Seasonal and Multi-year Variability of Ice Dynamics of South Croker Bay Glacier, Devon Ice Cap, Canadian Arctic from 2015 to 2021
Bibliographic record
Abstract
The effects of climate change have already been observed across the globe, impacting weather, ecosystems, and society. These effects have been most pronounced in polar regions, which experience warming at a faster rate than other latitudes due to positive feedbacks resulting from reduced ice and snow cover. Compared to the 1.1oC of warming around the globe since the 1980s, the Arctic has warmed by 3oC. Glaciers and ice caps are of particular concern as they have profound impacts on water resources, shipping and travel routes, and global sea level rise. As such, glacier dynamics play a key role in understanding effects on the global system. The Canadian High Arctic in particular has doubled in rates of mass loss since the 1990s, which is of great concern as it is the third largest contributor to global sea level rise after Antarctica and Greenland. While glacier flow within the region has been studied, some glaciers have been observed to not align with current understandings of dynamics. The subject of this study, South Croker Bay Glacier, located on Devon Ice Cap in Nunavut, Canada has exhibited velocity variability on oscillating temporal scales which do not align with surging, pulsing, or consistent acceleration explanations. The primary objective of this thesis was to create a dense record of velocities derived from TerraSAR-X imagery every 11 days from 2015 to 2021 to gain insight into seasonal and multi-annual velocity variability. As a result, a near-continuous velocity record of South Croker Bay Glacier has been created, highlighting a shift in velocities which occurred during the winter of 2018/19. The second objective was to explore the potential drivers of the observed velocity variability, which were hydrology, sea ice buttressing, and bed topography. Looking at the spatial propagation of acceleration and terminus position as well, it is concluded that the variability is not driven by surge- or pulse-type mechanisms. Instead, it is suggested that the driver of the observed variability on the glacier is the result of the evolving configuration of the hydrological network. This is supported by surface air temperature and surface lake area records during the study period. Finally, the third objective was to assess the feasibility of utilizing remote sensing for seasonal variability detection. Based on the analysis, the method was successful in the proposed objectives, creating a record of velocities that was not previously available for South Croker Bay Glacier.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".