Tip Jets and Barrier Winds: A QuikSCAT Climatology of High Wind Speed Events around Greenland
Bibliographic record
Abstract
Abstract The high topography of Greenland results in a number of orographically induced high wind speed flows along its coast that are of interest from both a severe weather and climate perspective. Here the surface wind field dataset from the NASA–JPL SeaWinds scatterometer on board the Quick Scatterometer (QuikSCAT) satellite is used to develop a wintertime climatology of these flows. The high spatial resolution and the twice-daily sampling of the SeaWinds instrument allows for a much more detailed view of the surface winds around Greenland than has been previously possible. Three phenomena stand out as the most distinctive features of the surface wind field during the winter months: the previously identified tip jets and reverse tip jets, as well as the hitherto unrecognized barrier flows along its southeast coast in the vicinity of the Denmark Strait. Peak surface wind speeds associated with these phenomena can be as large as 50 m s−1 with winds over 25 m s−1 occurring approximately 10%–15% of the time at each location. A compositing technique is used to show that each type of flow is the result of an interaction between a synoptic-scale parent cyclone and the high topography of Greenland. In keeping with previous work, it is argued that tip jets are caused by a combination of conservation of the Bernoulli function during orographic descent and acceleration due to flow splitting as stable air passes around Cape Farewell, while barrier winds are a geostrophic response to stable air being forced against high topography. It is proposed that reverse tip jets occur when barrier winds reach the end of the topographic barrier and move from a geostrophic to a gradient wind balance, becoming supergeostrophic as a result of their anticyclonic curvature.
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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 | 0.001 |
| 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".