Characteristics of extreme daily precipitation events over the Canadian Arctic
Bibliographic record
Abstract
Abstract Given growing interest in extreme high‐latitude weather events, we use records from nine meteorological stations and atmospheric reanalysis data to examine extreme daily precipitation events (leading, 99th and 95th percentile) over Arctic Canada. Leading events span 90 mm at Cape Dyer, along the southeast coast of Baffin Island, to 26 mm at Sachs Harbour, on the southwest coast of Banks Island. The 95th percentiles range from 20 to 30% of leading event sizes. Extreme events are most common on or near the month of climatological peak precipitation. Contrasting with Eurasian continental sites having a July precipitation peak corresponding to the seasonal peak in precipitable water, seasonal cycles in precipitation and the frequency of extremes over Arctic Canada are more varied, reflecting marine influences. At Cape Dyer and Clyde River, mean precipitation and the frequency of extremes peak in October when the atmosphere is quickly cooling, promoting strong evaporation from Baffin Bay. At all stations, leading events involved snowfall and strong winds and were associated with cyclone passages (mostly of relatively strong storms). They also involved strong vapour fluxes, sometimes associated with atmospheric rivers or their remnants. The most unusual sequence of events identified here occurred at Clyde River, where the three largest recorded precipitation events occurred in April of 1977. Obtaining first‐hand accounts of this series of events has proven elusive. Identified links between extreme events and atmospheric rivers demonstrates the need to better understand how the characteristics of such features will change in the future.
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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 | 0.002 | 0.004 |
| 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) | 0.001 | 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".