The Development of Arctic Air Masses in Northwest Canada and Their Behavior in a Warming Climate
Bibliographic record
Abstract
Surface observations, soundings, and a thermodynamic budget are used to investigate the formation process of 93 arctic airmass events. The events involve very cold surface temperatures—an average of −42.8°C at Norman Wells, a centrally located station in the formation region—and cooling in the 1000–500-hPa layer. A multistage process for their formation in northwestern Canada is proposed. This process is contrary to the classical conceptualization of extremely shallow, surface formations. In the first stage of formation, snow falls into a layer of unsaturated air in the lee of the Rocky Mountains, causing sublimational cooling and moistening the subcloud layer. Simultaneously, the midtroposphere is cooled by cloud-top radiation emissions. In the second stage, snowfall abates, the air column dries, and clear-sky surface radiational cooling predominates, augmented by the high emissivity of fresh snow cover. The surface temperature falls very rapidly, up to a maximum of 18°C day−1 in one event. In the final stage, after near-surface temperatures fall below the frost point, ice crystals and, nearer the surface, ice fog form. At the end of formation, there is cold-air damming, with a cold pool and anticyclone in the lee of the Rockies, lower pressure in the Gulf of Alaska, and an intense baroclinic zone oriented northwest to southeast along the mountains. There have been secular changes in the characteristics of the arctic air masses over the period 1948–2008. The surface temperature during the events has become warmer, and the air masses are deeper and moister. The 1000-hPa diabatic cooling during events, which includes latent heat and radiative processes, has decreased by 2.2°C day−1.
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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 | 0.001 |
| Science and technology studies | 0.002 | 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".