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Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios
Concerns over climate change are motivated in large part because of their impact on human society. Assessing the effect of that uncertainty on specific potential impacts is demanding, since it requires a systematic survey over both climate and impacts models. We provide a comprehensive evaluation of uncertainty in projected crop yields for maize, spring and winter wheat, rice, and soybean, using a suite of nine crop models and up to 45 CMIP5 and 34 CMIP6 climate projections for three different forcing scenarios. To make this task computationally tractable, we use a new set of statistical crop model emulators. We find that climate and crop models contribute about equally to overall uncertainty. While the ranges of yield uncertainties under CMIP5 and CMIP6 projections are similar, median impact in aggregate total caloric production is typically more negative for the CMIP6 projections (+1% to −19%) than for CMIP5 (+5% to −13%). In the first half of the 21st century and for individual crops is the spread across crop models typically wider than that across climate models, but we find distinct differences between crops: globally, wheat and maize uncertainties are dominated by the crop models, but soybean and rice are more sensitive to the climate projections. Climate models with very similar global mean warming can lead to very different aggregate impacts so that climate model uncertainties remain a significant contributor to agricultural impacts uncertainty. These results show the utility of large-ensemble methods that allow comprehensively evaluating factors affecting crop yields or other impacts under climate change. The crop model ensemble used here is unbalanced and pulls the assumption that all projections are equally plausible into question. Better methods for consistent model testing, also at the level of individual processes, will have to be developed and applied by the crop modeling community.
A regional nuclear conflict would compromise global food security
A limited nuclear war between India and Pakistan could ignite fires large enough to emit more than 5 Tg of soot into the stratosphere. Climate model simulations have shown severe resulting climate perturbations with declines in global mean temperature by 1.8 °C and precipitation by 8%, for at least 5 y. Here we evaluate impacts for the global food system. Six harmonized state-of-the-art crop models show that global caloric production from maize, wheat, rice, and soybean falls by 13 (±1)%, 11 (±8)%, 3 (±5)%, and 17 (±2)% over 5 y. Total single-year losses of 12 (±4)% quadruple the largest observed historical anomaly and exceed impacts caused by historic droughts and volcanic eruptions. Colder temperatures drive losses more than changes in precipitation and solar radiation, leading to strongest impacts in temperate regions poleward of 30°N, including the United States, Europe, and China for 10 to 15 y. Integrated food trade network analyses show that domestic reserves and global trade can largely buffer the production anomaly in the first year. Persistent multiyear losses, however, would constrain domestic food availability and propagate to the Global South, especially to food-insecure countries. By year 5, maize and wheat availability would decrease by 13% globally and by more than 20% in 71 countries with a cumulative population of 1.3 billion people. In view of increasing instability in South Asia, this study shows that a regional conflict using <1% of the worldwide nuclear arsenal could have adverse consequences for global food security unmatched in modern history.