Seasonality in the Vertical Structure of Long-Term Temperature Trends Over North America
Bibliographic record
Abstract
The surface warming of northern continents during the twentieth century is not uniform across seasons. Surface warming is particularly pronounced over northwestern Canada, where winter trends are much larger than summer ones. The upper-air temperature trends over the region are analyzed in three radiosonde datasets from 1958 to 2012 to assess their seasonal structure. The seasonal variation of upper-air trends can provide insights into the dynamical and thermodynamical processes generating these trends, including warming at the surface. The focus is not on the canonical structure of secular (i.e., long-term) trends—tropospheric warming and stratospheric cooling—but its seasonal variation. We find the boreal winter-minus-summer difference in trends over northwestern Canada to be positive and large in the lower troposphere (p ≳ 500 hPa) and lower stratosphere (50 hPa ≲ p ≲ 150 hPa); it is largest at the surface and smallest at the tropopause. The decreasing seasonality of the tropospheric trend with height supports the attribution of the notable seasonality of surface warming in this region to both land–surface–hydroclimate interactions and changes in winter circulation. In the lower stratosphere, a cooling trend is evident in all seasons, not unexpectedly, but a pronounced seasonality is again apparent, with the strongest cooling in summer. The near-zero trend tropopause region is a rare point of confluence for seasonal trends.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".