>We analyse simulations performed for the Chemistry-Climate Model Initiative (CCMI) to estimate the return dates of the stratospheric ozone layer from depletion caused by anthropogenic stratospheric chlorine and bromine. We consider a total of 155 simulations from 20 models, including a range of sensitivity studies which examine the impact of climate change on ozone recovery. For the control simulations (unconstrained by nudging towards analysed meteorology) there is a large spread (±20 DU in the global average) in the predictions of the absolute ozone column. Therefore, the model results need to be adjusted for biases against historical data. Also, the interannual variability in the model results need to be smoothed in order to provide a reasonably narrow estimate of the range of ozone return dates. Consistent with previous studies, but here for a Representative Concentration Pathway (RCP) of 6.0, these new CCMI simulations project that global total column ozone will return to 1980 values in 2049 (with a 1σ uncertainty of 2043–2055). At Southern Hemisphere mid-latitudes column ozone is projected to return to 1980 values in 2045 (2039–2050), and at Northern Hemisphere mid-latitudes in 2032 (2020–2044). In the polar regions, the return dates are 2060 (2055–2066) in the Antarctic in October and 2034 (2025–2043) in the Arctic in March. The earlier return dates in the Northern Hemisphere reflect the larger sensitivity to dynamical changes. Our estimates of return dates are later than those presented in the 2014 Ozone Assessment by approximately 5–17 years, depending on the region, with the previous best estimates often falling outside of our uncertainty range. In the tropics only around half the models predict a return of ozone to 1980 values, around 2040, while the other half do not reach the 1980 value. All models show a negative trend in tropical total column ozone towards the end of the 21st century. The CCMI models generally agree in their simulation of the time evolution of stratospheric chlorine and bromine, which are the main drivers of ozone loss and recovery. However, there are a few outliers which show that the multi-model mean results for ozone recovery are not as tightly constrained as possible. Throughout the stratosphere the spread of ozone return dates to 1980 values between models tends to correlate with the spread of the return of inorganic chlorine to 1980 values. In the upper stratosphere, greenhouse gas-induced cooling speeds up the return by about 10–20 years. In the lower stratosphere, and for the column, there is a more direct link in the timing of the return dates of ozone and chlorine, especially for the large Antarctic depletion. Comparisons of total column ozone between the models is affected by different predictions of the evolution of tropospheric ozone within the same scenario, presumably due to differing treatment of tropospheric chemistry. Therefore, for many scenarios, clear conclusions can only be drawn for stratospheric ozone columns rather than the total column. As noted by previous studies, the timing of ozone recovery is affected by the evolution of N₂O and CH₄. However, quantifying the effect in the simulations analysed here is limited by the few realisations available for these experiments compared to internal model variability. The large increase in N₂O given in RCP 6.0 extends the ozone return globally by ∼ 15 years relative to N₂O fixed at 1960 abundances, mainly because it allows tropical column ozone to be depleted. The effect in extratropical latitudes is much smaller. The large increase in CH₄ given in the RCP 8.5 scenario compared to RCP 6.0 also lengthens ozone return by ∼ 15 years, again mainly through its impact in the tropics. Overall, our estimates of ozone return dates are uncertain due to both uncertainties in future scenarios, in particular those of greenhouse gases, and uncertainties in models. The scenario uncertainty is small in the short term but increases with time, and becomes large by the end of the century. There are still some model–model differences related to well-known processes which affect ozone recovery. Efforts need to continue to ensure that models used for assessment purposes accurately represent stratospheric chemistry and the prescribed scenarios of ozone-depleting substances, and only those models are used to calculate return dates. For future assessments of single forcing or combined effects of CO₂, CH₄, and N₂O on the stratospheric column ozone return dates, this work suggests that it is more important to have multi-member (at least three) ensembles for each scenario from every established participating model, rather than a large number of individual models.

We present here results from the Geoengineering Model Intercomparison Project (GeoMIP) simulations for the experiments G6sulfur and G6solar for six Earth system models participating in the Climate Model Intercomparison Project (CMIP) Phase 6. The aim of the experiments is to reduce the warming that results from a high-tier emission scenario (Shared Socioeconomic Pathways SSP5-8.5) to that resulting from a medium-tier emission scenario (SSP2-4.5). These simulations aim to analyze the response of climate models to a reduction in incoming surface radiation as a means to reduce global surface temperatures, and they do so either by simulating a stratospheric sulfate aerosol layer or, in a more idealized way, through a uniform reduction in the solar constant in the model. We find that over the final two decades of this century there are considerable inter-model spreads in the needed injection amounts of sulfate (29 ± 9 Tg-SO₂/yr between 2081 and 2100), in the latitudinal distribution of the aerosol cloud and in the stratospheric temperature changes resulting from the added aerosol layer. Even in the simpler G6solar experiment, there is a spread in the needed solar dimming to achieve the same global temperature target (1.91 ± 0.44 %). The analyzed models already show significant differences in the response to the increasing CO₂ concentrations for global mean temperatures and global mean precipitation (2.05 K ± 0.42 K and 2.28 ± 0.80 %, respectively, for SSP5-8.5 minus SSP2-4.5 averaged over 2081–2100). With aerosol injection, the differences in how the aerosols spread further change some of the underlying uncertainties, such as the global mean precipitation response (−3.79 ± 0.76 % for G6sulfur compared to −2.07 ± 0.40 % for G6solar against SSP2-4.5 between 2081 and 2100). These differences in the behavior of the aerosols also result in a larger uncertainty in the regional surface temperature response among models in the case of the G6sulfur simulations, suggesting the need to devise various, more specific experiments to single out and resolve particular sources of uncertainty. The spread in the modeled response suggests that a degree of caution is necessary when using these results for assessing specific impacts of geoengineering in various aspects of the Earth system. However, all models agree that compared to a scenario with unmitigated warming, stratospheric aerosol geoengineering has the potential to both globally and locally reduce the increase in surface temperatures.

Making informed future decisions about solar radiation modification (SRM; also known as solar geoengineering)—approaches such as stratospheric aerosol injection (SAI) that would cool the climate by reflecting sunlight—requires projections of the climate response and associated human and ecosystem impacts. These projections, in turn, will rely on simulations with global climate models. As with climate-change projections, these simulations need to adequately span a range of possible futures, describing different choices, such as start date and temperature target, as well as risks, such as termination or interruptions. SRM modeling simulations to date typically consider only a single scenario, often with some unrealistic or arbitrarily chosen elements (such as starting deployment in 2020), and have often been chosen based on scientific rather than policy-relevant considerations (e.g., choosing quite substantial cooling specifically to achieve a bigger response). This limits the ability to compare risks both between SRM and non-SRM scenarios and between different SRM scenarios. To address this gap, we begin by outlining some general considerations on scenario design for SRM. We then describe a specific set of scenarios to capture a range of possible policy choices and uncertainties and present corresponding SAI simulations intended for broad community use.

Solar climate intervention using stratospheric aerosol injection is a proposed method of reducing global mean temperatures to reduce the worst consequences of climate change. A detailed assessment of responses and impacts of such an intervention is needed with multiple global models to support societal decisions regarding the use of these approaches to help address climate change. We present a new modeling protocol aimed at simulating a plausible deployment of stratospheric aerosol injection and reproducibility of simulations using other Earth system models: Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI). The protocol and simulations are aimed at enabling community assessment of responses of the Earth system to solar climate intervention. ARISE-SAI simulations are designed to be more policy-relevant than existing large ensembles or multi-model simulation sets. We describe in detail the first set of ARISE-SAI simulations, ARISE-SAI-1.5, which utilize a moderate emissions scenario, introduce stratospheric aerosol injection at ∼21.5 km in the year 2035, and keep global mean surface air temperature near 1.5 ^∘C above the pre-industrial value utilizing a feedback or control algorithm. We present the detailed setup, aerosol injection strategy, and preliminary climate analysis from a 10-member ensemble of these simulations carried out with the Community Earth System Model version 2 with the Whole Atmosphere Community Climate Model version 6 as its atmospheric component.

A previous model intercomparison of the Tambora aerosol cloud has highlighted substantial differences among simulated volcanic aerosol properties in the pre-industrial stratosphere and has led to questions about the applicability of global aerosol models for large-magnitude explosive eruptions prior to the observational period. Here, we compare the evolution of the stratospheric aerosol cloud following the well-observed June 1991 Mt. Pinatubo eruption simulated with six interactive stratospheric aerosol microphysics models to a range of observational data sets. Our primary focus is on the uncertainties regarding initial SO₂ emission following the Pinatubo eruption, as prescribed in the Historical Eruptions SO₂ Emission Assessment experiments (HErSEA), in the framework of the Interactive Stratospheric Aerosol Model Intercomparison Project (ISA-MIP). Six global models with interactive aerosol microphysics took part in this study: ECHAM6-SALSA, EMAC, ECHAM5-HAM, SOCOL-AERv2, ULAQ-CCM, and UM-UKCA. Model simulations are performed by varying the SO₂ injection amount (ranging between 5 and 10 Tg S) and the altitude of injection (between 18–25 km). The comparisons show that all models consistently demonstrate faster reduction from the peak in sulfate mass burden in the tropical stratosphere. Most models also show a stronger transport towards the extratropics in the Northern Hemisphere, at the expense of the observed tropical confinement, suggesting a much weaker subtropical barrier in all the models, which results in a shorter e-folding time compared to the observations. Furthermore, simulations in which more than 5 Tg S in the form of SO₂ is injected show an initial overestimation of the sulfate burden in the tropics and, in some models, in the Northern Hemisphere and a large surface area density a few months after the eruption compared to the values measured in the tropics and the in situ measurements over Laramie. This draws attention to the importance of including processes such as the ash injection for the removal of the initial SO₂ and aerosol lofting through local heating.

This study assesses the impacts of stratospheric aerosol intervention (SAI) and solar dimming on stratospheric ozone based on the G6 Geoengineering Model Intercomparison Project (GeoMIP) experiments, called G6sulfur and G6solar. For G6sulfur, an enhanced stratospheric sulfate aerosol burden reflects some of the incoming solar radiation back into space to cool the surface climate, while for G6solar, the reduction in the global solar constant in the model achieves the same goal. Both experiments use the high emissions scenario of SSP5-8.5 as the baseline experiment and define surface temperature from the medium emission scenario of SSP2-4.5 as the target. In total, six Earth system models (ESMs) performed these experiments, and three out of the six models include interactive stratospheric chemistry. The increase in absorbing sulfate aerosols in the stratosphere results in a heating of the lower tropical stratospheric temperatures by between 5 to 13 K for the six different ESMs, leading to changes in stratospheric transport, water vapor, and other related changes. The increase in the aerosol burden also increases aerosol surface area density, which is important for heterogeneous chemical reactions. The resulting changes in the springtime Antarctic ozone between the G6sulfur and SSP5-8.5, based on the three models with interactive chemistry, include an initial reduction in total column ozone (TCO) of 10 DU (ranging between 0–30 DU for the three models) and up to 20 DU (between 10–40 DU) by the end of the century. The relatively small reduction in TCO for the multi-model mean in the first 2 decades results from variations in the required sulfur injections in the models and differences in the complexity of the chemistry schemes. In contrast, in the Northern Hemisphere (NH) high latitudes, no significant changes can be identified due to the large natural variability in the models, with little change in TCO by the end of the century. However, all three models with interactive chemistry consistently simulate an increase in TCO in the NH mid-latitudes up to 20 DU, compared to SSP5-8.5, in addition to the 20 DU increase resulting from increasing greenhouse gases between SSP2-4.5 and SSP5-8.5. In contrast to G6sulfur, G6solar does not significantly change stratospheric temperatures compared to the baseline simulation. Solar dimming results in little change in TCO compared to SSP5-8.5. Only in the tropics does G6solar result in an increase of TCO of up to 8 DU, compared to SSP2-4.5, which may counteract the projected reduction in SSP5-8.5. This work identifies differences in the response of SAI and solar dimming on ozone for three ESMs with interactive chemistry, which are partly due to the differences and shortcomings in the complexity of aerosol microphysics, chemistry, and the description of ozone photolysis. It also identifies that solar dimming, if viewed as an analog to SAI using a predominantly scattering aerosol, would succeed in reducing tropospheric and surface temperatures, but any stratospheric changes due to the high forcing greenhouse gas scenario, including the potential harmful increase in TCO beyond historical values, would prevail.