Bibliographic record
Abstract
Abstract A notable characteristic of the summertime Arctic is the existence of a narrow band of strong horizontal temperature gradients spanning the coastlines of Siberia, Alaska, and western Canada that extends through a considerable depth of the troposphere. Past research has associated this summer Arctic Frontal Zone (AFZ) with contrasts in atmospheric heating between the Arctic Ocean and snow-free land, with its regional strength strongly influenced by topography; however, little is known about its variability. In this study, output from the latest generation of global atmospheric reanalyses is used to better constrain and define the summer AFZ, including its spatial and seasonal characteristics. The relative importance of different factors linked to its variability is then evaluated. The AFZ is best expressed in July and is manifested aloft as a separate Arctic jet feature at about 250 hPa. It is clearly associated with differential atmospheric heating, as evidenced by the sharp difference in surface energy balance terms between the Arctic Ocean and land. Furthermore, the AFZ is strongest over the coastline whether observed near the surface or throughout the troposphere. Interannual variations in peak strength of the AFZ are spatially heterogeneous and systematic near the surface (the 2-m level). Spatiotemporal variability is primarily dependent on factors affecting temperature over land, especially variability in cloud cover, surface wind direction, and the timing of the annual snow cover retreat. Local variability in the timing of annual sea ice retreat is also important through its control on temperatures over coastal seas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".