An interactive stratospheric aerosol model intercomparison of solar geoengineering by stratospheric injection of SO <sub>2</sub> or accumulation-mode sulfuric acid aerosols
Bibliographic record
Abstract
Abstract. Studies of stratospheric solar geoengineering have tended to focus on modification of the sulfuric acid aerosol layer, and almost all climate model experiments that mechanistically increase the sulfuric acid aerosol burden assume injection of SO2. A key finding from these model studies is that the radiative forcing would increase sublinearly with increasing SO2 injection because most of the added sulfur increases the mass of existing particles, resulting in shorter aerosol residence times and aerosols that are above the optimal size for scattering. Injection of SO3 or H2SO4 from an aircraft in stratospheric flight is expected to produce particles predominantly in the accumulation-mode size range following microphysical processing within an expanding plume, and such injection may result in a smaller average stratospheric particle size, allowing a given injection of sulfur to produce more radiative forcing. We report the first multi-model intercomparison to evaluate this approach, which we label AM-H2SO4 injection. A coordinated multi-model experiment designed to represent this SO3- or H2SO4-driven geoengineering scenario was carried out with three interactive stratospheric aerosol microphysics models: the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM2) with the Whole Atmosphere Community Climate Model (WACCM) atmospheric configuration, the Max-Planck Institute's middle atmosphere version of ECHAM5 with the HAM microphysical module (MAECHAM5-HAM) and ETH's SOlar Climate Ozone Links with AER microphysics (SOCOL-AER) coordinated as a test-bed experiment within the Geoengineering Model Intercomparison Project (GeoMIP). The intercomparison explores how the injection of new accumulation-mode particles changes the large-scale particle size distribution and thus the overall radiative and dynamical response to stratospheric sulfur injection. Each model used the same injection scenarios testing AM-H2SO4 and SO2 injections at 5 and 25 Tg(S) yr−1 to test linearity and climate response sensitivity. All three models find that AM-H2SO4 injection increases the radiative efficacy, defined as the radiative forcing per unit of sulfur injected, relative to SO2 injection. Increased radiative efficacy means that when compared to the use of SO2 to produce the same radiative forcing, AM-H2SO4 emissions would reduce side effects of sulfuric acid aerosol geoengineering that are proportional to mass burden. The model studies were carried out with two different idealized geographical distributions of injection mass representing deployment scenarios with different objectives, one designed to force mainly the midlatitudes by injecting into two grid points at 30∘ N and 30∘ S, and the other designed to maximize aerosol residence time by injecting uniformly in the region between 30∘ S and 30∘ N. Analysis of aerosol size distributions in the perturbed stratosphere of the models shows that particle sizes evolve differently in response to concentrated versus dispersed injections depending on the form of the injected sulfur (SO2 gas or AM-H2SO4 particulate) and suggests that prior model results for concentrated injection of SO2 may be strongly dependent on model resolution. Differences among models arise from differences in aerosol formulation and differences in model dynamics, factors whose interplay cannot be easily untangled by this intercomparison.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 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 | 0.002 |
| 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 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".