Impacts of AMOC Collapse on Monsoon Rainfall: A Multi‐Model Comparison
Bibliographic record
Abstract
Abstract A collapse of the Atlantic Meridional Overturning Circulation (AMOC) would have substantial impacts on global precipitation patterns, especially in the vulnerable tropical monsoon regions. We assess these impacts in experiments that apply the same freshwater hosing to four state‐of‐the‐art climate models with bistable AMOC. As opposed to previous results, we find that the spatial and seasonal patterns of precipitation change are remarkably consistent across models. We focus on the South American Monsoon (SAM), the West African Monsoon (WAM), the Indian Summer Monsoon (ISM) and the East Asian Summer Monsoon (EASM). Models consistently suggest substantial disruptions for WAM, ISM, and EASM with shorter wet and longer dry seasons (−29.07%, −18.76%, and −3.78% ensemble mean annual rainfall change, respectively). Models also agree on changes for the SAM, suggesting rainfall increases overall, in contrast to previous studies. These are more pronounced in the southern Amazon (+43.79%), accompanied by decreasing dry‐season length. Consistently across models, our results suggest a robust and major rearranging of all tropical monsoon systems in response to an AMOC collapse.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".