Effects of meteorology and soil moisture on the spatio-temporal evolution of the depth hoar layer in the polar desert snowpack
Bibliographic record
Abstract
Abstract In polar deserts, depth hoar (hereinafter: DH) growth is not systematic unlike on tundra and this is critical for snowpack properties. Here, we address the spatio-temporal variability of the DH layer in the polar desert at two sites in the Canadian High Arctic: Ward Hunt Island (83° N) and Resolute Bay (75° N). Our data show that, over humid areas, DH represented a larger fraction of the snowpack and was characterized by lower density and coarser crystals than over dry gravelly areas. Increased soil moisture extends the zero-curtain period during freeze-up, leading to stronger temperature gradients in the snowpack and greater kinetic metamorphism. Our results also demonstrate that the large inter-annual variability in DH is primarily driven by wind conditions in the fall since this key variable controls the initial snow density and snow onset date. These strong controls exerted by soil moisture and meteorological conditions on DH growth in polar deserts highlight the possibility of major changes in polar snowpacks physical properties in response to the rapid climate and environmental changes currently affecting these regions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".