Diurnal Cycles of Meltwater Percolation, Refreezing, and Drainage in the Supraglacial Snowpack of Haig Glacier, Canadian Rocky Mountains
Why this work is in the frame
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Bibliographic record
Abstract
Meltwater refreezing and storage in the supraglacial snowpack can reduce and delay meltwater runoff from glaciers. These are well-established processes in polar environments, but the importance of meltwater refreezing and the efficiency of meltwater drainage are uncertain on temperate alpine glaciers. To examine these processes and quantify their importance on a mid-latitude mountain glacier, we measured the temperature and meltwater content in the upper 50 cm of the supraglacial snowpack of Haig Glacier in the Canadian Rocky Mountains. Thermistors and TDR probes were installed at 10-cm intervals at two sites in the glacier accumulation area from May to September, 2015. A Denoth meter was used to make point measurements for comparison with the TDR inferences of snowpack dielectric properties. These data are supplemented by automatic weather station data, used to calculate surface melt rates and drive a model of subsurface temperature, refreezing, and drainage. We observed a strong diurnal cycle in snow water content throughout the summer melt season, but subsurface refreezing was only significant in May; after this, overnight refreezing was restricted to a thin surface layer of the snowpack. Overnight decreases in water content after May are associated with meltwater percolation and drainage. There was negligible meltwater retention in the snow on a daily basis, but the refrozen water does represent an ‘energy sink’, with 10-15% of the available melt energy diverted to recycled rather than new meltwater. This reduces the total meltwater runoff from the site, even though no meltwater is retained in the system.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it