The Influence of High-Frequency Atmospheric Forcing on the Circulation and Deep Convection of the Labrador Sea
Bibliographic record
Abstract
Abstract The influence of high-frequency atmospheric forcing on the circulation of the North Atlantic Ocean with emphasis on the deep convection of the Labrador Sea was investigated by comparing simulations of a coupled ocean–ice model with hourly atmospheric data to simulations in which the high-frequency phenomena were filtered from the air temperature and wind fields. In the absence of high-frequency atmospheric forcing, the strength of the Atlantic meridional overturning circulation and subpolar gyres was found to decrease by 25%. In the Labrador Sea, the eddy kinetic energy decreased by 75% and the average maximum mixed layer depth decreased by between 20% and 110% depending on the climatology. In particular, high-frequency forcing was found to have a greater impact on mixed layer deepening in moderate to warm years whereas in relatively cold years the temperatures alone were enough to facilitate deep convection. Additional simulations in which either the wind or temperature was filtered revealed that the wind, through its impact on the bulk formulas for latent and sensible heat, had a greater impact on deep convection than the temperature.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".