to a direct response through reduced surface albedo causing further melting (Box et al. 2012), and in Svalbard, the mean glacier albedo has decreased between 1979 and 2015 (Möller and Möller 2017). Across the Arctic, increased surface melt and subsequent ice lens formation due to internal refreezing also reduce the ability of glaciers to store meltwater, which increases runoff (Zdanowicz et al. 2012; Gascon et al. 2013; Noël et al. 2018). Between the 1990s and 2017, tidewater glaciers have shown regional patterns in glacier dynamics; glaciers in CAA have largely slowed, while glaciers in Svalbard and the Russian Arctic have accelerated (van Wychen et al. 2016; Strozzi et al. 2017).
\nThis work identified the glacial zones on Axel Heiberg Island using multitemporal TerraSAR-X WideScan (HH polarized) data from 2017 to 2020. This is achieved based on an analysis of the backscatter behaviour of the SAR signal. In order to obtain plausible results, optical (Sentinel-2) satellite images, a digital elevation model, as well as climatological data are used. Seasonal melting and refreezing patterns have been detected, matching to an extent climatological data, in particular the local temperatures. Overall, there is a positive trend, showing a continuous increase, in temperatures. This is reflected in the zonal glacier changes, in the warmer years, more extensive melt zones are more expansive and occur more frequently. 
\nIn addition, glacier flow velocities are determined for White Glacier (Axel Heiberg Island) using offset tracking. A seasonal recurring behaviour can also be identified in the glacier velocities. In the summer months (end of May to mid/end of September), velocities are relatively higher than in the winter months. However, a direct correlation between rising temperatures and increased velocities could not be detected, which may be due to the other factors influencing the glacier velocities. In this context, it is necessary to perform further research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.096
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.075
GPT teacher head0.355
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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