The causes, variability and behaviour in a warming world of the coldest winter-season Canadian temperatures and their associated Arctic air masses
Bibliographic record
Abstract
The coldest surface temperatures in Canada are associated with arctic air masses. These air masses form during the snow-covered and low-sunlight environment of the high-latitude northwest in the winter. This is a region that has been experiencing intense localized surface temperature warming that has not been well captured by climate models. The purpose of this study is to examine the arctic air masses of the region in detail, the larger synoptic context of changes in temperature intensity across Canada in which they are embedded, their thermodynamic properties, and secular changes that they may be experiencing.Trends in temperature anomalies relative to a 30-year running mean were examined, a measure of changes in intensity separated from changes in the mean. Trends towards decreasing variability were found in the southwest and northeast during the winter and trends in increasing variability in the Prairies, southern Ontario and Quebec during mid-winter and in the Atlantic stations in the early-spring. However, no trends were found in the variability of the northwest meaning that even though temperatures inside arctic air masses are increasing, their intensity relative to the 30-year running mean has not been changing.Ninety-three arctic air masses were isolated, using the anomalies calculated relative to the 30-year running mean, and examined. They were found to be deep-layer cold-air damming events associated with an intense anticyclone in the lee of the Canadian Rockies. Using a thermodynamic budget, we find the primary formation mechanism to be diabatic, with cold-air advection playing a small role, counter-balanced by subsidence warming. Sublimation cooling from snowfall at the start of the formation is one of the diabatic processes playing a role. A secular trend toward deeper events was found and decreased radiative cooling during the event, possibly owing to increased cloudiness.In a case study of an intense and long-lived event in February of 1979, moisture was found to be a crucial component in maintaining the cold air. Ice crystals radiatively cool the layer in which they are embedded but settle gravitationally over time or are brought to the ground through subsidence. Moisture must be replenished by precipitation if the air mass is to continue cooling. Moisture transport into the event region is primarily from the upper-levels, 700 hPa, from cyclones in the Gulf of Alaska and from the north over the pole, where it precipitates and falls into the lower-levels.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".