Why does stratospheric aerosol forcing strongly cool the warm pool?
Bibliographic record
Abstract
Stratospheric aerosol forcing causes only a small global-mean temperature change compared to CO2 forcing of equal magnitude. It has been shown that the dampened temperature response to aerosol forcing originates from enhanced surface temperature change in the tropical Indian and Western Pacific Ocean, relative to the global mean. Due to the pronounced temperature change in this “warm pool” region, strong negative feedback processes are activated. These stabilizing processes strengthen the global mean radiative feedback and abate Earth’s global mean temperature response. In comparison, CO2 forcing has a smaller effect on warm pool temperatures and therefore produces relatively weak feedback, i.e. a strong temperature change.However, it has remained unclear why stratospheric aerosol forcing affects warm pool temperatures more strongly than CO2 forcing. We address this problem using simulations of aerosol and CO2 forcing in MPI-ESM. At the top of the atmosphere (TOA), aerosol forcing is stronger in the warm pool than in the global mean, while CO2 forcing is relatively homogeneous, which could explain the different temperature patterns. However, we find that the forcing pattern at the TOA is not sufficient to explain the aerosols’ strong influence on warm pool temperatures. The effect can only be explained when taking into account the effective forcing pattern at the surface, which is substantially different from the effective forcing at the TOA. In the case of stratospheric aerosol forcing, the stratospheric heating causes an acceleration of the Brewer-Dobson circulation, which induces an enhanced energy transport from the tropics to the extratropics. Although the transport occurs in the stratosphere, it affects the troposphere and causes a strongly negative forcing at the surface of the tropics. In contrast, CO2 does not substantially affect the Brewer-Dobson circulation, and therefore the surface response is not amplified in the tropics.Our results stress the importance of circulation adjustments for the climate response. In the case of stratospheric aerosol forcing, the troposphere is impacted by changes to the wave-driven stratospheric circulation. The accelerated Brewer-Dobson circulation affects the forcing pattern at the surface, and in consequence the pattern of surface temperatures and the climate feedback. Furthermore, we argue that the commonly used method of measuring effective forcing at the TOA is not sufficient for understanding the evolution of surface temperature patterns.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".