A new look at Greenland flow distortion and its impact on barrier flow, tip jets and coastal oceanography
Bibliographic record
Abstract
A new diagnostic, that partitions the occurrence of high speed surface wind events by wind direction, is described that allows for a more complete view of the atmospheric flow distortion arising from Greenland's high topography. This flow distortion has previously been shown to result in the frequent occurrence of high speed surface wind events in the vicinity of Cape Farewell, Greenland's southernmost point, as well along its southeast coast. This new diagnostic is able to distinguish between easterly and westerly Cape Farewell tip jets. In addition, it clearly identifies the 2 locations along the southeast coast of Greenland where barrier flow is enhanced and confirms previous work that indicated that these locations are collocated with regions of steep coastal topography. It also results in the identification of new regions, the northeast and southwest coasts of Greenland as well as the southeast coast of Iceland, where tip jets and barrier flow also develop. Along the northeast coast, these high speed wind events are proposed to be associated with the formation of the North East Water polynya as well as contributing to the southward advection of sea ice. Along the southwest coast, the high speed wind events, which result in a reversal of the wind direction, may contribute to the enhanced oceanic eddy activity observed to occur in this region.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".