Modelling the evolution of near-surface ice layers and their impact on runoff generation processes across a High Arctic Ice Cap
Bibliographic record
Abstract
Abstract Near-surface ice layers in the lower accumulation zone of Arctic glaciers and ice sheets may significantly affect deep meltwater percolation and runoff availability. This study presents a framework to assess three methods for characterizing near-surface ice layer permeability and its influence on runoff and mass balance on the Devon Ice Cap using field data. In the most effective method, ice layer permeability depends on temperature and thickness: they remain permeable above a threshold temperature ( T th = −0.15°C) and become impermeable once exceed a critical thickness ( H imp = 1 m). Our modelling replicates ice layers that are typically thinner in the upper accumulation zone and thicker in the lower accumulation zone. Additionally, we simulate an observed increase in the number of ice layers in the upper accumulation zone after 2007. The evolution of thicker (>1 m) ice layers (or ice slab) in the lower accumulation zone reduces meltwater retention through refreezing, making surface mass balance (SMB) and runoff sensitive to climate changes. Simulated mean SMB ranged from −0.09 to 0.26 m w.e. a −1 from 1999 to 2022. Our model can be applied to simulate the long-term evolution of ice slab and project its impact on ice sheet runoff.
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 | 0.000 | 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".