Mass balance of glaciers in the Queen Elizabeth Islands, Nunavut, Canada
Bibliographic record
Abstract
Abstract Mass-balance measurements began in the Canadian High Arctic in 1959. This paper considers the >40 years of measurements made since then, principally on two stagnant ice caps (on Meighen and Melville Islands), parts of two ice caps (the northeast section of Agassiz Ice Cap on northern Ellesmere Island and the northwest part of Devon Ice Cap on Devon Island) and two glaciers (White and Baby Glaciers, Axel Heiberg Island). The results show continuing negative balances. All the glaciers and ice caps except Meighen Ice Cap show weak but significant trends with time towards increasingly negative balances. Meighen Ice Cap may owe its lack of a trend to a cooling feedback from the increasingly open Arctic Ocean nearby (Johannessen and others, 1995). Feedback from this ocean has been shown to be the main cause of this ice cap’s growth and persistence at such a low elevation of <300 ma.s.l. (Alt, 1979). There may be a similar feedback in the lower elevations on Sverdrup Glacier which drains the northwest sector of Devon Ice Cap. The ablation rates there have not increased to the same extent as they have at higher elevations on the same glacier. Although evidence from the meteorological stations in the area shows that the eastern Arctic has either been cooling or has shown no change on an annual basis between 1950 and 1998, the same records show that the summers are showing a slight warming (Zhang and others, 2000). The summer warming, although slight (<1.0˚C over 48 years), is the cause of the weak trend to increasingly negative balances. This is because the mass-balance variability is dominated by the year-to-year variations in the summer balance; there is a very low variability, and no trend over time even within sections of the time series, of the winter balance of the various ice caps and glaciers. Repeat laser altimetry of ice caps by NASA for the period 1995–2000 over most of the ice caps in the Canadian Arctic Archipelago (Abdalati and others, 2004) has shown that the ablation zones are thinning while the accumulation zones show either a slight thickening or very little elevation change. Laser altimetry is revealing similar patterns of change in Greenland (Krabill and others, 2000) and Svalbard (Bamber and others, 2004). The thickening of the accumulation zones in the Canadian case may be due to higher accumulation rates, not just between the two years of laser measurements, but over a period substantially longer than the >40 years of ground-based measurements.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".