Imperfect emergency brake: Can delayed Solar Radiation Modification revert AMOC and SPG weakening? 
Bibliographic record
Abstract
Solar Radiation Modification (SRM) is a collection of hitherto hypothetical methods that would reflect a small fraction of incoming solar radiation, thereby cooling the Earth and reducing the impact of greenhouse gas forcing, albeit imperfectly. The best-researched method so far is Stratospheric Aerosol Injection (SAI), which would work by injecting a reflective aerosol (e.g. sulphate) or a precursor gas (e.g. SO2) into the stratosphere.Previous studies (e.g., Tilmes et al, 2018, 2020, Xie et al., 2022) have shown that SAI and other SRM methods can reduce or even prevent Atlantic Meridional Overturning Circulation (AMOC) weakening. No dedicated study has however been done on the effect of SRM on the Subpolar Gyre (SPG). Also, most SRM modelling studies focus on present-day (2020) or at least speedy initialization of SRM. In reality, SRM might only begin many decades from now, if at all. In our study, we investigate whether delaying SRM will cause irreversible changes to the AMOC and the SGP. To this end we compare three scenarios in the CESM2 model:Control: An extreme warming scenario (RCP8.5) without SAI SAI2020: As Control, but keeping global mean surface temperature constant by means of SAI from 2020 onwards SAI2080: As Control, but starting SAI from 2080 such as to bring global mean surface temperature to 2020 levels and keeping it constant thereafter. These are extreme scenarios, not intended to represent plausible policy choices but meant to investigate whether irreversibility can occur in principle.We find that in Control AMOC weakens from 16 Sv in 2020 to 7 Sv in 2100, while in SAI2020, it only weakens to 12 Sv. In SAI2080, AMOC stops weakening after 2080, but does not recover (at least till 2100) to the strength it has in SAI2020. Thus, delayed SAI cannot quickly revert AMOC weakening, if at all. This has effects on the local climate, in particular overcooling around the North Atlantic, and even the interhemispheric temperature gradient.In addition, we find for Control, that deep convection (i.e. deep mixed layers in winter) ceases in the Labrador sea around 2050 and south of Iceland around 2070. Under SAI2020, deep convection remains active south of Iceland. Under SAI2080, deep convection does not recover by 2100.We conclude that SAI is not a perfect “emergency brake” for global warming: If action is delayed, changes in ocean circulation persist at least for several decades. However, we stress that other, including political, factors must be taken into account when considering (near-term) SAI, and that phasing out greenhouse gas emissions must remain the primary tool of climate policy.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".