Abstract

Solar geoengineering (SG) has the potential to restore average surface temperatures by increasing planetary albedo1,2,3,4, but this could reduce precipitation5,6,7. Thus, although SG might reduce globally aggregated risks, it may increase climate risks for some regions8,9,10. Here, using the high-resolution forecast-oriented low ocean resolution (HiFLOR) model—which resolves tropical cyclones and has an improved representation of present-day precipitation extremes11,12alongside 12 models from the Geoengineering Model Intercomparison Project (GeoMIP), we analyse the fraction of locations that see their local climate change exacerbated or moderated by SG. Rather than restoring temperatures, we assume that SG is applied to halve the warming produced by doubling CO2 (half-SG). In HiFLOR, half-SG offsets most of the CO2-induced increase of simulated tropical cyclone intensity. Moreover, neither temperature, water availability, extreme temperature nor extreme precipitation are exacerbated under half-SG when averaged over any Intergovernmental Panel on Climate Change (IPCC) Special Report on Extremes (SREX) region. Indeed, for both extreme precipitation and water availability, less than 0.4% of the ice-free land surface sees exacerbation. Thus, while concerns about the inequality of solar geoengineering impacts are appropriate, the quantitative extent of inequality may be overstated13.

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Data availability

The GeoMIP and CMIP5 data used in this study are available on the Earth System Grid (https://www.earthsystemgrid.org/), the processed HiFLOR data used in this study will be made available upon request.

Additional information

Journal peer review information: Nature Climate Change thanks Trude Storelvmo, Claudia Timmreck and other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Acknowledgements

We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We thank all participants of the Geoengineering Model Intercomparison Project and their model development teams, CLIVAR/WCRP Working Group on Coupled Modeling for endorsing GeoMIP and the scientists managing the Earth System Grid data nodes who have assisted with making GeoMIP output available. The authors acknowledge the help of C. Curry who provided the extreme indices data for the GeoMIP ensemble. The authors thank M. Mostefaoui for her help in preparing the synthetic tropical cyclone data sets. The authors acknowledge R. Stanhope for help finalizing the figures. The authors thank D. Fahey and K. Caldeira for comments on the draft and L. Miller, G. Wagner and D. Kluger for helpful discussions on the statistical approach.

Author information

Affiliations

  1. John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA

    • Peter Irvine
    •  & David Keith
  2. Lorenz Center, Massachusetts Institute of Technology, Cambridge, MA, USA

    • Kerry Emanuel
  3. The Program in Atmospheric and Oceanic Sciences, Princeton University, Princeton, NJ, USA

    • Jie He
  4. National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA

    • Jie He
    •  & Larry W. Horowitz
  5. School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA

    • Jie He
  6. Department of Geosciences and the Princeton Environmental Institute, Princeton University, Princeton, NJ, USA

    • Gabriel Vecchi

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Contributions

P.I., D.K. and G.V. conceived and designed the study. P.I. and D.K. developed the analysis approach. G.V. and L.W.H. performed the HiFLOR simulations and K.E. performed the downscaled tropical cyclone simulations. P.I. and J.H. analysed the main results. K.E. analysed the tropical cyclone results. P.I. and D.K. wrote the paper.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Peter Irvine.

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    Supplementary Figures 1–5, Supplementary Tables 1–5

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https://doi.org/10.1038/s41558-019-0398-8