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Optimal climate intervention scenarios for crop production vary by nation

Nature Food volume 4, pages 902–911 (2023)Cite this article

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Abstract

Stratospheric aerosol intervention (SAI) is a proposed strategy to reduce the effects of anthropogenic climate change. There are many temperature targets that could be chosen for a SAI implementation, which would regionally modify climatically relevant variables such as surface temperature, precipitation, humidity, total solar radiation and diffuse radiation. In this work, we analyse impacts on national maize, rice, soybean and wheat production by looking at output from 11 different SAI scenarios carried out with a fully coupled Earth system model coupled to a crop model. Higher-latitude nations tend to produce the most calories under unabated climate change, while midlatitude nations maximize calories under moderate SAI implementation and equatorial nations produce the most calories from crops under high levels of SAI. Our results highlight the challenges in defining ‘globally optimal’ SAI strategies, even if such definitions are based on just one metric.

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Fig. 1: Climate impacts of SAI and climate change scenarios.
Fig. 2: Crop production impacts under SAI scenarios relative to climate change.
Fig. 3: Crop production changes for top producers under SAI relative to climate change.
Fig. 4: Climate change or SAI scenario that produces the most calories for each nation under SSP2-4.5.
Fig. 5: Climate change or SAI scenario that produces the most calories for each nation under SSP5-8.5.
Fig. 6: Climate change or SAI scenario that produces the most calories for each nation under SSP5-3.4-OS.
Fig. 7: Individual climate impacts on crop production under SAI relative to climate change.

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Data availability

Output from the CESM2(WACCM6) SSP2-4.5 and SSP2-4.5-1.5 °C is freely available at https://doi.org/10.26024/0cs0-ev98. CESM2(WACCM6) output from SSP5-8.5, SSP5-3.4-OS, Geoengineering Model Intercomparison Project G6Solar and G6Sulfur is freely available on Earth System Grid at https://esgf-node.llnl.gov/search/cmip6/. CESM2(WACCM6) output from SSP5-3.4-OS-2.0 °C, SSP5-3.4-OS-1.5 °C and SSP5-8.5-1.5 °C is available at https://doi.org/10.26024/t49k-1016. Coupled and offline CLM5crop postprocessed yield data are available at https://doi.org/10.6084/m9.figshare.24085797.v1. Historical yield observation data were obtained from FAOSTAT at https://www.fao.org/faostat/en/#data.

Code availability

The source code for the CESM(WACCM) model used in this study is freely available at https://www.cesm.ucar.edu/working_groups/Whole-Atmosphere/code-release.html, and the code for CLM5 is available at https://www.cesm.ucar.edu/models/cesm2/land/. Postprocessing and figure generation scripts can be found at https://github.com/bjc204/Clark_etal_NatureFood_2023.

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Acknowledgements

This work was supported by NSF grant nos. AGS-2017113 and ENG-2028541 awarded to A.R. and L.X. and by a gift from SilverLining’s Safe Climate Research Initiative. This material is based on work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the NSF under cooperative agreement no. 1852977. Computing and data storage resources, including the Cheyenne supercomputer (https://doi.org/10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory at the National Center for Atmospheric Research. We thank H. Stephens for developing the yield conversion script.

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Authors and Affiliations

  1. Department of Environmental Sciences, Rutgers University, New Brunswick, NJ, USA

    Brendan Clark, Lili Xia, Alan Robock & Sam S. Rabin

  2. Atmospheric Chemistry, Observations, and Modeling Laboratory, National Center for Atmospheric Research, Boulder, CO, USA

    Simone Tilmes

  3. Climate Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, USA

    Jadwiga H. Richter & Sam S. Rabin

  4. Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY, USA

    Daniele Visioni

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Contributions

B.C., L.X. and A.R. designed the study. S.T., J.H.R. and D.V. conducted the climate model simulations. B.C., S.S.R. and L.X. conducted the offline crop model simulations. B.C. analysed the data with contributions from all the authors. B.C., L.X. and A.R. wrote the first draft, and all authors contributed to editing and revising the paper.

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Correspondence to Brendan Clark.

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Clark, B., Xia, L., Robock, A. et al. Optimal climate intervention scenarios for crop production vary by nation. Nat Food 4, 902–911 (2023). https://doi.org/10.1038/s43016-023-00853-3

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