Anthropogenic carbon storage and its decadal changes in the Atlantic between 1990–2020
Bibliographic record
Abstract
The Atlantic inventory of anthropogenic carbon (C ant ) and its changes between 1990 and 2020 are investigated by applying the transit time distribution (TTD) method to anthropogenic tracer data. In contrast to previous TTD applications, here we take into account the admixture of old waters free of anthropogenic tracers. The greatest difference from other methods based on direct carbon observations is the higher C ant storage in the deep ocean. Estimations of the decadal C ant increase based on direct carbon observations yield in general a smaller share of C ant storage in the North Atlantic and a larger share in the South Atlantic compared to our results. Changes in oceanic circulation and/or ventilation have significant impacts on the C ant inventory on the regional scale. The enhanced upwelling of older water in the Southern Ocean and the variability in the convection depth in the Labrador Sea lead to deviations in the inferred C ant increase between 1990 and 2020 from the rate equivalent to a steady-state ocean. For the total Atlantic C ant inventory, however, decadal ventilation variability of individual water masses partially compensates for each other. In addition, its impact on the C ant storage is small due to the much higher flushing time for the whole Atlantic of the order of hundreds of years. The total C ant inventory increases from 43.0 ± 7.3 Pg C in 1990 to 68.2 ± 10.8 Pg C in 2020, almost in unison with the rising CO 2 in the atmosphere. So far, ventilation changes have impacted the C ant concentrations only on the regional scale, especially in the subpolar North Atlantic and the Southern Ocean.
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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 | 0.001 | 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) | 0.001 | 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".