Understanding the weather signal in national crop-yield variability

14616 12 77700 2 214582 document 77700 Frieler_et_al-2017-Earth's_Future.pdf application/pdf 7c805f7b067d04ad0af09d140118823d MD5 1033531 2017-05-22 08:55:34 https://pure.iiasa.ac.at/id/eprint/14616/1/Frieler_et_al-2017-Earth%27s_Future.pdf 14616 1 1 application/pdf text en public cc_by_nc

Frieler_et_al-2017-Earth's_Future.pdf

77702 2 214593 document 77702 lightbox.jpg image/png c9a01e3ad3b35076b71618a5a4b916e6 MD5 53927 2017-05-22 09:05:41 https://pure.iiasa.ac.at/id/eprint/14616/2/lightbox.jpg 14616 2 2 image/png other Thumbnails conversion from text to thumbnail_lightbox en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/77700 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/77700 http://eprints.org/relation/isIndexCodesVersionOf https://pure.iiasa.ac.at/id/document/77700 archive 5 disk0/00/01/46/16 2017-05-22 08:59:38 2021-08-27 17:29:01 2017-05-22 08:59:38 article show Frieler K. Schauberger B. Arneth A. Balkovic J. 1977 0000-0003-2955-4931 Chryssanthacopoulos J. Deryng D. Elliott J. Folberth C. 2033 0000-0002-6738-5238 Khabarov N. 1850 0000-0001-5372-4668 Müller C. Olin S. Pugh T.A.M. Schaphoff S. Schewe J. Schmidt E. Warszawski L. Levermann A. Understanding the weather signal in national crop-yield variability pub prog_esm Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather-induced crop-yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state-of-the-art, process-based crop model simulations. We find that observed weather variations can explain more than 50% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50% in seven countries, including the US. The explained variance exceeds 50% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop-yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process-based crop models not only account for weather influences on crop yields, but also represent human-management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations. 2017-08 published Wiley 10.1002/2016EF000525 23 92 151 public Earth's Future 5 6 605-616 TRUE 23284277 FALSE yes info:eu-repo/grantAgreement/EC/FP7/603542/EU/Land use change: assessing the net climate forcing, and options for climate change mitigation and adaptation/LUC4C; info:eu-repo/grantAgreement/EC/FP7/603864/EU/ High-End cLimate Impacts and eXtremes/HELIX info:eu-repo/semantics/article info:eu-repo/semantics/openAccess