Spatial distribution of air‐sea heat fluxes over the sub‐polar North Atlantic Ocean
Bibliographic record
Abstract
On a variety of spatial and temporal scales, the energy transferred by air‐sea heat and moisture fluxes plays an important role in both atmospheric and oceanic circulations. This is particularly true in the sub‐polar North Atlantic Ocean, where these fluxes drive water‐mass transformations that are an integral component of the Atlantic Meridional Overturning Circulation (AMOC). Here we use the ECMWF Interim Reanalysis to provide a high‐resolution view of the spatial structure of the air‐sea turbulent heat fluxes over the sub‐polar North Atlantic Ocean. As has been previously recognized, the Labrador and Greenland Seas are areas where these fluxes are large during the winter months. Our particular focus is on the Iceland Sea region where, despite the fact that water‐mass transformation occurs, the winter‐time air‐sea heat fluxes are smaller than anywhere else in the sub‐polar domain. We attribute this minimum to a saddle point in the sea‐level pressure field, that results in a reduction in mean surface wind speed, as well as colder sea surface temperatures associated with the regional ocean circulation. The magnitude of the heat fluxes in this region are modulated by the relative strength of the Icelandic and Lofoten Lows, and this leads to periods of ocean cooling and even ocean warming when, intriguingly, the sensible and latent heat fluxes are of opposite sign. This suggests that the air‐sea forcing in this area has large‐scale impacts for climate, and that even modest shifts in the atmospheric circulation could potentially impact the AMOC.
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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".