Letter

Simulating US agriculture in a modern Dust Bowl drought

  • Nature Plants 3, Article number: 16193 (2016)
  • doi:10.1038/nplants.2016.193
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Abstract

Drought-induced agricultural loss is one of the most costly impacts of extreme weather1,​2,​3, and without mitigation, climate change is likely to increase the severity and frequency of future droughts4,5. The Dust Bowl of the 1930s was the driest and hottest for agriculture in modern US history. Improvements in farming practices have increased productivity, but yields today are still tightly linked to climate variation6 and the impacts of a 1930s-type drought on current and future agricultural systems remain unclear. Simulations of biophysical process and empirical models suggest that Dust-Bowl-type droughts today would have unprecedented consequences, with yield losses 50% larger than the severe drought of 2012. Damages at these extremes are highly sensitive to temperature, worsening by 25% with each degree centigrade of warming. We find that high temperatures can be more damaging than rainfall deficit, and, without adaptation, warmer mid-century temperatures with even average precipitation could lead to maize losses equivalent to the Dust Bowl drought. Warmer temperatures alongside consecutive droughts could make up to 85% of rain-fed maize at risk of changes that may persist for decades. Understanding the interactions of weather extremes and a changing agricultural system is therefore critical to effectively respond to, and minimize, the impacts of the next extreme drought event.

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Acknowledgements

This research was performed as part of the Center for Robust Decision-making on Climate and Energy Policy (RDCEP) at the University of Chicago. RDCEP is funded by a grant from NSF (no. SES-0951576) through the Decision Making Under Uncertainty program. M.G. acknowledges support of an NSF Graduate Fellowship (no. DGE-1144082). We thank C. Müller, A. Ruane and J. Winter—as well as the AgMIP (Agricultural Model Intercomparison and Improvement Project) community—for valuable insight in formulating the ideas for this research. We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, and we thank the climate modelling 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 software infrastructure development in partnership with the Global Organization for Earth System Science Portals. Computing for this project was facilitated using the Swift parallel scripting language (NSF grant OCI-1148443), and completed in part with resources provided by the University of Chicago Research Computing Center.

Author information

Author notes

    • Michael Glotter
    •  & Joshua Elliott

    These authors contributed equally to this work.

Affiliations

  1. Department of the Geophysical Sciences, University of Chicago, 5734 S Ellis Avenue, Chicago, Illinois 60637, USA

    • Michael Glotter
  2. NASA Goddard Institute for Space Studies, 2880 Broadway, New York, New York 10025, USA

    • Joshua Elliott
  3. Computation Institute, University of Chicago, 5735 S Ellis Avenue, Chicago, Illinois 60637, USA

    • Joshua Elliott

Authors

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Contributions

M.G. and J.E. contributed equally to this work. Both authors designed and performed the experiments, analysed the data, discussed the results, and wrote the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Michael Glotter or Joshua Elliott.

Supplementary information

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    Supplementary Information

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