The water cycle of the mid‐Holocene West African monsoon: The role of vegetation and dust emission changes
Bibliographic record
Abstract
During the mid‐Holocene (6 kyr BP), West Africa experienced a much stronger and geographically extensive monsoon than in the present day. Changes in orbital forcing, vegetation and dust emissions from the Sahara have been identified as key factors driving this intensification. Here, we analyse how the timing, origin and convergence of moisture fluxes contributing to the monsoonal precipitation change under a range of scenarios: orbital forcing only; orbital and vegetation forcings (Green Sahara); orbital, vegetation and dust forcings (Green Sahara‐reduced dust). We further compare our results to a range of reconstructions of mid‐Holocene precipitation from palaeoclimate archives. In our simulations, the greening of the Sahara leads to a cyclonic water vapour flux anomaly over North Africa with an anomalous westerly flow bringing large amounts of moisture into the Sahel from the Atlantic Ocean. Changes in atmospheric dust under a vegetated Sahara shift the anomalous moisture advection pattern northwards, increasing both moisture convergence and precipitation recycling over the northern Sahel and Sahara and the associated precipitation during the boreal summer. During this season, under both the Green Sahara and Green Sahara‐reduced dust scenarios, local recycling in the Saharan domain exceeds that of the Sahel. This points to local recycling as an important factor modulating vegetation‐precipitation feedbacks and the impact of Saharan dust emissions. Our results also show that temperature and evapotranspiration over the Sahara in the mid‐Holocene are close to Sahelian pre‐industrial values. This suggests that pollen‐based paleoclimate reconstructions of precipitation during the Green Sahara period are likely not biased by possible large evapotranspiration changes in the region.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".