Climate change has the potential to be a source of increased variability if crops are more frequently exposed to damaging weather conditions. Yield variability could respond to a shift in the frequency of extreme events to which crops are susceptible, or if weather becomes more variable. Here we focus on the United States, which produces about 40% of the world’s maize, much of it in areas that are expected to see increased interannual variability in temperature. We combine a statistical crop model based on historical climate and yield data for 1950–2005 with temperature and precipitation projections from 15 different global circulation models. Holding current growing area constant, aggregate yields are projected to decrease by an average of 18% by 2030–2050 relative to 1980–2000 while the coefficient of variation of yield increases by an average of 47%. Projections from 13 out of 15 climate models result in an aggregate increase in national yield coefficient of variation, indicating that maize yields are likely to become more volatile in this key growing region without effective adaptation responses. Rising CO₂ could partially dampen this increase in variability through improved water use efficiency in dry years, but we expect any interactions between CO₂ and temperature or precipitation to have little effect on mean yield changes.

An important source of uncertainty in anticipating the effects of climate change on agriculture is limited understanding of crop responses to extremely high temperatures. This uncertainty partly reflects the relative lack of observations of crop behaviour in farmers’ fields under extreme heat. We used nine years of satellite measurements of wheat growth in northern India to monitor rates of wheat senescence following exposure to temperatures greater than 34 °C. We detect a statistically significant acceleration of senescence from extreme heat, above and beyond the effects of increased average temperatures. Simulations with two commonly used process-based crop models indicate that existing models underestimate the effects of heat on senescence. As the onset of senescence is an important limit to grain filling, and therefore grain yields, crop models probably underestimate yield losses for +2 °C by as much as 50% for some sowing dates. These results imply that warming presents an even greater challenge to wheat than implied by previous modelling studies, and that the effectiveness of adaptations will depend on how well they reduce crop sensitivity to very hot days.

Crop models predict that recent and future climate change may have adverse effects on crop yields. Intentional deflection of sunlight away from the Earth could diminish the amount of climate change in a high-CO₂ world. However, it has been suggested that this diminution would come at the cost of threatening the food and water supply for billions of people. Here, we carry out high-CO₂, geoengineering and control simulations using two climate models to predict the effects on global crop yields. We find that in our models solar-radiation geoengineering in a high-CO₂ climate generally causes crop yields to increase, largely because temperature stresses are diminished while the benefits of CO₂ fertilization are retained. Nevertheless, possible yield losses on the local scale as well as known and unknown side effects and risks associated with geoengineering indicate that the most certain way to reduce climate risks to global food security is to reduce emissions of greenhouse gases.

Perennial crops are among the most valuable of California’s diverse agricultural products. They are also potentially the most influenced by information on future climate, since individual plants are commonly grown for more than 30 years. This study evaluated the impacts of future climate changes on the 20 most valuable perennial crops in California, using a combination of statistical crop models and downscaled climate model projections. County records on crop harvests and weather from 1980 to 2005 were used to evaluate the influence of weather on yields, with a series of cross-validation and sensitivity tests used to evaluate the robustness of perceived effects. In the end, only four models appear to have a clear weather response based on historical data, with another four presenting significant but less robust relationships. Projecting impacts of climate trends to 2050 using historical relationships reveals that cherries are the only crop unambiguously threatened by warming, with no crops clearly benefiting from warming. Another robust result is that almond yields will be harmed by winter warming, although this effect may be counteracted by beneficial warming in spring and summer. Overall, the study has advanced understanding of climate impacts on California agriculture and has highlighted the importance of measuring and tracking uncertainties due to the difficulty of uncovering crop-climate relationships.

This paper was prepared for Stanford University’s Global Food Policy and Food Security Symposium Series, hosted by the Center on Food Security and the Environment, and supported by the Bill and Melinda Gates Foundation.

Food policy makers are increasingly faced with the question of how to adapt to climate change. The increased attention on climate adaptation is partly related to the fact that greenhouse gas emissions and climate change show little sign of slowing, partly because of prospects for large sums of money devoted to adaptation, and partly because of well publicized recent weather events that have affected agricultural regions and rattled global food markets. A common and reasonable reaction from the food policy and agricultural community has been to argue that climate variations have always been a challenge to agriculture, and that climate change just makes addressing these variations more important. A logical conclusion from this perspective is to emphasize activities that help build resilience to unpredictable weather events, as well as to focus on the types of weather variables that exhibit a lot of year-to-year variability and cause the bulk of farmers’ concerns in current climate.

However reasonable as a starting point, this perspective is misguided and risks taking a challenging problem and making it even harder. Anthropogenic global warming (AGW) is fundamentally different from the natural variations driven by internal dynamics in the climate system. Indeed, predicting the course of climate change is less like predicting the weather next week than it is like predicting that summer will be warmer than winter. Progress in climate science has shown that the most indelible hallmarks of AGW will be increased occurrence and severity of high temperature and heavy rainfall extremes in all regions, and increased frequency and severity of drought in sub-tropical regions. Changes in the timing and amount of seasonal rainfall also appear likely in some regions, but at a much smaller pace relative to natural variability. In all of these cases, predictions from climate science are most robust at broader spatial scales, with considerable uncertainty in predicting changes for any single country.

Meanwhile, progress in crop science has shown that most crops show fairly rapid declines in productivity as temperatures rise above critical thresholds, with as much as 10 percent yield loss for +1°C of warming in some locations. Both sub-Saharan Africa and South Asia appear particularly prone to productivity losses from climate change, in part because major staples in these regions are often already grown well above their optimum temperature.

Approaches to climate adaptation should recognize these realities, and should not equate anticipating climate changes with the considerably harder task of predicting next year’s weather. Predicting and building resilience to climate variability still remain important goals for agricultural development, but adaptation efforts should balance these activities with those focused more on the specific threats presented by climate change. Heat tolerant crop varieties and strategies to deal with heavy rainfall provide two examples of important needs. Similarly, balance is needed between the local-scale efforts that attract most of adaptation investment currently, and regional and global networks to develop needed technologies. Given the greater certainty of climate changes at broader scales, as well as the positive track record of international networks for crop breeding, investments in these global systems are very likely to deliver substantial adaptation benefits. Finally, given the downward pressures that climate change will exert on smallholder farm productivity in sub-Saharan Africa, and the critical role productivity gains play in catalyzing an escape from poverty, speeding the pace of investment in African agriculture can also be viewed as a good bet for climate adaptation.