Uncertainty in future agro-climate projections in the United States and benefits of greenhouse gas mitigation

Scientific challenges exist on how to extract information from thewide range of projected impacts simulated by cropmodels driven by climate ensembles. A stronger focus is required to understand and identify themechanisms and drivers of projected changes in crop yield. In this study, we investigate the robustness of future projections offivemetrics relevant to agriculture stakeholders (accumulated frost days, dry days, growing season length, plant heat stress and start offield operations).We use a large ensemble of climate simulations by theMIT IGSM-CAM integrated assessmentmodel that accounts for the uncertainty associatedwith different emissions scenarios, climate sensitivities, and representations of natural variability. By the end of the century, theUS is projected to experience fewer frosts, a longer growing season,more heat stress and an earlier start offield operations—although the magnitude and even the sign of these changes vary greatly by regions. Projected changes in dry days are shownnot to be robust.We highlight the important role of natural variability, in particular for changes in dry days (a precipitation-related index) and heat stress (a threshold index). Thewide range of our projections compares well the CMIP5multi-model ensemble, especially for temperature-related indices. This suggests that using a single climatemodel that accounts for key sources of uncertainty can provide an efficient and complementary framework to themore common approach ofmultimodel ensembles.We also show that greenhouse gasmitigation has the potential to significantly reduce adverse effects (heat stress, risks of pest and disease) of climate change on agriculture, while also curtailing potentially beneficial impacts (earlier planting, possibility formultiple cropping). A major benefit of climatemitigation is potentially preventing changes in several indices to emerge from the noise of natural variability, even by 2100. This hasmajor implications considering that any significant climate change impacts on crop yieldwould result in nation-wide changes in the agriculture sector. Finally, we argue that the analysis of agro-climate indices shouldmore often complement crop model projections, as they can provide valuable information to better understand the drivers of changes in crop yield and production and thus better inform adaptation decisions.