The weakening of AMOC highly linked to climate warming outside the Arctic
Bibliographic record
Abstract
Global warming since the industrial revolution has led to a series of changes in the atmosphere and ocean. As a key indicator of global ocean circulation, AMOC has shown a weakening in recent decades from both the observed and simulated results. This process which is not only affected by the local variation of the Arctic, but also by the ocean and atmosphere circulation changes in the middle and lower latitudes, might have important implications for future global climate changes. We employ the Alfred Wegener Institute Climate Model (AWI-CM 1.1 LR) and a method of perturbing coupled models to quantify and understand the impact of anthropogenic warming on the slowdown of AMOC. Conducted one control (CTRL) experiment and three sensitivity experiments (60N, 60NS, and GLOB) in which CO2 concentration were abruptly quadrupled either regionally (60N-north of 60°N, 60NS-south of 60°N) or globally (GLOB). The goal of our research is to identify the response of AMOC weakening to the quadrupling of CO2 concentration in different regions and provide future insight into ocean circulation changes in the context of climate warming. Our results show that CO2 forcing outside the Arctic dominates the weakening of AMOC. In a warming climate, the poleward heat transport increased due to the extra-Arctic CO2 forcing, which enhanced the upper ocean average stratification within the mixed-layer depth over Nordic Seas and Labrador Sea and thus weakens the AMOC to a large extent. The warming in upper-layer also lead to the dominant role of temperature contribution to stratification. However, in both the deep convection regions, the mechanism resulting in the strengthening of stratification might be quite different.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".