Polar Lows and Their Effects on Sea Ice and the Upper Ocean in the Iceland, Greenland, and Labrador Seas
Bibliographic record
Abstract
Abstract Using two case studies, we analyze the effects of explicitly resolving polar lows in a global climate model (ICON‐Sapphire) with a high resolution of 2.5 km on the upper ocean and sea ice. We aim to understand the mechanism of how polar lows form in a global coupled model and how they interact with the upper ocean and sea ice. When polar lows form at the sea ice edge, they induce marine cold air outbreaks that lead to large heat loss from the ocean. This heat loss contributes to dense water formation in the Iceland and Greenland Seas, which replenishes the climatically important Denmark Strait Overflow Water (DSOW). The high wind speeds of polar lows open leads and polynyas in the sea ice cover, such as the Sirius Water Polynya in northeastern Greenland. Heat loss in polynyas is compensated for by the formation of new ice, and the rejected brine densifies the water on the Greenland shelf. In the Labrador Sea, polar lows intensify cold air outbreaks from the sea ice and rapidly deepen the ocean mixed layer. Resolving polar lows and kinematic features in the sea ice improves the realism of climate models, in particular the surface heat loss and the dense water formation in (sub)polar oceans.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".