The Rainy Continental snow and avalanche climate: International comparison with 40 years of snow cover modeled in the Chic-Chocs, northeastern Appalachian Mountains
Bibliographic record
Abstract
Abstract This study provides a comprehensive analysis of the snow and avalanche climate of the Chic-Chocs region of the Gaspé Peninsula, located in the northeastern Appalachians of eastern Canada. The data revealed two major components of the snow and avalanche climate: a cold snow cover combined with a maritime influence causing melt/ice layers through rain-on-snow events. The CRCM6-SNOWPACK model chain was good at representing the seasonal mean of climatic indicators, snow grain type and an avalanche problem type that well represented the investigated snow and avalanche climate of the study region. The global comparison shows that the snow and avalanche climate is different from other areas in western North America, but similar to Mount Washington (New Hampshire, USA) and central Japan. We show a clustering based solely on avalanche problem types, which showed that the onset date of wet snow problems divided most of the winters into three clusters. We compare these clusters with the French Alps and show some similarities, moving away from a traditional snow and avalanche climate description. The paper concludes that the use of advanced snow cover modeling combined with avalanche problem type characterization represents a suitable method to improve our understanding and classification of snow and avalanche climates for avalanche related problems, ultimately contributing to improved forecasting and risk management in similar regions.
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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".