Northern Hemisphere Land Monsoon Precipitation Increased by the Green Sahara During Middle Holocene
Bibliographic record
Abstract
Abstract Changes in land cover and dust emission may significantly influence the Northern Hemisphere land monsoon precipitation (NHLMP), but observations are too short to fully evaluate their impacts. The “Green Sahara” during the mid‐Holocene (6,000 years BP) provides an opportunity to unravel these mechanisms. Here we show that during the mid‐Holocene, most of the NHLMP changes revealed by proxy data are reproduced by the Earth System model results when the Saharan vegetation cover and dust reduction are taken into consideration. The simulated NHLMP significantly increases by 33.10% under the effect of the Green Sahara. The North African monsoon precipitation increases most significantly. Additionally, the Saharan vegetation (dust reduction under vegetated Sahara) alone remotely intensifies the Asian (North American) monsoon precipitation through large‐scale atmospheric circulation changes. These findings imply that future variations in land cover and dust emissions may appreciably influence the NHLMP.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".