Seasonal Variability in Baffin Bay
Bibliographic record
Abstract
Abstract Three dominant characteristics and underlying dynamics of the seasonal cycle in Baffin Bay are discussed. The study is based on a regional, high‐resolution coupled sea ice‐ocean numerical model that complements our understanding drawn from observations. Subject to forcing from the atmosphere, sea ice, Greenland, and other ocean basins, the ocean circulation exhibits complex seasonal variations that influence Arctic freshwater storage and export. The basin‐scale barotropic circulation is generally stronger (weaker) in summer (winter). The interior recirculation (∼2 Sv) is primarily driven by oscillating along‐topography surface stress. The volume transport along the Baffin Island coast is also influenced by Arctic inflows (∼0.6 Sv) via Smith Sound and Lancaster Sound with maximum (minimum) in June‐August (October‐December). In addition to the barotropic variation, the Baffin Island Current also has changing vertical structure with the upper‐ocean baroclinicity weakened in winter‐spring. It is due to a cross‐shelf circulation associated with spatially variable ice‐ocean stresses that flattens isopycnals. Greenland runoff and sea ice processes dominate buoyancy forcing to Baffin Bay. Opposite to the runoff that freshens the west Greenland shelf, stronger salinification by ice formation compared to freshening by ice melt enables a net densification in the interior of Baffin Bay. Net sea ice formation in the past 30 years contributes to ∼25% of sea ice export via Davis Strait. The seasonal variability in baroclinicity and water mass transformation changes in recent decades based on the simulation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".