Anthropogenic Aerosols Dominate Forced Multidecadal Sahel Precipitation Change through Distinct Atmospheric and Oceanic Drivers
Bibliographic record
Abstract
Abstract Sahel precipitation has undergone substantial multidecadal time scale changes during the twentieth century that have had severe impacts on the region’s population. Using initial-condition large ensembles (LE) of coupled general circulation model (GCM) simulations from two institutions, forced multidecadal variability is found in which Sahel precipitation declines from the 1950s to 1970s and then recovers from the 1970s to 2000s. This forced variability has similar timing to, but considerably smaller magnitude than, observed Sahel precipitation variability. Isolating the response using single forcing simulations within the LEs reveals that anthropogenic aerosols (AA) are the primary driver of this forced variability. The roles of the direct-atmospheric and the ocean-mediated atmospheric responses to AA forcing are determined with the atmosphere–land GCM (AGCM) components of the LE coupled GCMs. The direct-atmospheric response arises from changes to aerosol and precursor emissions with unchanged oceanic boundary conditions while the ocean-mediated response arises from changes to AA-forced sea surface temperatures and sea ice concentrations diagnosed from the AA-forced LE. In the AGCMs studied here, the direct-atmospheric response dominates the AA-forced 1970s − 1950s Sahel drying. On the other hand, the 2000s − 1970s wetting is mainly driven by the ocean-mediated effect, with some direct atmospheric contribution. Although the responses show differences, there is qualitative agreement between the AGCMs regarding the roles of the direct-atmospheric and ocean-mediated responses. Since these effects often compete and show nonlinearity, the model dependence of these effects and their role in the net aerosol-forced response of Sahel precipitation need to be carefully accounted for in future model analysis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".