Ventilation changes in the Subpolar North Atlantic: Insights from Six Decades of Oxygen Observations and Tracer-Based Age Analysis
Bibliographic record
Abstract
The subpolar North Atlantic assumes a key role in ventilating the ocean’s interior as it is a primary site for deep water formation. Dissolved oxygen concentrations exhibit high sensitivity to climate variability and changes due to the interplay between sea-surface temperature fluctuations and ocean stratification. This relationship not only affects the solubility of dissolved oxygen but also modulates its transport from the near-surface ocean to the interior, known as ventilation. We collected sixty years of observations, spanning from 1960 to 2022, from three different datasets: GLODAPV2, WOD18 and BGC-Argo. These data underwent rigorous secondary quality control process, which adjusted biases between GLODAPV2 and WOD18, as well as BGC-Argo to minimize systematic errors. We conducted an in-depth analysis of the long-term changes and interannual variability in dissolved oxygen, apparent oxygen utilization (AOU), oxygen utilization rate (OUR) and water mass ages within the upper 2000 meters of the water column. Our specific focus encompassed the Subpolar Mode Water (SPMW), Intermediate Water (IW) and Labrador Sea Water (LSW). The computation of OUR and water mass ages in particular relied on tracer data such as chlorofluorocarbons (CFCs) and Sulphur hexafluoride (SF6) to estimate ventilation ages via the Transit Time Distribution (TTD) method. OUR provides insights into local oxygen consumption due to remineralization of organic matter, while the total AOU is the integrated OUR along the pathway of the water parcel. Therefore, identifying these parameters enables to distinguish between the primary drivers behind oxygen variations in the subpolar North Atlantic, namely air-sea gas exchanges, ocean circulation, and marine biology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".