Surface albedo observations of Hudson Bay (Canada) landfast sea ice during the spring melt
Bibliographic record
Abstract
Abstract The shortwave albedo is a major component in determining the surface energy balance and thus the evolution of the spring melt cycle. As the melt commences, the ice is partitioned into multiple surface types ranging from highly reflective white ice to absorptive blue ice. The reflectance from these surfaces shows significant spatial and temporal variability. Spectral albedo measurements were made at six different sites encompassing these two surface types, from 19 March to 3 May 2005, on 1.5 m thick landfast sea ice in southwestern Hudson Bay, Canada (58˚ N). Furthermore, the broadband albedo and the surface energy balance were continuously recorded at a nearby site during the 1 month period. Rapid changes in the albedo were found to relate to typical subarctic climate conditions, i.e. frequent incursions of southerly air, resulting snow and rain events and the generally high maximum solar insolation levels. Subsequently, diurnal variations in snow surface temperature were evident, often causing daytime melting and night-time refreezing resulting in the formation of ice lenses and superimposed ice. After rain events and extensive melting, the snowpack was transformed throughout into melt/freeze metamorphosed snow and superimposed ice. The integrated (350–1050 nm) albedo varied between 0.52 and 0.95 at the blue-ice sites, while it varied between 0.73 and 0.91 at white-ice sites. Variability on the order of ±10% in the white-ice broadband albedo resulted from the diurnal freeze–thaw cycle, but also synoptic weather events, such as snowfall and rain events, could rapidly change the surface conditions.
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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) | 0.000 | 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".