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An end-to-end assessment of extreme weather impacts on food security

Abstract

Both governments and the private sector urgently require better estimates of the likely incidence of extreme weather events1, their impacts on food crop production and the potential consequent social and economic losses2. Current assessments of climate change impacts on agriculture mostly focus on average crop yield vulnerability3 to climate and adaptation scenarios4,5. Also, although new-generation climate models have improved and there has been an exponential increase in available data6, the uncertainties in their projections over years and decades, and at regional and local scale, have not decreased7,8. We need to understand and quantify the non-stationary, annual and decadal climate impacts using simple and communicable risk metrics9 that will help public and private stakeholders manage the hazards to food security. Here we present an ‘end-to-end’ methodological construct based on weather indices and machine learning that integrates current understanding of the various interacting systems of climate, crops and the economy to determine short- to long-term risk estimates of crop production loss, in different climate and adaptation scenarios. For provinces north and south of the Yangtze River in China, we have found that risk profiles for crop yields that translate climate into economic variability follow marked regional patterns, shaped by drivers of continental-scale climate. We conclude that to be cost-effective, region-specific policies have to be tailored to optimally combine different categories of risk management instruments.

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Figure 1: Schematic diagram of the end-to-end methodology for deriving crop production and economic-risk profiles.
Figure 2: Results of weather index-based modelling of maize yield in Shandong province.
Figure 3: Risk profiles of province-level physical production and aggregate economic loss in China’s northeast Shandong province.

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Acknowledgements

T. Jiang and M. Gemmer of the National Climate Centre of the China Meteorological Administration shared the gridded weather data, C. Yang of the Chinese Academy of Mathematics and System Sciences communicated the provincial input–output tables, and simulated crop data was shared by W. Xiong of the Chinese Academy of Agricultural Sciences. It is a pleasure to thank M. Vrac and P. Naveau of the Laboratoire des Sciences du Climat et de l’Environnement, as well as Maarten Speekenbrink of University College London for many helpful discussions. The work of E.C. was supported by the CONACyT, Mexico, and by the Grantham Institute for Climate Change, Imperial College London. M.G. acknowledges support from the US Department of Energy, grant DE-SC0006694, and from the US National Science Foundation, grant OCE-1243175.

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E.C., G.C. and M.G. designed the study. E.C. obtained the data and carried out the calculations. M.S. provided further insights into the application of risk profiles to market practice. All four authors contributed to the writing.

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Correspondence to Erik Chavez.

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The authors declare no competing financial interests.

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Chavez, E., Conway, G., Ghil, M. et al. An end-to-end assessment of extreme weather impacts on food security. Nature Clim Change 5, 997–1001 (2015). https://doi.org/10.1038/nclimate2747

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