Modelling the delivery of supraglacial meltwater to the ice/bed interface: application to southwest Devon Ice Cap, Nunavut, Canada
Bibliographic record
Abstract
Abstract The transfer of surface-generated meltwater to the subglacial drainage system through full ice thickness crevassing may lead to accelerated glacier velocities, with implications for ice motion under future climatic scenarios. Accurate predictions of where surface meltwater accesses the ice/bed interface are therefore needed in fully coupled hydrodynamic ice-sheet models. We present a spatially distributed modelling routine for predicting the location and timing of delivery of surface-derived meltwater to the ice/bed interface through moulins and supraglacial lake drainage. The model is explained as it is applied to the Croker Bay glacial catchment of Devon Ice Cap, Canada. The formation of moulins, drainage of lakes, and the transfer of meltwater through the full ice thickness are modelled for the 2004 and 2006 ablation seasons. Through this case study we assess the model’s sensitivity to degree-day factors, fracture toughness, tensile strength and crevasse width, and confirm that parameters influencing the rate at which water fills a crevasse are the most significant controls on the ability of a crevasse to reach the bed. Increased surface melt production, therefore, has the potential to significantly influence the spatial and temporal transfer of meltwater through surface-to-bed connections in a warmer climate
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".