Interannual transport variability of Upper Labrador Sea Water at Flemish Cap
Bibliographic record
Abstract
The transport of Upper Labrador Sea Water (ULSW) at Flemish Cap (47°N/45°W) is investigated in the period 1960–2009 using the output from an 8 km resolution numerical ocean model. The average model transport of ULSW decreases southward from 6.7 Sv at 53°N to 4.5 Sv at 45°N due to interior pathways. The largest fraction of the total ULSW volume transport goes around Flemish Cap within the Deep Western Boundary Current (DWBC, 72%) but a significant part goes through Flemish Pass (20%). At interannual timescales, the variability at Flemish Pass shows a distinct behavior when compared to the variability in the DWBC and to the upstream fluctuations. A running correlation method is applied to obtain the connection of the transport variability at Flemish Pass with several quantities, representative for different physical mechanisms: (1) the North Atlantic Oscillation index, (2) the Ekman transport, (3) the rate of ULSW formation in the Labrador Sea, (4) the position of the North Atlantic Current (NAC) relative to the slope and (5) the averaged transport in the subpolar gyre. Weakened or strengthened transport of ULSW through Flemish Pass coincides with changes of the atmospheric forcing or with changes of the NAC‘s position. Strong meandering of the NAC close to the DWBC reduces the transport off Flemish Cap, and the ULSW flow is “redirected” into the Flemish Pass, enhancing the transport there. In contrast, the transport variability in the DWBC is mainly caused by upstream fluctuations and changes according to the rate of ULSW formation.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".