| 11 Mar 2026
Exploring divergent long-term stratospheric aerosol injection scenarios with the G2-SAI and ARISE-hybrid experiments
Abstract. Stratospheric aerosol injection (SAI) simulations are often short relative to climatic timescales and conducted against a background that evolves due to changes in anthropogenic greenhouse gas emissions and other forcings. This can cause challenges in assessing certain impacts of the intervention, especially for aspects of the climate that respond slowly to such changes. The early Geoengineering Model Intercomparison Project (GeoMIP) G2 experiment prescribes solar dimming to offset 1%CO2 forcing in a preindustrial control background. Here we propose a new G2-SAI experiment, in which SAI is applied in the same scenario, to isolate SAI climate responses from transient changes other than CO2. Using the Community Earth System Model (CESM2), we present three 150-year "G2-SAI" simulations which use contemporary SAI strategies: two use the commonly-used "three degree-of-freedom" ("3DOF") strategy, in which independent injections at 30° N, 15° N, 15° S, and 30° S are used to manage global mean temperature (T0) and large-scale meridional temperature gradients (T1, T2). Our third G2-SAI simulation uses a "1DOF" strategy that injects at 30°N and 30°S to manage global mean temperature only. Our two 3DOF simulations both maintain the same temperature targets; however, one simulation, which injects mostly at 15° S, slows but does not prevent the decline of the Atlantic Meridional Overturning Circulation (AMOC) compared to the baseline simulation, while the other, which injects mostly at 30° N and 30° S, stops the decline of AMOC entirely, similarly to the 1DOF simulation. These results demonstrate that multiple distinct Earth system states can satisfy the same temperature targets, challenging the assumption of linearity commonly used in strategy design. In addition, the results highlight that long simulations are required to identify some of the long-term impacts of SAI, such as AMOC changes. Using this knowledge, we revisit the ARISE-SAI-1.5 experiment and modify the injection strategy without changing the temperature targets, producing an "ARISE-hybrid" ensemble. We demonstrate that this results in some significant differences in the climate response to SAI, with implications for the perceived effects of the intervention.
This manuscript introduces a new set of long term experiments, G2-SAI, to better isolate and understand the impacts of stratospheric aerosol injection (SAI), and propose them as new GeoMIP experiments. Using CESM2, the authors show that the commonly used feedback algorithm, when adjusted, can result in the scenario meeting the same temperature targets using different injection location magnitudes. These different injections can produce fundamentally different climate states, especially through their influence on the AMOC, whilst still achieving the same temperature targets. The study highlights the importance of longer simulations to capture slower climate feedbacks, and shows that small changes in the feedback algorithm can change the resulting climate impacts.
This paper is very well written and formulated. The revision of the ARISE simulations are particularly interesting. I recommend it for publication and have only a few comments below.
General comments
Section 2.2: Please could you clarify the algorithm used for G2-SAI-hybrid. You discuss in this section that l0 determines the injection for 15°N+15°S and its l1 and l2 which determine how much is injected in 30°N+30°S, how does the hybrid scenario determine injection at 30°N+30°S if l1 and l2 are turned off? It might be worth expanding on your explanation of this scenario in this section. It was not immediately clear that the three temperature targets were still being used when you discuss turning off the feedforward terms.
Section 3.2:
I really like how you have displayed the figures as “per degree of warming” but I think the way you have done this could be better explained in the opening paragraph. I think you get to some of that in the figure caption but this section would benefit from further explanation in the main text as to how you calculate the “per unit warming”. Personally, the addition of the global mean temperature increase values in the figure caption helped me understand what you had done, so perhaps adding that to the main text would help. Lines 259-261 discussing the average of the maps added confusion for me personally, so might benefit from further explanation.
Regarding the precipitation changes, I agree that a detailed investigation would be beyond the scope of the study. But it might be worth mentioning again that for the G2-SAI simulations you are only looking at one ensemble member and precipitation is highly variable and would benefit from multiple ensemble members to determine any specific impacts.
Specific comments
Line 149: remove “above”
Lines 150-152: “Feedback gains, which adjust the injection rates each year based on the error (the difference between the actual and desired model behavior) over the course of the simulation.”
Figure 1: It might be worth adjusting the width of the ensemble mean lines, it looks quite messy with the variation, in particular the black lines. This is an aesthetic judgement which the authors should feel free to ignore.
Line 196: 4f not 4f-g
Lines 200-201: “AOD distributions in years 16-35 of injection likewise have similar shapes.” Please add a reference to 4g here.
Lines 225-228: Figure references should be 5 not 4.
Line 229: Figure reference should be 4 not 3.
Line 272: Should that read “compare Figs 5a and 8d”?