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Understanding the weather signal in national crop-yield variability

  • Katja Frieler
  • Bernhard Schauberger
  • Almut Arneth
  • Juraj Balkovič
  • James Chryssanthacopoulos
  • Delphine Deryng
  • Joshua Elliott
  • Christian Folberth
  • Nikolay Khabarov
  • Christoph Müller
  • Stefan Olin
  • Thomas Alan Miller Pugh
  • Sibyll Schaphoff
  • Jacob Schewe
  • Erwin Schmid
  • Lila Warszawski
  • Anders Levermann
Publishing year: 2017-06-20
Language: English
Pages: 605-616
Publication/Series: Earth´s Future
Volume: 5
Issue: 6
Document type: Journal article
Publisher: John Wiley and Sons Inc.

Abstract english

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 United States. 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 provide options to represent human-management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.


  • Environmental Sciences related to Agriculture and Land-use
  • Climate Research
  • Crop yield variability
  • Weather sensitivity


  • ISSN: 2328-4277
E-mail: stefan [dot] olin [at] nateko [dot] lu [dot] se

Postdoctoral fellow

Dept of Physical Geography and Ecosystem Science

+46 46 222 38 30



Department of Physical Geography and Ecosystem Science
Lund University
Sölvegatan 12
S-223 62 Lund

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