• climate change;
  • crop yield change;
  • probabilistic projections

[1] There is a widely recognized need in the scientific and policy communities for probabilistic estimates of climate change impacts, beyond simple scenario analysis. Here we propose a methodology to evaluate one major climate change impact - changes in global average yields of wheat, maize, and barley by 2030 - by a probabilistic approach that integrates uncertainties in climate change and crop yield responses to temperature, precipitation, and carbon dioxide. The resulting probability distributions, which are conditional on assuming the SRES A1B emission scenario and no agricultural adaptation, indicate expected changes of +1.6%, −14.1%, −1.8% for wheat, maize, and barley, with 95% probability intervals of (−4.1, +6.7), (−28.0, −4.3), (−11.0, 6.2) in percent of current yields, respectively. This fully probabilistic analysis aims at quantifying the range of plausible outcomes and allows us to gauge the relative importance of different sources of uncertainty.