Intraseasonal Variations of Winter Wind Chill Temperatures across Canada and the United States
Bibliographic record
Abstract
Abstract Wind chill temperature (WCT) is a measure of the human sensation of cold and also is a parameter used to represent the severity of winter weather. This study provides a unique investigation to quantify the spatial patterns of monthly mean, extreme, and severe WCTs across Canada and the United States. WCT was examined across 45 winters (December–February) spanning 1969/70–2013/14 using 156 surface locations reporting hourly meteorological conditions. Intraseasonal analyses of WCT showed that January had 1) the coldest mean WCTs, 2) the most extreme WCTs as statistically represented by the coldest 1% of the monthly WCT frequency distribution at each surface location, and 3) the greatest frequency of severe WCT hours that were ≤ −32°C. The most extreme WCTs were most often located in the Hudson Bay region of Canada, and north-central and northeastern North America experienced the largest monthly changes in WCT during the winter season. Results suggest that intraseasonal changes of air temperature are the primary influence on variations of WCT and that changes of wind speed are a secondary factor.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".