Extratropical Cyclones and Precipitation within the Canadian Archipelago during the Cold Season
Bibliographic record
Abstract
Extratropical cyclones produce much of the precipitation over the Arctic, but the details of this cause-effect relationship are not well documented. In this study, we examined extratropical cyclones within the Canadian Archipelago, a subregion of the Arctic, over the period 1948– 97. Using data from the Historical Canadian Climate Data (HCCD), the U.S. National Climate Center (UNCC), and the European Meteorological Bulletin (EMB), we assessed the relationship between extratropical cyclones and cold-season snowfall (October–April) for 10 events at each of 11 surface stations within the region. These events were relatively brief (72 h or less), but resulted in precipitation totals that exceeded the average monthly amount. At each station, within the 10 most extreme precipitation months of the 50-year study period, we often found a single event that accounted for approximately one-third of the total snowfall in that month. For sites located in the southeastern Archipelago, eventrelated storms typically approached from the southeast, whereas southwestern sites were affected by southwesterly storms, and northwestern sites, by northwesterly storms. In many cases, cyclone dissipation occurred within 24 h of the event’s conclusion. Precipitation analyses in this study were considerably affected by snowfall undercatchment; the magnitude of this effect needs further examination in future studies. However, the identification of extreme events and related storm tracks appears to be relatively unaffected by the lack of corrected precipitation data.
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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".