An Inferred Climatology of Icing Conditions Aloft, Including Supercooled Large Drops. Part I: Canada and the Continental United States
Bibliographic record
Abstract
Abstract Because of a lack of regular, direct measurements, little information is available about the frequency and spatial and temporal distribution of icing conditions aloft, including supercooled large drops (SLD). Research aircraft provide in situ observations of these conditions, but the sample set is small and can be biased. Other techniques must be used to create a more unbiased climatology. The presence and absence of icing and SLD aloft can be inferred using surface weather observations in conjunction with vertical profiles of temperature and moisture. In this study, such a climatology was created using 14 yr of coincident, 12-hourly Canadian and continental U.S. surface weather reports and balloonborne soundings. The conditions were found to be most common along the Pacific Coast from Alaska to Oregon, and in a large swath from the Canadian Maritimes to the Midwest. Prime locations migrated seasonally. Most SLD events appeared to occur below 4 km, were less than 1 km deep, and were formed via the collision–coalescence process.
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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 | 0.000 |
| 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 | 0.000 |
| 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".