Atmospheric forcing on the Canadian Arctic Archipelago freshwater outflow and implications for the Labrador Sea variability
Bibliographic record
Abstract
[1] The variability of the freshwater export through the Canadian Arctic Archipelago (CAA) is analyzed using a hindcast simulation forced by surface atmospheric forcing from the ERA40 reanalysis (1958–2001). Although the two channels representing the archipelago in the model are both sensitive to the along-channel sea surface height (SSH) gradient, they appear to have very distinct behaviors. The outflow to Lancaster Sound is shown to be largely controlled by the magnitude of the upstream SSH gradient across McClure Strait. The gradient shows a close link to the wind stress curl in the western Arctic but also to a large-scale SSH anomaly pattern which has a strong signal over the shelf to the south of McClure Strait. The latter has, however, little statistical connection to the SSH variability in the Beaufort Gyre. By contrast, the outflow through Nares Strait responds preferentially to SSH variations in the northern Baffin Bay which are remotely forced by air-sea heat exchanges in the Labrador Sea. The variability is largely coherent between the two outflows and is controlled by a dipolar atmospheric pattern reminiscent of the North Atlantic/Arctic Oscillation. When entering the subpolar gyre, the CAA freshwater outflow remains confined to the Labrador shelf with little impact on the salinity of the interior Labrador Sea and potentially on the convection. The latter is represented by a distinct mode of salinity variability in the western subpolar gyre which is rather influenced by the variability of the sea ice export through Fram Strait.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 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".