When Will Current Climate Extremes Affecting Maize Production Become the Norm?

We estimate the effects of climate anomalies (heat stress and drought) on annual maize production, variability, and trend from the country level to the global scale using a statistical model. Moderate climate anomalies and extremes are diagnosed with two indicators of heat stress and drought computed over maize growing regions during the most relevant period of maize growth. The calibrated model linearly combines these two indicators into a single Combined Stress Index. The Combined Stress Index explains 50% of the observed global production variability in the period 1980-2010. We apply the model on an ensemble of high-resolution global climate model simulations. Global maize losses, due to extreme climate events with 10-year return times during the period 1980-2010, will become the new normal already at 1.5 degrees C global warming levels (approximately 2020s). At 2 degrees C warming (late 2030s), maize areas will be affected by heat stress and drought never experienced before, affecting many major and minor production regions. Plain Language Summary Global warming is negatively affecting several aspects of ecosystems and societies. This study analyzes the impact of climate on global and regional maize production in the past and in the future. The effects of warmer temperatures and lack of rain on maize production is first analyzed from reported national maize production time series, and these relationships are then projected into the future, using state-of-the-art global climate model simulations. The worse climate events causing the larger maize production losses observed in the past will become normal already at the global warming level of 1.5 degrees C compared to the preindustrial period. Our findings highlight the importance of Paris Agreement mitigation goals to hold the increase of global temperature well below 2 degrees C and pursuing efforts to limit increase to 1.5 degrees C, as well as the need of identifying and adopting efficient adaptation measures.