Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project's Global Gridded Crop Model Intercomparison based on CMIP5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new 21st-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to −6% (SSP126) and from +1% to −24% (SSP585)-explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO 2 concentrations and expanded high-latitude gains. The 'emergence' of climate impacts consistently occurs earlier in the new projectionsbefore 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.

Although biophysical yield responses to local warming have been studied, we know little about how crop yield growth—a function of climate and technology—responds to global temperature and socioeconomic changes. Here, we present the yield growth of major crops under warming conditions from preindustrial levels as simulated by a global gridded crop model. The results revealed that global mean yields of maize and soybean will stagnate with warming even when agronomic adjustments are considered. This trend is consistent across socioeconomic assumptions. Low-income countries located at low latitudes will benefit from intensive mitigation and from associated limited warming trends (1.8 °C), thus preventing maize, soybean and wheat yield stagnation. Rice yields in these countries can improve under more aggressive warming trends. The yield growth of maize and soybean crops in high-income countries located at mid and high latitudes will stagnate, whereas that of rice and wheat will not. Our findings underpin the importance of ambitious climate mitigation targets for sustaining yield growth worldwide.

The Global Risk Assessment toward Stable Production of Food (GRASP) project uses global crop models to evaluate the impacts on global food security by changes in climate extremes, water resources, and land use. Such models require meteorological forcing data. This study presents the development of the GRASP forcing data that is a hybrid of the reanalyses (ERA-40 and JRA-25) and observations. The GRASP data offer daily mean, maximum, and minimum 2 m air temperatures as well as precipitation, solar radiation, vapor pressure, and 10 m wind speed over global land areas, excluding Antarctica, for the period 1961-2010 at a grid size of 1.125°. The monthly climatologies of the variables of the GRASP data were forced to be close to those of the observations for the baseline period (1961-1990 or 1983-2005) through bias corrections. The GRASP data are intercompared with other forcing data for land surface modeling (the S06, WATCH Forcing Data, and WATCH Forcing Data Methodology Applied to ERA-Interim data). The results demonstrate that the daily minimum temperature, diurnal temperature range, vapor pressure, solar radiation, and wind speed from the GRASP data are more valuable for crop modeling than the reanalyses and other forcing data. For remaining variables, the reliability of the GRASP data is higher than that of the reanalyses and on a similar level with that of the other forcing data. The GRASP data offer accurate estimates of daily weather as the inputs for crop models, providing unique opportunities to link historical changes in climate with crop production over the last half century.

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