Using CMIP6 simulations to assess significance of an AMOC trend seen by the RAPID array
Bibliographic record
Abstract
Observations between 2004 and 2020 at the RAPID array suggest a weakening trend in the Atlantic Meridional Overturning Circulation (AMOC). To assess the significance of this trend, trends that one might expect from natural variabilty in a time series of this length are assessed using CMIP6 pre-industrial simulations. The observed trend is not found to be statistically significant relative to this benchmark. Both the observed trend and the standard deviation of short-term model trends are found to decrease in magnitude with time. The rate of decrease, however, is faster for the observed trend, further calling into question its significance. To clarify how variability in short-term model trends is related to power spectra of modelled AMOC strength, a conceptual model is developed. Essentially, trend variance is represented by a random walk in which there is one step for each frequency bin of the power spectrum (with step size determined by the frequency and variance of the bin in question). Most models are found underestimate interannual variability in AMOC strength; however, it is the variability at somewhat longer time scales that most influences model trends. This variability is represented quite differently between the various CMIP6 models. The conceptual model is also used to illustrate how the detectability threshold for trend detection (i.e., the 2 sigma level in a PDF of short-term model trends) is altered by the addition of noise added to make AMOC variance more in line with observations.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".