What Caused the Remarkable February 2018 North Greenland Polynya?
Bibliographic record
Abstract
Abstract During late February and early March 2018, an unusual polynya was observed off the north coast of Greenland. This period was also notable for the occurrence of a sudden stratospheric warming. Here we use satellite and in situ data, a reanalysis and an ice‐ocean model to document the evolution of the polynya and its synoptic forcing. We show that its magnitude was unprecedented and that it was associated with the transient response to the sudden stratospheric warming leading to anomalous warm southerly flow in north Greenland. Indeed, regional wind speeds and temperatures were the highest during February going back to the 1960s. There is evidence that the thinning sea ice has increased its wind‐driven mobility. However, we show that the polynya would have developed under thicker ice conditions representative of the late 1970s and that even with the predicted trend toward thinner sea ice, it will only open during enhanced southerly flow.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".