Oxygen export to the deep ocean following Labrador Sea Water formation
Bibliographic record
Abstract
Abstract. The Labrador Sea in the North Atlantic Ocean is one of the few regions globally where oxygen from the atmosphere can reach the deep ocean directly. This is the result of wintertime convection, which homogenizes the water column to a depth of up to 2000 m, and brings deep water undersaturated in oxygen into contact with the atmosphere. In this study, we analyze how the intense oxygen uptake during Labrador Sea Water (LSW) formation affects the properties of the outflowing deep western boundary current, which ultimately feeds the upper part of the North Atlantic Deep Water layer in much of the Atlantic Ocean. Seasonal cycles of oxygen concentration, temperature, and salinity from a two-year time series collected by sensors moored at 600 m nominal depth in the outflowing boundary current at 53° N show that LSW is primarily exported in the months following the onset of convection, from March to August. During the rest of the year, properties of the outflow resemble those of Irminger Water, which enters the basin with the boundary current from the Irminger Sea. The input of newly ventilated LSW increases the oxygen concentration from 298 μmol L−1 in January to a maximum of 306 μmol L−1 in April. As a result of this LSW input, 1.57 × 1012 mol year−1 of oxygen are added to the outflowing boundary current, mostly during summer, equivalent to 49 % of the wintertime uptake from the atmosphere in the interior of the basin. The export of oxygen from the subpolar gyre associated with this direct southward pathway of LSW is estimated to supply about 71 % of the oxygen consumed annually in the upper North Atlantic Deep Water layer in the Atlantic Ocean between the equator and 50° N. Our results show that the formation of LSW is important for replenishing oxygen to the deep oceans, meaning that possible changes in its formation rate and ventilation due to climate change could have wide-reaching impacts on marine life.
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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 | 0.000 | 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".