Analysis of long-term weather, snow and avalanche data at Glacier National Park, B.C., Canada
Bibliographic record
Abstract
Long-term changes of the global climate system have been observed. However, the effect of long-term changes in the climate system on avalanche hazard in mountainous areas remains inconclusive. For this study we analyzed long-term weather, snow cover, and avalanche data from Glacier National Park. Weather and snow cover data were measured at two sites (1315 m and 1905 m a.s.l.). The avalanche data were observed along the section of the Trans Canada Highway within the park. Meteorological data were analyzed by winter season, i.e. early, mid and late winter, represented by three-month periods between September and May. Increasing trends were found for the mean seasonal air temperature at both stations during the mid season. Trends for the solid precipitation rate were not significant, indicating no trend towards more rain events. Decreasing trends of the maximum snow depth were only found for the lower elevation station at Rogers Pass for the mid and late season, which is consistent with decreasing trends for all seasons of the mean 24-hour new snow amounts at the lower elevation and for the mid season at the higher elevation station at Mt. Fidelity. Due to uncertainty arising from changes in explosive control, we draw no conclusions regarding the regional change of avalanche activity. However, the weather and snowpack trends observed in Glacier National Park are consistent with longer time series from mountains with similar latitudes and elevations in France and Switzerland.
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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 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| 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".