established23,34,35. Crop models and trade models are applied to simulate the response of crop yield and market 
price under climate change, based on process-based crop growth in daily time steps, either in selected field sites 
or in selected  regions36–39. The statistical regression analysis usually explores the relationship between historical 
crop yields and meteorological records in different sites or counties to establish regression functions for crop 
responses  predictions40–43. These researches have documented that crop yield and price would be threatened 
much more seriously by global warming, especially due to the increasing trend of frequency and intensity of 
climate extreme events in the future.
OPEN
1Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, 
Beijing 100081, China. 2International Maize and Wheat Improvement Center, Texcoco, Mexico. 3Peking University, 
Beijing, China. *email: hqlk2000@163.com