Exploring Controls on the Flow Dynamics of Devon Ice Cap using a Basal Friction Inversion
Bibliographic record
Abstract
Accurately predicting the future dynamic contribution to mass loss from the ice caps of the High Arctic requires an improved understanding of the basal conditions of these ice bodies. An adjoint method numerical inversion is therefore applied to elucidate the basal and englacial conditions of Devon Ice Cap in the Canadian Arctic Archipelago, which exhibits a variety of changes to flow dynamics in recent years. These include the surge of Southeast1 and Southeast2 Glaciers, which is suggested to be thermally-regulated. A cryo-hydraulic warming feedback may contribute to the acceleration during this surge as an additional source of heat or water is required for the base of sliding areas to reach pressure melting point. During the active phase of the surge, freezing rates increase as the basal temperature gradient increases dramatically, leading to enhanced conductive heat loss which is not countered by additional frictional heating as the weakened till provides less resistance to flow. The termination of this surge could therefore result from water withdrawal from the underlying till without the need for changes to geometry. Glaciers defined as pulsing consistently had lower basal shear stresses when velocities were higher, but different pulses produced different changes to the basal conditions, making it difficult to suggest a mechanism for these events. The cause of the unequal periods of faster and slower flow observed on the Croker Bay Glaciers also remains uncertain. However, changes to water storage in the till layer are far smaller than interannual variability in surface meltwater reaching the bed, suggesting this could play some role in modulating till strength, thus flow speeds. The bed of Belcher Glacier provides very little resistance to flow near the terminus, supporting the hypothesis that its acceleration is a result of the thinning and retreat of the terminus reducing resistive stresses.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".