Melting on glaciers: environmental controls examined with orbiting radar
Bibliographic record
Abstract
Abstract Direct, in situ measurements of glacier mass balance are expensive. Remote sensing would be an attractive alternative if remotely observable quantities could be interpreted in terms of mass gain or loss. A system developed recently for the analysis of Radarsat browse images is used here to explore temporal and environmental controls of melting on glaciers on Axel Heiberg Island, Nunavut, Canada. The browse images have an effective spatial resolution of 2 km, are georeferenced to single‐pixel accuracy, and number about 200 over the two study years, 1998 and 1999. Surface melting in the accumulation zone is readily recognized by the contrast between bright frozen firn, which exhibits a microwave signal dominated by volume scattering from ice lenses and pipes, and dark wet firn, the signal from which is muted by either absorption or near‐specular reflection at the surface. In the ablation zone, radar images, apart from showing the brief spring period of snowmelt, contain little information about the intensity or even the fact of melting. However, in the accumulation zone there is a definite dependence of brightness on temperature: at temperatures above freezing, the hotter it is the darker is the appearance of the glacier. This is most naturally (and encouragingly) interpreted as a relation between brightness and melting rate. Analysis of same‐day image pairs shows that, as expected, the terrain slope and the aspect influence the radar brightness strongly and must therefore be allowed for in future modelling of the hydrology of ablation on glaciers. Copyright © 2001 John Wiley & Sons, Ltd.
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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) | 0.002 | 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".