Observed acidification trends in North Atlantic water masses
Bibliographic record
Abstract
Abstract. The lack of observational pH data has made it difficult to assess recent rates of ocean acidification, particularly in the high latitudes. Here we present a time series that spans over 27 yr (1981–2008) of high-quality carbon system measurements in the North Atlantic, which comprises fourteen cruises and covers the important water mass formation areas of the Irminger and Iceland Basins. We provide direct quantification of acidification rates in upper and intermediate North Atlantic waters. The highest rates were associated with surface waters and with Labrador Sea Water (LSW). The Subarctic Intermediate and Subpolar Mode Waters (SAIW and SPMW) showed acidification rates of −0.0019 ± 0.0001 and −0.0012 ± 0.0002 yr−1, respectively. The deep convection activity in the North Atlantic Subpolar Gyre injects surface waters loaded with anthropogenic CO2 into lower layers, provoking the remarkable acidification rate observed for LSW in the Iceland Basin (−0.0016 ± 0.0002 yr−1). An extrapolation of the observed linear acidification trends suggests that the pH of LSW could drop 0.45 units with respect to pre-industrial levels by the time atmospheric CO2 concentrations reach ~775 ppm. Under circulation conditions and evolution of CO2 emission rates similar to those of the last three decades, by the time atmospheric CO2 reaches 550 ppm, an aragonite undersaturation state could be reached in the cLSW of the Iceland Basin, earlier than surface SPMW.
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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 | 0.000 | 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".