Mid-Holocene ENSO Variability reduced by northern African vegetation changes: a model intercomparison study
Bibliographic record
Abstract
The relationship between the mean state of the Pacific Ocean and El Niño Southern Oscillation (ENSO) and its variability through time is inadequately understood, especially on longer timescales. Several studies have indicated that the mid-Holocene (6,000 years before present) was characterized by stronger east-west temperature contrast and lower ENSO variability relative to the present day. While climate models show a reduction in ENSO variability, they underestimate this reduction compared to many paleoclimate reconstructions. Further, the drivers behind these changes remain unclear. In this work, we use five global climate models to show that incorporating vegetation changes over northern Africa during the mid-Holocene are vital to capturing global circulation changes. Greening the Sahara alters the Walker Circulation, enhancing zonal temperature and pressure gradients in the equatorial Pacific and driving it to a La Niña-like state. Incorporating Green Sahara boundary conditions leads to reductions in interannual variability in all Niño index regions relative to orbital and GHG changes, with reductions of up to 18% in the Niño3.4 region. Our work highlights the importance of the Atlantic influence on ENSO and provides paleoclimatic evidence for this synergistic teleconnection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".