Mid-Holocene climate at mid-latitudes: modelling the impact of the Green Sahara
Bibliographic record
Abstract
During the mid-Holocene (6,000 years ago) the Northern Hemisphere experienced a reinforcement of the monsoonal regime, which led to the so-called “African Humid Period” (AHP) and to the greening of the Sahara region. Paleoclimate archives also show a gradual cooling of north-eastern Atlantic and the warming of the western subtropical Atlantic, eastern Mediterranean and northern Red Sea during the Holocene. These changes were likely accompanied by a positive-to-negative transition of the AO/NAO phase from mid-late Holocene into the pre-industrial period, leading to climate impacts in North America, Europe, the Mediterranean and Siberia. However, inconsistencies still exist between proxies and model simulations of the Holocene climate. To explain the limitations of climate models, several studies pointed out the role of the vegetation feedback at tropical and higher latitudes. The objective of this study is to investigate the impact of the Green Sahara on the Northern Hemispheric mid-latitude atmospheric circulation and associated climate variability during the African Humid Period. To this aim, vegetated Sahara with reduced dust emission is prescribed into a coupled ocean-atmosphere model (the Green Sahara experiment). Model simulations show a sizable impact on the main circulation features in the Northern Hemisphere when the Green Sahara is prescribed, especially during boreal summer, when the African monsoon develops. This study provides a first constraint on the Green Sahara influence on northern mid-latitudes, indicating new opportunities for understanding mid-Holocene climate anomalies in North America and Eurasia. However, inconsistencies between proxies and model simulations still persist in the Green Sahara experiment, indicating that more accurate simulations of the MH climate modifications are needed (e.g. prescribing realistic vegetation at mid and high latitudes, considering seasonal cycle in vegetation cover).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".