The Impact of Snow Accumulation on the Active Layer Thermal Regime in High Arctic Soils
Bibliographic record
Abstract
This study quantifies the impacts of snow augmentation and the timing of snow accumulation on the soil thermal regime at the Cape Bounty Arctic Watershed Observatory (CBAWO), in the Canadian High Arctic. Monthly soil temperatures between December and March 2006–2007 were 7.7 to 9.9°C warmer beneath a deep drift (54 cm) relative to soils beneath ambient (unamended or background) snow conditions (10 cm). Although air temperatures and total snow accumulation at the sites in 2007–2008 were very similar to the previous winter, the mean monthly soil temperatures beneath two snow drifts (50 and 88 cm) were only 0.2 to 5.7°C warmer for January through March than soils subject to ambient snow depths (18 and 35 cm). Results demonstrate that the timing of snow accumulation was more important than snow depth in determining winter soil temperatures. In 2006–2007, snow cover insulated soils by early November, while in 2007–2008 there was insufficient snow cover to insulate soils until late January 2008. In 2006–2007, winter (December–March) soil temperatures beneath the deepest snow (54 cm) exceeded winter air temperatures by 6°C, and mean annual air temperatures by 1°C, while in 2007–2008 winter soil temperatures beneath 88 cm of snow were only 0.3°C warmer than air, and mean annual temperatures were 2.4°C cooler than air. There was a weak but significant inverse correlation between the maximum active layer thickness and the snow depth; however, this correlation was more pronounced for snow depths below approximately 30 cm. This study demonstrates that an understanding of the timing of projected increases in winter precipitation is necessary to predict changes in the active layer's thermal, hydrological, and biogeochemical response to regional climate change.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".