Weakening the CO2 Greenhouse Effect via Stratospheric Aerosol Injection

doi:10.21203/rs.3.rs-5210392/v1

Download PDF

Article

Weakening the CO2 Greenhouse Effect via Stratospheric Aerosol Injection

https://doi.org/10.21203/rs.3.rs-5210392/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Stratospheric aerosol injection (SAI) represents one of the primary potential options for intentionally modifying the climate to offset the warming from increasing greenhouse gases. The hypothesized strategy typically involves the injection of scattering aerosols in the lower stratosphere to increase the amount of sunlight reflected to space, thereby reducing the amount of sunlight absorbed by Earth. We demonstrate a new and potentially more efficient approach to SAI, using it to induce a weakening of the Earth’s greenhouse effect. We show that the injection of absorptive aerosols in the upper stratosphere (~ 10 hPa) increases the emission of top-of-atmosphere infrared radiation. Warming the emission level of CO₂ weakens the greenhouse effect by altering the thermal structure of the upper stratosphere rather than the concentration of greenhouse gases. Climate model simulations indicate that the reduction in global temperatures induced through this process is an order of magnitude larger (per unit aerosol mass) than the injection of more traditional reflective aerosols. These results argue for further research into the possible impacts, particularly unintended deleterious side effects, of injecting absorptive aerosols in the upper stratosphere as a potential alternative strategy for solar radiation management.

Earth and environmental sciences/Climate sciences/Climate change/Climate and Earth system modelling

Earth and environmental sciences/Climate sciences/Climate change/Climate-change mitigation

Keeping global warming below the 1.5°C threshold set by the Paris Agreement (UNFCCC, 2015) requires dramatic decreases in the emissions of greenhouse gases (GHGs). The potential to rapidly reduce GHG emissions is real, but progress is slow and global GHG emissions continue unabated (Forster et al., 2024). Considering these concerns, exploring alternative intervention strategies, including solar radiation management, is essential. One possible approach, stratospheric aerosol injection (SAI), involves artificially enhancing the Earth’s planetary albedo by increasing the number of small reflective particles in the stratosphere and has been proposed as an effective means of reducing surface temperature increases on a global scale, supported by substantial modeling and empirical evidence (e.g., Long & Shepherd, 2014; Lawrence et al., 2018; MacMartin et al., 2018). Sulfate (SO₄) aerosols have been featured prominently in SAI research, with volcanic eruptions serving as a natural analog (e.g., Kravitz et al., 2015). Although the intervention could reduce surface temperatures and potentially ameliorate some risks posed by climate change, it does not address the underlying driver of climate change (i.e., increasing GHG concentrations in the atmosphere) and cannot compensate for the radiative effects of the increased atmospheric GHGs in a direct way.

In contrast to the conventional SO₄ SAI, we hypothesize that alternative approaches that involve weakening the atmospheric greenhouse effect by warming the upper stratosphere (~ 10 hPa) via the injection of absorptive aerosols [e.g., black carbon (BC)] may warrant consideration and address some of the potential shortcomings of traditional SAI. This strategy is motivated by theoretical and modeling evidence that the CO₂ greenhouse effect depends strongly on the upper stratospheric temperature (He et al., 2023; Jeevanjee et al., 2021), where the CO₂ absorption bands achieve unit optical depth. These studies show that increasing the emission temperature at these levels enhances the net longwave emission of radiation to space, weakening the greenhouse effect and countering the CO₂-induced cooling within the stratosphere, suggesting any change in atmospheric composition that perturbs the upper stratospheric temperature could also impact the climate by modulating the CO₂ forcing at the top-of-atmosphere (TOA), even without changing the CO₂ amount. This approach of warming the upper stratosphere with BC injection differs fundamentally from most SAI approaches, which use reflective aerosols to cool the planet. While analytic and radiative transfer calculations demonstrate the feasibility of weakening the CO₂ greenhouse effect, such an approach has heretofore never been proposed or tested in coupled ocean-atmosphere or earth system models, and its potential relative to other traditional SAI approaches remains largely unknown.

Admittedly, a few previous studies of SAI using BC aerosols have been performed (Ferraro et al., 2011; Jones et al., 2016; Kravitz et al., 2012); however, these studies did not consider the impact of BC in modifying the greenhouse effect, focusing instead on its ability to cool the planet by reducing the solar radiation at the surface. Moreover, these studies only considered the injection of BC aerosols in the lower stratosphere, where its impact on the longwave emission to space by CO₂ is small and where it has the deleterious effect of warming tropopause temperatures and enhancing input of water vapor to the stratosphere. Although some studies investigated the altitude dependence of BC and SO₄ aerosols (Allen et al., 2019; Samset & Myhre, 2011, 2015), these studies primarily examined the radiative effects of aerosols in the troposphere.

This study evaluates the altitude dependence of stratospheric aerosol deployments with both reflective and absorptive aerosols, as well as the difference between their effectiveness in mediating future warming. Utilizing a series of global climate model simulations, we show that by placing BC aerosols in the upper stratosphere (~ 10 hPa), near the emission level of CO₂, one can optimize its impact on enhancing the longwave emission to space and minimize the potential negative effects of tropopause warming. We further demonstrate that this approach provides a more efficient radiative forcing per unit aerosol burden relative to conventional scattering-based SAI approaches, with corresponding increases in cooling efficiency.

The atmospheric greenhouse effect fundamentally depends on two quantities: the concentration of GHGs and the atmospheric temperature structure. An analytical model demonstrates that the radiative heat trapped by CO₂ represents a swap of tropospheric emission for stratospheric emission and, therefore, can be understood in terms of a dependence on the emission temperature of both the stratosphere and troposphere (Jeevanjee et al., 2021). The former refers to the temperature of the upper stratosphere, where the CO₂ absorption bands achieve unit optical depth, while the latter depends on surface temperature and free-troposphere relative humidity. Recently, He et al. (2023) used this model in conjunction with detailed radiative transfer calculations to demonstrate the dominant role that changes in upper stratospheric temperature play in determining the magnitude of the radiative forcing and greenhouse effect of CO₂.

Figure 1 shows the sensitivity of the outgoing longwave radiation to the temperature perturbations within the stratosphere ranging from 100 hPa to 1 hPa. The results are obtained from a set of offline radiative transfer calculations using monthly climatological temperature and humidity profiles of pre-industrial simulations as well as the specified temperature perturbations at individual layers, by a broadband radiative transfer model [SOCRATES (Edwards & Slingo, 1996; Manners et al., 2015)].

These results demonstrate the importance of the vertical location of warming on the emission of outgoing longwave radiation. For the same magnitude of perturbation, a change in temperature at a higher altitude has a larger impact on the outgoing longwave radiation. Optimal sensitivity occurs when the temperature perturbation coincides with the level where CO₂ optical depth is ~ 1 (upper stratosphere), allowing for unimpeded emission to space. Air temperature increases within the upper stratosphere provide a more efficient longwave emission to space. Thus, one can reduce the strength of the CO₂ greenhouse effect by reducing the concentration of CO₂ or warming the emission level of CO₂.

2.1 Altitude dependence of effective radiative forcing from prescribed absorptive and reflective aerosols

To test the sensitivity to the vertical level at which the aerosols are deployed, individual effective radiative forcing (ERF) calculations are done by separately placing the aerosols in each of the highest 7 model levels (Materials and Methods; Extended Data Tables 1 & 2). Figure 2 shows the global ERF for a horizontally-uniform deployment of 0.5 Tg BC aerosols (left) and 0.5 and 5.0 Tg SO₄ aerosols separately (right). For the SO₄ deployments, the ERF exhibits little sensitivity to the vertical location of the aerosol layer, with an ERF of ~ 0.12 W m^− 2 for 0.5 Tg of SO₄ and ~ 1.3 W m^− 2 for 5.0 Tg of SO₄, suggesting a roughly linear relationship between SO₄ aerosol loads and the corresponding ERF.

In contrast to the SO₄, the ERF for BC aerosols exhibits a very strong sensitivity to the vertical level of deployment with higher altitude deployment resulting in significantly higher ERF values. Peak ERF values of ~ 2 W m^− 2, which are an order of magnitude larger than that obtained for the equivalent mass of SO₄, are found for the highest 2 sigma levels (σ = 0.0035 and σ = 0.0074, or roughly ~ 1–10 hPa). As shown below, this larger value of forcing results primarily from the increased longwave emission to space induced by the warming of the stratosphere. These peak forcing levels coincide with the emission level of CO₂ (i.e., τ ~ 1) where the outgoing longwave radiation is most sensitive to warming (Fig. 1). The ERF rapidly diminishes below this level, becoming effectively zero for σ = 0.0701 (~ 70 hPa). Nearly identical results are found with the GFDL-AM2.1 model (Extended Data Fig. 1). The weak values of ERF when BC is placed in the lower stratosphere are consistent with previous studies that found BC to be an ineffective option for solar radiation management (Kravitz et al. 2012; Jones et al. 2016). However, these studies only considered injection in the lower stratosphere. In contrast, when BC aerosols are injected in the upper stratosphere, they deliver a much more efficient radiative forcing per unit aerosol burden (~ 12 times stronger) relative to conventional SO₄-based SAI approaches with a peak ERF of -1.67 W m^− 2 from 0.5 Tg BC vs. -0.12 W m^− 2 from 0.5 Tg SO₄.

Next, we decompose the ERF into individual shortwave and longwave components (Extended Data Fig. 2). For SO₄ aerosol deployments, both the shortwave and longwave components exhibit little sensitivity to the vertical location of the aerosol layer (Extended Data Fig. 2b). For BC, which exhibits a very strong dependence of the ERF on altitude, most of this dependence (over two-thirds) results from the longwave component (Extended Data Fig. 2a), with the remainder from the shortwave which is discussed further below. To further examine the altitude dependence of BC forcing, we decompose the ERF into the instantaneous radiative forcing (IRF; direct effects) and rapid adjustments (indirect effects) (Extended Data Fig. 3; See more details in Materials and Methods). Note that we sum up the longwave IRF and stratospheric temperature adjustment as stratospheric adjusted longwave radiative forcing in Extended Data Fig. 3a to avoid discussing their altitude dependencies separately. This decomposition reveals a strong altitude dependence in the stratospheric adjusted longwave radiative forcing, ranging from − 4.7 W m^− 2 in the uppermost layers to -2.2 W m^− 2 in the lowest layer (Extended Data Fig. 3a). The shortwave IRF is basically the same for all aerosol layers (Extended Data Fig. 3b).

Rapid adjustments from tropospheric clouds are also strongly dependent upon the level of aerosol deployment. The longwave cloud adjustment drops from − 0.25 W m^− 2 when BC aerosols are plated at σ = 0.0035 (uppermost level) to -1.43 W m^− 2 when the aerosols are placed at σ = 0.0701 (lowest level). Similarly, the shortwave cloud adjustment strengthens from 0.73 W m^− 2 when BC aerosols are placed at the uppermost layer to 1.23 W m^− 2 when the aerosols are placed at the lowest layer. This increasing cloud adjustment is responsible for the altitude dependence of the shortwave ERF (Extended Data Fig. 3). While the temperature dependence of the CO₂ emission to space is based on fundamental physics and robust across models (He et al., 2023; Jeevanjee et al., 2021), cloud adjustments to anthropogenic forcing are poorly understood and differ significantly between models (e.g., Smith et al., 2018, 2020). Thus, the cloud adjustments to stratospheric injection of BC aerosols are also likely to be model-dependent.

2.2 Effectiveness in mediating warming and related climate impacts

To evaluate the effectiveness of these SAI deployments in mediating warming, we perform a series of coupled simulations (Materials and Methods) with both the high-resolution climate model (GFDL-CM2.5-FLOR, Extended Data Table 1) and the lower-resolution (more efficient) version model (GFDL-CM2.1, Extended Data Table 2). These climate intervention simulations are initiated from pre-industrial conditions and are done for both the 0.5 Tg BC and 5.0 Tg SO₄ aerosols. The 0.5 Tg BC simulation induces slightly more cooling (~ 0.8 K) compared to the 5.0 Tg of SO₄ (~ 0.6 K) (Fig. 3a). The effectiveness in mediating warming is observed in both a single realization of the GFDL-CM2.5-FLOR (dotted line) and the 3-member ensemble mean of the GFDL-CM2.1 (solid line and shading). The difference in the cooling effects between that of 0.5 Tg BC and 5.0 Tg SO₄ aerosols is mainly attributed to their difference in ERF, as both sets of experiments have similar feedback values (Extended Data Fig. 4a).

The more substantial cooling in the 0.5 Tg BC simulations leads to a greater reduction in global rainfall (Fig. 3b), noting that both sets of forcing experiments exhibit similar rates of rainfall reduction per unit global temperature change (Extended Data Fig. 4b). Rapid precipitation decreases are found in both of these climate intervention simulations (Fig. 3b and Extended Data Fig. 4b). In particular, the fast precipitation decline in the BC simulations occurs without significant surface temperature changes.

Similar patterns of air temperature and precipitation change are also found between both intervention strategies. We focus on the last 30 years of these coupled simulations and plot the time-mean spatial patterns of both surface air temperature and precipitation changes per unit global temperature change (Fig. 4 and Extended Data Fig. 5). Both models exhibit delayed cooling over the Southern Ocean, resulting in an interhemispheric cooling contrast with more cooling over the Northern Hemisphere and less cooling over the Southern Hemisphere. The interhemispheric contrast is more noticeable in BC simulations using the GFDL-CM2.1 (Fig. 4), enhanced by the strong Arctic amplification and the more uniform cooling over the northern Pacific, which do not occur in the SO₄ simulations. Correspondingly, there is a general precipitation declining pattern, which is opposite to the “dry gets drier, and wet gets wetter” paradigm (Held & Soden, 2006), and the effect of tropical ocean warming patterns (Xie et al., 2010) under CO₂ increase scenarios. There is significant drying occurring over the tropics and wetting over subtropics, while stronger wetting is found over the southern hemisphere accompanied by the southward shifts of the Inter Tropical Convergence Zone. Consistent with the above-mentioned different cooling over the tropical Pacific, BC simulations show more uniform drying over the tropics, while SO₄ simulations display more drying over the eastern Pacific and tropical Atlantic, as well as an eye-catching wetting over the equatorial western Pacific.

Similar cooling patterns are also shown in the single realization of the GFDL-CM2.5-FLOR (Extended Data Fig. 5), especially for the BC simulation, except for the weaker “warming hole” over the Northern Atlantic in both simulations. In addition, noticeably inconsistent features are found over polar areas for the SO₄ simulation. Different from the ensemble-mean results of GFDL-CM2.1, GFDL-CM2.5-FLOR simulates a stronger Arctic amplification with comparable strength to that of BC simulation, but it is offset by even stronger delayed cooling over the Southern Ocean, resulting in a comparable global cooling rate. It is worth noting that identical tropical cooling patterns are found consistently across the two models, especially over the tropical Pacific, with a La Niña-like pattern for the BC simulations and missed cooling over the central Pacific for the SO₄ simulations, leading to identical precipitation responses. The consistent tropical responses probably suggest the role of radiative forcing in mediating warming via modulating the forced cooling patterns over the tropics, while the distinct responses over polar areas across the two models could probably be attributed to the internal variabilities, especially the low-frequency internal variability in models, considering the exact ocean model is adopted in the two climate models.

A concern of both intervention strategies is the warming of tropopause temperatures, which can lead to negative impacts on both stratospheric ozone concentrations (Mills et al., 2008; Kravitz et al., 2012) and monsoonal circulations (Hueholt et al., 2023; Simpson et al., 2019; Visioni et al., 2020). As expected, the maximum atmospheric warming closely matches the location of the aerosol layer for both SO₄ and BC, although BC aerosols generate significantly more warming due to their greater absorptivity (Extended Data Fig. 6a). The higher and thinner the atmosphere, the greater the warming. Aerosols in the lower stratosphere induce more warming around tropopause and upper troposphere, and a larger increase in the saturation vapor pressure. Without enhanced water vapor transport into the area, it is reasonable to expect a decrease in the relative humidity (Extended Data Fig. 6b). Similarly, cloud fraction decreases within the upper troposphere (Extended Data Fig. 6c). The lower we prescribe the BC aerosols, the more the cloud fraction decreases, likely due to the stability Iris hypothesis (Bony et al., 2016), which states that the increased stability reduces the magnitude of the radiatively driven clear-sky mass convergence at the height of anvil clouds, thus weakening convective detrainment at that height, leading to a reduction of the anvil coverage.

Motivated by theoretical and modeling evidence that the CO₂ greenhouse effect depends strongly on the upper stratospheric temperature (He et al., 2023; Jeevanjee et al., 2021), we propose a new and potentially more effective approach to SAI that uses absorbing aerosols to induce a weakening of the Earth’s greenhouse effect. The injection of absorbing aerosols in the upper stratosphere increases the emission of infrared radiation out of the TOA. By warming the emission level of CO₂, this process directly weakens the greenhouse effect by altering the thermal structure of the upper stratosphere rather than the concentration of GHGs.

Prescribing the same amount of aerosols separately at each of the highest 7 sigma levels of the aerosol input file and running the recommended ERF diagnostics, we found the ERF of BC aerosols depends strongly on the altitude at which BC aerosols are injected, while the ERF of SO₄ aerosols exhibits little sensitivity to the vertical location of the aerosol layer. Here the stratospheric adjusted longwave radiative forcing initiated by BC aerosols, from the weakening CO₂ greenhouse effects and strengthening stratospheric temperature adjustment, dominates the altitude dependence of BC ERF.

By placing BC in the upper stratosphere near the emission level of CO₂, the BC aerosols deliver a more efficient radiative forcing per unit aerosol burden (~ 12 times stronger) relative to conventional SO₄-based SAI approaches. The models examined here have very similar climate sensitivities for both forms of SAI, thus BC aerosols also provide a more efficient cooling of the climate per unit aerosol mass. For the models examined here, GFDL-CM2.5-FLOR and GFDL-CM2.1, the reduction in global temperatures induced through the upper stratospheric BC aerosol injection is more than an order of magnitude larger compared to the injection of more traditional SO₄ aerosols. These results argue for further research into the possible benefits, costs, and unintended side effects of injecting absorptive aerosols in the upper stratosphere as a potential alternative strategy for solar radiation management. Particular future emphasis should be on better understanding the optical, chemical, and photochemical processes for absorbing aerosols in the upper stratosphere, and for modeling studies with more comprehensive models that incorporate this improved knowledge. Further, these results indicate that the impact of volcanic and other natural stratospheric aerosols that may arrive to the upper stratosphere will be strongly dependent on the optical properties of these aerosols.

We note that neither of the atmospheric model configurations we consider (AM2.5 and AM2.1, and the respective coupled models) has interactive aerosols, stratospheric chemistry, or a well-resolved stratosphere [unlike, for example, GFDL’s ESM4 (Dunne et al., 2020), or NCAR’s WACCM6 (Gettelman et al., 2019)]. An advantage of our model configuration is that their efficiency and simple aerosol treatment allow us to explore the climate response to highly controlled aerosol changes. These experiments provide motivation for further, more computationally expensive, work (some ongoing) with more comprehensive models (e.g., models with interactive chemistry in the stratosphere, a better-resolved stratosphere, etc.) to better understand the full response of the system to absorbing aerosols in the stratosphere.

Models and experiments

To evaluate the effectiveness of this strategy, we perform a series of climate model simulations using atmospheric models with prescribed sea surface temperatures (SSTs) and sea ice concentration to explore the altitude dependence in stratospheric aerosol deployments with both reflective and absorptive aerosols. These fixed-SST simulations provide the recommended effective radiative forcing (ERF) diagnostics (Forster et al., 2016), including both the direct radiative effects of the SAI and the additional radiative effects from the climate response to the intervention, such as rapid adjustments, which are substantial for anthropogenic aerosols (Smith et al., 2018). These fixed-SST simulations also help to understand how SAI injection of absorbing aerosols modifies the temperature structure of the stratosphere and the net flow of radiation at the TOA.

A high-resolution global atmosphere model [GFDL-AM2.5 as configured and run in the Princeton University Tiger2 supercomputer (Hsieh et al., 2022; Yang et al., 2021)] is used for a comprehensive set of experiments (Extended Data Table 1). GFDL-AM2.5 is the atmospheric component of the global coupled climate models GFDL-CM2.5 (Delworth et al., 2012) and GFDL-CM2.5-FLOR (Vecchi et al., 2014). The GFDL-AM2.5 has a finite volume cubed-sphere dynamical core at a global 50-km resolution (180 × 180 grid points on each cube face) at 32 vertical levels (Putman & Lin, 2007). In this study, a present-day simulation is integrated for 10 years as a control run in GFDL-AM2.5 with the prescribed SST and sea ice concentration of the monthly climatology of the period 1986–2005, as well as GHG and aerosol concentrations fixed at corresponding levels.

To explore the altitude dependence in stratospheric aerosol deployments, we prescribe 0.5 Tg of horizontally-uniform aerosols separately within each of the highest 7 sigma levels for both BC and SO₄. For SO₄, we perform an additional set of simulations using 5.0 Tg, which provides a more similar ERF to the 0.5 Tg BC forcing. The two sets of SO₄ aerosol simulations can also be used to evaluate the linearity between prescribed SO₄ aerosol mass-burdens and corresponding ERF. The exploration of the altitude dependence in stratospheric aerosol deployments helps to determine the most effective layer for the stratospheric BC aerosol injection experiments. As we demonstrate below, by warming at the altitude where the peak CO₂ absorption band achieves unit optical depth, we are able to maximize the weakening of the CO₂ greenhouse effect.

Next, the global coupled climate model (GFDL-CM2.5-FLOR) is used to evaluate the cooling effects of the stratospheric BC aerosol injection strategy and explore other potential climate impacts of BC deployment relative to the more traditional SO₄ deployments (Extended Data Table 1). The GFDL-CM2.5-FLOR is the forecast-oriented low ocean resolution version of GFDL-CM2.5, with a horizontal resolution of approximately 50 km for the atmosphere and land components developed from GFDL-CM2.5 and a coarser (~ 1°) resolution for the oceanic and sea ice components from GFDL-CM2.1 (Delworth et al., 2006). Before undertaking any specific investigations, we run a 200-year control simulation by maintaining radiative forcing and land use/land cover at the level of the year 1860. Initializing from one year of the control simulation, 0.5 Tg BC and 5.0 Tg SO₄ aerosols are prescribed separately at the most effective layer found in the previous series of fixed-SST simulations and then integrated for 150 years. The cooling effects of the proposed BC intervention strategy are compared with that of the most common solar radiation management with SO₄ aerosol injection. It is worth noting that the high-resolution climate models (GFDL-AM2.5 and GFDL-CM2.5-FLOR) also allow for prospective explorations of the changes in the occurrence of and impacts from extreme weather events (e.g., tropical cyclones and extreme precipitation) to the potential climate interventions. As an initial assessment of the model dependence within the results presented here and in order to conduct multiple ensemble members to minimize the impact of internal variability, a less computationally-expensive GFDL model (GFDL-AM2.1 and corresponding coupled model GFDL-CM2.1) is also adapted to provide further corroboration of our results (Extended Data Table 2).

Methods

To better understand the ERF and the subsequent cooling processes, the radiative kernel method is adopted to decompose the ERF and radiative responses into contributions from each radiatively relevant state variable, including temperature, water vapor, albedo, and cloud (Soden et al., 2008). Host-model radiative kernels derived from the atmospheric model GFDL-AM2.1 are used to provide higher accuracy in the decompositions. Here, the radiative kernel method is used primarily for longwave radiation decomposition.

Although the shortwave water vapor absorptions are also calculated using the radiative kernel method, most shortwave decomposition relies on the approximate partial radiative perturbation (APRP) technique. The APRP technique (Taylor et al., 2007) is applied to decompose perturbations in shortwave radiative flux at the TOA into contributions from changes in surface albedo, non-cloud atmospheric constituents, and clouds. We consider the non-cloud contribution to be the sum of the shortwave water vapor absorptions and the direct effects (e.g., absorption and scattering) of aerosol perturbations. Therefore, the direct effects of aerosol perturbations [or the shortwave instantaneous radiative forcing (IRF)] are calculated as the difference between the non-cloud component from the APRP technique and the shortwave water vapor absorptions of the radiative kernel method.

We chose to use the APRP technique for the shortwave decomposition to avoid prescribing the unknown cloud masking extent required for the shortwave IRF in the radiative kernel method decomposition. Aided by the combined radiative kernel and APRP method, the differences in decomposed components, including the IRF and rapid adjustments of the atmosphere initiated by the two aerosol types, will help to better understand their differences in the resultant ERF.

Competing Interest Statement:

The authors declare no competing interests.

Author Contributions:

H.H., B.J.S., and G.A.V. designed research; H.H. and W.Y. performed research; H.H. analyzed data; H.H., B.J.S., G.A.V., and W.Y. contributed to the interpretation of the results; H.H., B.J.S., and G.A.V. wrote the paper.

Acknowledgments

This work was supported by Award MPS-SRM-00006584 from the Simons Foundation, Award 80NSSC22K0999 from the National Aeronautics and Space Administration, and Award DE-SC0021333 from the United States Department of Energy.

Allen, R. J., Amiri-Farahani, A., Lamarque, J.-F., Smith, C., Shindell, D., Hassan, T., & Chung, C. E. (2019). Observationally constrained aerosol–cloud semi-direct effects. Npj Climate and Atmospheric Science, 2(1), 16.
Bony, S., Stevens, B., Coppin, D., Becker, T., Reed, K. A., Voigt, A., & Medeiros, B. (2016). Thermodynamic control of anvil cloud amount. Proceedings of the National Academy of Sciences, 113(32), 8927–8932.
Delworth, T. L., Broccoli, A. J., Rosati, A., Stouffer, R. J., Balaji, V., Beesley, J. A., et al. (2006). GFDL's CM2 global coupled climate models. Part I: Formulation and simulation characteristics. Journal of Climate, 19(5), 643–674.
Delworth, T. L., Rosati, A., Anderson, W., Adcroft, A. J., Balaji, V., Benson, R., et al. (2012). Simulated climate and climate change in the GFDL CM2.5 high-resolution coupled climate model. Journal of Climate, 25(8), 2755–2781.
Dunne, J. P., Horowitz, L. W., Adcroft, A. J., Ginoux, P., Held, I. M., John, J. G., et al. (2020). The GFDL Earth System Model Version 4.1 (GFDL-ESM 4.1): Overall coupled model description and simulation characteristics. Journal of Advances in Modeling Earth Systems, 12, e2019MS002015.
Edwards, J. M., & Slingo, A. (1996). Studies with a flexible new radiation code. I: Choosing a configuration for a large-scale model. Quarterly Journal of the Royal Meteorological Society, 122(531), 689–719.
Ferraro, A. J., Highwood, E. J., and Charlton-Perez, A. J. (2011). Stratospheric heating by potential geoengineering aerosols. Geophysical Research Letters, 38, L24706.
Forster, P. M., Richardson, T., Maycock, A. C., Smith, C. J., Samset, B. H., Myhre, G., & Schulz, M. (2016). Recommendations for diagnosing effective radiative forcing from climate models for CMIP6. Journal of Geophysical Research: Atmospheres, 121, 12,460–12,475.
Forster, P. M., Smith, C., Walsh, T., Lamb, W. F., Lamboll, R., Hall, B., et al. (2024). Indicators of Global Climate Change 2023: annual update of key indicators of the state of the climate system and human influence. Earth System Science Data, 16(6), 2625–2658.
Gettelman, A., Mills, M. J., Kinnison, D. E., Garcia, R. R., Smith, A. K., Marsh, D. R., et al. (2019). The whole atmosphere community climate model version 6 (WACCM6). Journal of Geophysical Research: Atmospheres, 124, 12380–12403.
He, H., Kramer, R. J., Soden, B. J., & Jeevanjee N. (2023). State dependence of CO2 forcing and its implications for climate sensitivity. Science, 382 (6674), 1051-1056.
Held, I. M., & Soden, B. J. (2006). Robust Responses of the Hydrological Cycle to Global Warming. Journal of Climate, 19(21), 5686–5699.
Hsieh, T.-L., Yang, W., Vecchi, G. A., & Zhao, M. (2022). Model spread in the tropical cyclone frequency and seed propensity index across global warming and ENSO-like perturbations. Geophysical Research Letters, 49, e2021GL097157.
Hueholt, D. M., Barnes, E. A., Hurrell, J. W., Richter, J. H., & Sun, L. (2023). Assessing outcomes in stratospheric aerosol injection scenarios shortly after deployment. Earth's Future, 11, e2023EF003488.
Jeevanjee, N., Seeley, J. T., Paynter, D., & Fueglistaler, S. (2021). An Analytical Model for Spatially Varying Clear-Sky CO2 Forcing. Journal of Climate, 34(23), 9463-9480.
Jones, A. C., Haywood, J. M., & Jones, A. (2016). Climatic impacts of stratospheric geoengineering with sulfate, black carbon and titania injection. Atmospheric Chemistry and Physics, 16(5), 2843–2862.
Kravitz, B., Robock, A., Shindell, D. T., & Miller M. A. (2012). Sensitivity of stratospheric geoengineering with black carbon to aerosol size and altitude of injection, Journal of Geophysical Research: Atmospheres, 117, D09203.
Kravitz, B., Robock, A., Tilmes, S., Boucher, O., English, J. M., Irvine, P. J., Jones, A., Lawrence, M. G., MacCracken, M., Muri, H., Moore, J. C., Niemeier, U., Phipps, S. J., Sillmann, J., Storelvmo, T., Wang, H., & Watanabe, S. (2015). The Geoengineering Model Intercomparison Project Phase 6 (GeoMIP6): Simulation design and preliminary results. Geoscientific Model Development, 8, 3379–3392.
Lawrence, M. G., Schäfer, S., Muri, H., Scott, V., Oschlies, A., Vaughan, N. E., Boucher, O., Schmidt, H., Haywood, J., & Scheffran, J. (2018). Evaluating climate geoengineering proposals in the context of the Paris Agreement temperature goals. Nature Communications, 9(1), 3734.
Long, J. C. S., & Shepherd, J. G. (2014). The strategic value of geoengineering research. Global Environmental Change, Springer, 757–770.
MacMartin, D. G., Ricke, K. L., & Keith, D. W. (2018). Solar geoengineering as part of an overall strategy for meeting the 1.5 °C Paris target. Philosophical Transactions of the Royal Society A, 376, 20160454.
Manners, J., Edwards, J. M., Hill, P., & Thelen, J.-C. (2015). SOCRATES (Suite Of Community RAdiative Transfer codes based on Edwards and Slingo) technical guide. Met Office
Mills, M. J., Toon, O. B., Turco, R. P., Kinnison, D. E., & Garcia, R. R. (2008). Massive global ozone loss predicted following regional nuclear conflict. Proceedings of the National Academy of Sciences of the United States of America, 105(14), 5307–5312.
Putman, W. M., & Lin, S.-J. (2007). Finite-volume transport on various cubed-sphere grids. Journal of Computational Physics, 227(1), 55–78.
Samset, B. H., & Myhre, G. (2011). Vertical dependence of black carbon, sulphate and biomass burning aerosol radiative forcing. Geophysical Research Letters, 38(24), L24802.
Samset, B. H., and G. Myhre (2015), Climate response to externally mixed black carbon as a function of altitude. Journal of Geophysical Research: Atmospheres, 120, 2913–2927.
Simpson, I. R., Tilmes, S., Richter, J. H., Kravitz, B., MacMartin, D. G., Mills, M. J., et al. (2019). The regional hydroclimate response to stratospheric sulfate geoengineering and the role of stratospheric heating. Journal of Geophysical Research: Atmospheres, 124, 12587–12616.
Smith, C. J., Kramer, R. J., Myhre, G., Forster, P. M., Soden, B. J., Andrews, T., et al. (2018). Understanding rapid adjustments to diverse forcing agents. Geophysical Research Letters, 45, 12,023–12,031.
Smith, C. J., Kramer, R. J., Myhre, G., Alterskjær, K., Collins, W., Sima, A., et al. (2020). Effective radiative forcing and adjustments in CMIP6 models. Atmospheric Chemistry and Physics, 20(16), 9591–9618.
Soden, B. J., Held, I. M., Colman, R., Shell, K. M., Kiehl, J. T., & Shields, C. A. (2008). Quantifying climate feedbacks using radiative kernels. Journal of Climate, 21, 3504–3520.
Taylor, K. E., Crucifix, M., Braconnot, P., Hewitt, C. D., Doutriaux, C., Broccoli, A. J., et al. (2007). Estimating Shortwave Radiative Forcing and Response in Climate Models. Journal of Climate, 20(11), 2530–2543.
UNFCCC (2015). Adoption of the Paris Agreement Tech. Rep. FCCC/CP/2015/L.9/Rev.1. https://unfccc.int/resource/docs/2015/cop21/eng/l09r01.pdf
Vecchi, G. A., Delworth, T., Gudgel, R., Kapnick, S., Rosati, A., Wittenberg, A. T., Zeng, F., Anderson, W., Balaji, V., Dixon, K., Jia, L., Kim, H.-S., Krishnamurthy, L., Msadek, R., Stern, W. F., Underwood, S. D., Villarini, G., Yang, X., & Zhang, S. (2014). On the Seasonal Forecasting of Regional Tropical Cyclone Activity. Journal of Climate, 27(21), 7994-8016.
Visioni, D., MacMartin, D. G., Kravitz, B., Richter, J. H., Tilmes, S., & Mills, M. J. (2020). Seasonally modulated stratospheric aerosol geoengineering alters the climate outcomes. Geophysical Research Letters, 47, e2020GL088337.
Xie, S.-P., Deser, C., Vecchi, G. A., Ma, J., Teng, H., & Wittenberg, A. T. (2010). Global Warming Pattern Formation: Sea Surface Temperature and Rainfall*. Journal of Climate, 23(4), 966–986.
Yang, W., Hsieh, T.-L., & Vecchi, G. A. (2021). Hurricane annual cycle controlled by both seeds and genesis probability. Proceedings of the National Academy of Sciences, 118(41), e2108397118.

There is NO Competing Interest.

ExtendedData.docx

Download PDF

Version 1

posted

You are reading this latest preprint version

Weakening the CO2 Greenhouse Effect via Stratospheric Aerosol Injection

Status:

Version 1

Abstract

Figures

1 Introduction

2 Results

2.1 Altitude dependence of effective radiative forcing from prescribed absorptive and reflective aerosols

2.2 Effectiveness in mediating warming and related climate impacts

3 Conclusion and discussion

Materials and Methods

Declarations

Competing Interest Statement:

Author Contributions:

Acknowledgments

References

Additional Declarations

Supplementary Files

Status:

Version 1