Tropical Rainfall Trends and the Indirect Aerosol Effect
Bibliographic record
Abstract
An atmospheric global climate model coupled to a mixed layer ocean model is used to study changes in tropical rainfall due to the indirect effects of anthropogenic sulfate aerosol.The model is run to equilibrium for present-day (PD) and preindustrial (PI) sulfur emission scenarios.As in two other recent studies, the model generally gives a southward shift of tropical rainfall in the PD run relative to the PI run.This is largely due to a hemispheric asymmetry in the reduction of sea surface temperature (SST) induced by the perturbation of cloud albedo and lifetime.Observed precipitation trends over land for the period 1900-98 show a complex pattern in the Tropics, but when zonally averaged, a southward shift similar to (but weaker than) the modeled shift is clearly evident.The zonally averaged tropical trends are significant at the 5% level in several latitude bands.The modeled presentday hemispheric contrast in cloud droplet effective radius (which affects cloud albedo) is well supported by one long-term satellite retrieval, but not by another.A third satellite retrieval, which only covers an 8-month period, does show a marked hemispheric contrast in effective radius.Both in the modeled changes and the observed trends, a prominent feature is the drying of the Sahel in North Africa.Modeled dynamical changes in this region are similar to observed changes that have been associated with Sahelian drought.Previous work has identified a near-global, quasi-hemispheric pattern of contrasting SST anomalies (cool in the Northern Hemisphere and warm in the Southern Hemisphere) associated with dry conditions in the Sahel.The present results, combined with this earlier finding, suggest that the indirect effects of anthropogenic sulfate may have contributed to the Sahelian drying trend.More generally, it is concluded that spatially varying aerosol-related forcing (both direct and indirect) can substantially alter low-latitude circulation and rainfall.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".