What determines the simulated strength of the future North Atlantic carbon uptake?
Bibliographic record
Abstract
The North Atlantic is one of the major sinks for anthropogenic carbon in the global ocean, yet future projections of its strength have presently high uncertainties. Here we analyze the mechanisms that determine the projected future North Atlantic carbon uptake of models and identify a list of variables that can be used to assess the associated model performance. We focus on an ensemble of 11 Earth system models and their simulations of a future with high atmospheric CO2. Some of these models simulate that a slowdown in North Atlantic carbon uptake has already begun, while others simulate that this slowdown will only occur very late in the 21th century. Our results show that the highest model spread in the carbon uptake occurs in the high latitudes of the North Atlantic. The models with a high future anthropogenic carbon uptake reveal deep winter mixing and high primary production. Associated with this, we find that the simulated (i) high latitude winter pCO2-anomaly and (ii) upper-ocean northward volume transport between the surface and 500-m depth in the Gulf Stream area are good performance indicators for a model´s future carbon uptake in the North Atlantic. The deep winter mixing and high primary production in models with high future North Atlantic carbon uptake enable an efficient carbon sequestration into the deep ocean, i.e. an efficient anthropogenic carbon drawdown in the Labrador and Irminger Seas, but furthermore an efficient southward transport of anthropogenic carbon out of the high latitudes via the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). Related to this, other well-suited performance indicators of the future carbon uptake of the North Atlantic are the simulated (iii) fraction of the carbon inventory that is stored below 1000-m depth and (iv) deep-ocean southward volume transport between 700 and 4700 m at 26∘N. We use observation-based estimates of these four indicators to assess the model performance for the future North Atlantic carbon uptake. Our results falsify that the slowdown of the North Atlantic carbon uptake has already begun. We suggest that the strength of the AMOC is less suited as a performance indicator for the future North Atlantic carbon uptake than our newly identified indicators. Hence, the relation of maximum northward volume transport to the ocean carbon sink is not as robust as often assumed in modelling studies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".