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Net benefits to US soy and maize yields from intensifying hourly rainfall


Many varieties of short-duration extreme weather pose a threat to global crop production, food security and farmer livelihoods1,2,3,4. Hourly exposure to extreme heat has been identified as detrimental to crop yields1,5; however, the influence of hourly rainfall intensity and extremes on yields remains unknown4,6,7. Here, we show that while maize and soy yields in the United States are severely damaged by the rarest hourly rainfall extremes (≥50 mm hr−1), they benefit from heavy rainfall up to 20 mm hr−1, roughly the heaviest downpour of the year on average. We also find that yields decrease in response to drizzle (0.1–1 mm hr−1), revealing a complex pattern of yield sensitivity across the range of hourly intensities. We project that crop yields will benefit by ~1–3% on average due to projected future rainfall intensification under climate warming8,9, slightly offsetting the larger expected yield declines from excess heat, with the benefits of more heavy rainfall hours outweighing the damages due to additional extremes. Our results challenge the view that an increasing frequency of high-intensity rainfall events poses an unequivocal risk to crop yields2,7,10 and provide insights that may guide adaptive crop management and improve crop models.

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Fig. 1: Sensitivity of maize and soy yields to hourly rainfall intensity.
Fig. 2: Frequency distribution of hourly rainfall intensities.
Fig. 3: Crop yield sensitivity to rainfall distribution across timescales.
Fig. 4: Current and projected future net yield impacts of hourly rainfall intensity.

Data availability

All datasets supporting the results of this paper are freely available from the references and links listed in Supplementary Table 4. The compiled dataset is available at Source data are provided with this paper.

Code availability

The processing and analysis codes are hosted at


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This material is based on work supported by the National Science Foundation Graduate Research Fellowship under grant no. DGE–1644869. Additional funding was provided by the Department of Interior Northeast Climate Adaptation Science Center and grant no. G16AC00256 from the United States Geological Survey. We thank N. Lenssen, J. Mankin, D. Singh, W. Anderson, R. DeFries and M. Ting for constructive feedback on the methods and results.

Author information




C.L. and E.C. designed and coordinated the research and conducted the analysis. All authors discussed the results and wrote the manuscript.

Corresponding author

Correspondence to Corey Lesk.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Ethan Butler, Yan Li and Deepak Ray 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.

Extended data

Extended Data Fig. 1 Correlation between the incidence of hourly rainfall intensities and seasonal total rainfall, extreme heat, and maximum daily rainfall.

Correlation coefficient of seasonal occurrence (hours) of rainfall of given intensities with seasonal total rainfall, killing degree days, and maximum daily rainfall, with annotated zones of significant positive (green) and negative (red) yield response (P < 0.05).

Source data

Extended Data Fig. 2 Regional maize and soy yield sensitivity to drizzle and heavy rainfall.

a) Schematic map of regional boundaries. Northeast is defined as latitude ≥40°N, east of 93°W, southeast as latitude <40°N, east of 93°W, and west as 93 to 104°W. b) Regional variation in the incidence of differing rainfall intensities, as percent deviation from the national mean incidence (Fig. 2). Regional mean county-level yield sensitivity (±SE) to hourly rainfall intensity per hour of exposure for ce) maize, and fh) soy. Extreme rainfall bins >40 mm hr−1 are omitted due to insufficient data for sample stratification. Sensitivities are plotted on symmetric logarithmic axes, with correspondingly transformed relative error bars. Green and red points indicate significant positive and negative sensitivities (two-sided P < 0.05).

Source data

Extended Data Fig. 3 Maize and soy yield sensitivity to drizzle and heavy rainfall among counties with more and less extensive irrigation.

Mean county-level yield sensitivity (±SE) to hourly rainfall intensity per hour of exposure for a, b) counties with less than 5% of crop area irrigated, and c, d) counties with more than 5% crop area irrigated (see Methods). Results are shown for maize in a) and c), and for soy in b) and d). Extreme rainfall bins >40 mm hr−1 are omitted due to insufficient data for sample stratification. Sensitivities are plotted on symmetric logarithmic axes, with correspondingly transformed relative error bars. Dark green and red points indicate significant positive and negative sensitivities (two-sided P < 0.05), while pink and light green points denote weakly significant effects (two-sided P < 0.1). The total counties analyzed is less than for the other analyses as irrigation data is not available for all counties.

Source data

Extended Data Fig. 4 Projected future incidence of heavy and extreme rainfall under climate warming.

Intensified distributions of heavy and extreme hourly rainfall under idealized warming of 1, 2 and 4 K projected by shifting the 2002–2017 baseline distribution (black curve, Fig. 2) under a) the uniform low-change scenario, b) the uniform high-change scenario, and c) the amplified scenario with greater intensification for higher intensities.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–8 and Tables 1–5.

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Source Data Extended Data Fig. 1

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Source data for Extended Data Fig. 3.

Source Data Extended Data Fig. 4

Source data for Extended Data Fig. 4.

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Lesk, C., Coffel, E. & Horton, R. Net benefits to US soy and maize yields from intensifying hourly rainfall. Nat. Clim. Chang. 10, 819–822 (2020).

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