Non-linear relationships between daily temperature extremes and US agricultural yields uncovered by global gridded meteorological datasets.

Global agricultural commodity markets are highly integrated among major producers. Prices are driven by aggregate supply rather than what happens in individual countries in isolation. Estimating the effects of weather-induced shocks on production, trade patterns and prices hence requires a globally representative weather data set. Recently, two data sets that provide daily or hourly records, GMFD and ERA5-Land, became available. Starting with the US, a data rich region, we formally test whether these global data sets are as good as more fine-scaled country-specific data in explaining yields and whether they estimate similar response functions. While GMFD and ERA5-Land have lower predictive skill for US corn and soybeans yields than the fine-scaled PRISM data, they still correctly uncover the underlying non-linear temperature relationship. All specifications using daily temperature extremes under any of the weather data sets outperform models that use a quadratic in average temperature. Correctly capturing the effect of daily extremes has a larger effect than the choice of weather data. In a second step, focusing on Sub Saharan Africa, a data sparse region, we confirm that GMFD and ERA5-Land have superior predictive power to CRU, a global weather data set previously employed for modeling climate effects in the region.

Violent conflict exacerbated drought-related food insecurity between 2009 and 2019 in sub-Saharan Africa.

Conflict, drought and locusts are leading concerns for African food security but the relative importance and spatiotemporal scale of crises resulting from each hazard is poorly characterized. Here we use continuous, subnational data to demonstrate that the rise of food insecurity across sub-Saharan Africa that began in 2014 is attributable to an increase in violent conflict, particularly in South Sudan and Nigeria. Although drought remains a leading trigger of food crises, the prevalence of drought-related crises did not increase from 2009 to 2018. When exposed to drought, pastoralists experienced more widespread, severe and long-lasting food crises than people living in agricultural zones. Food insecurity remained elevated in pastoral regions for 2 years following a drought, while agricultural regions returned to pre-drought food-security levels in ~12 months. The few confirmed famines during the 2009-2018 period coincided with both conflict and drought, while locusts had little effect on food security during this period.

Publisher Correction: The Effects of Extreme Weather on Apple Quality.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The Effects of Extreme Weather on Apple Quality.

A large literature has documented the effects of weather on agricultural yields. However, weather not only impacts the quantity produced, but also the quality of the product. Due to data limitations, the quality effects have primarily been studied using lab experiments for specific attributes, and the financial implications for farmers of a quality effect are less clear. Using a unique longitudinal micro-level data set of Swiss apple orchards that include information on both the quantity produced as well as the quality, we show that the latter can have an even larger effect on farm revenue. Ignoring the quality of the harvested product substantially biases the impact of weather extremes on agricultural income and the potential effects of climate change. Our quality measure is the orchard-year specific price shock. If an orchard gets a lower price for its specific apple variety compared to previous years and compared to other orchards in the same year, we observe the market's valuation of its inferior quality accounting for overall price movements (other orchards growing same variety that year) as well as orchard specific factors (orchard fixed effects). We find that spring frost events induce farm gate price drops and thus revenue reductions of up to 2.05% per hour of exposure.

Estimating global agricultural effects of geoengineering using volcanic eruptions.

Solar radiation management is increasingly considered to be an option for managing global temperatures1,2, yet the economic effects of ameliorating climatic changes by scattering sunlight back to space remain largely unknown3. Although solar radiation management may increase crop yields by reducing heat stress4, the effects of concomitant changes in available sunlight have never been empirically estimated. Here we use the volcanic eruptions that inspired modern solar radiation management proposals as natural experiments to provide the first estimates, to our knowledge, of how the stratospheric sulfate aerosols created by the eruptions of El Chichón and Mount Pinatubo altered the quantity and quality of global sunlight, and how these changes in sunlight affected global crop yields. We find that the sunlight-mediated effect of stratospheric sulfate aerosols on yields is negative for both C4 (maize) and C3 (soy, rice and wheat) crops. Applying our yield model to a solar radiation management scenario based on stratospheric sulfate aerosols, we find that projected mid-twenty-first century damages due to scattering sunlight caused by solar radiation management are roughly equal in magnitude to benefits from cooling. This suggests that solar radiation management-if deployed using stratospheric sulfate aerosols similar to those emitted by the volcanic eruptions it seeks to mimic-would, on net, attenuate little of the global agricultural damage from climate change. Our approach could be extended to study the effects of solar radiation management on other global systems, such as human health or ecosystem function.

Asylum applications respond to temperature fluctuations.

International negotiations on climate change, along with recent upsurges in migration across the Mediterranean Sea, have highlighted the need to better understand the possible effects of climate change on human migration-in particular, across national borders. Here we examine how, in the recent past (2000-2014), weather variations in 103 source countries translated into asylum applications to the European Union, which averaged 351,000 per year in our sample. We find that temperatures that deviated from the moderate optimum (~20°C) increased asylum applications in a nonlinear fashion, which implies an accelerated increase under continued future warming. Holding everything else constant, asylum applications by the end of the century are predicted to increase, on average, by 28% (98,000 additional asylum applications per year) under representative concentration pathway (RCP) scenario 4.5 and by 188% (660,000 additional applications per year) under RCP 8.5 for the 21 climate models in the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP).

Consistent negative response of US crops to high temperatures in observations and crop models.

High temperatures are detrimental to crop yields and could lead to global warming-driven reductions in agricultural productivity. To assess future threats, the majority of studies used process-based crop models, but their ability to represent effects of high temperature has been questioned. Here we show that an ensemble of nine crop models reproduces the observed average temperature responses of US maize, soybean and wheat yields. Each day >30 °C diminishes maize and soybean yields by up to 6% under rainfed conditions. Declines observed in irrigated areas, or simulated assuming full irrigation, are weak. This supports the hypothesis that water stress induced by high temperatures causes the decline. For wheat a negative response to high temperature is neither observed nor simulated under historical conditions, since critical temperatures are rarely exceeded during the growing season. In the future, yields are modelled to decline for all three crops at temperatures >30 °C. Elevated CO2 can only weakly reduce these yield losses, in contrast to irrigation.

Greater sensitivity to drought accompanies maize yield increase in the U.S. Midwest.

A key question for climate change adaptation is whether existing cropping systems can become less sensitive to climate variations. We use a field-level data set on maize and soybean yields in the central United States for 1995 through 2012 to examine changes in drought sensitivity. Although yields have increased in absolute value under all levels of stress for both crops, the sensitivity of maize yields to drought stress associated with high vapor pressure deficits has increased. The greater sensitivity has occurred despite cultivar improvements and increased carbon dioxide and reflects the agronomic trend toward higher sowing densities. The results suggest that agronomic changes tend to translate improved drought tolerance of plants to higher average yields but not to decreasing drought sensitivity of yields at the field scale.

Something in the water: contaminated drinking water and infant health.

This paper provides estimates of the effects of in utero exposure to contaminated drinking water on fetal health. To do this, we examine the universe of birth records and drinking water testing results for the state of New Jersey from 1997 to 2007. Our data enable us to compare outcomes across siblings who were potentially exposed to differing levels of harmful contaminants from drinking water while in utero. We find small effects of drinking water contamination on all children, but large and statistically significant effects on birth weight and gestation of infants born to less educated mothers. We also show that those mothers who were most affected by contamination were the least likely to move between births in response to contamination.

Climate trends and global crop production since 1980.

Efforts to anticipate how climate change will affect future food availability can benefit from understanding the impacts of changes to date. We found that in the cropping regions and growing seasons of most countries, with the important exception of the United States, temperature trends from 1980 to 2008 exceeded one standard deviation of historic year-to-year variability. Models that link yields of the four largest commodity crops to weather indicate that global maize and wheat production declined by 3.8 and 5.5%, respectively, relative to a counterfactual without climate trends. For soybeans and rice, winners and losers largely balanced out. Climate trends were large enough in some countries to offset a significant portion of the increases in average yields that arose from technology, carbon dioxide fertilization, and other factors.

Nonlinear temperature effects indicate severe damages to U.S. crop yields under climate change.

The United States produces 41% of the world's corn and 38% of the world's soybeans. These crops comprise two of the four largest sources of caloric energy produced and are thus critical for world food supply. We pair a panel of county-level yields for these two crops, plus cotton (a warmer-weather crop), with a new fine-scale weather dataset that incorporates the whole distribution of temperatures within each day and across all days in the growing season. We find that yields increase with temperature up to 29 degrees C for corn, 30 degrees C for soybeans, and 32 degrees C for cotton but that temperatures above these thresholds are very harmful. The slope of the decline above the optimum is significantly steeper than the incline below it. The same nonlinear and asymmetric relationship is found when we isolate either time-series or cross-sectional variations in temperatures and yields. This suggests limited historical adaptation of seed varieties or management practices to warmer temperatures because the cross-section includes farmers' adaptations to warmer climates and the time-series does not. Holding current growing regions fixed, area-weighted average yields are predicted to decrease by 30-46% before the end of the century under the slowest (B1) warming scenario and decrease by 63-82% under the most rapid warming scenario (A1FI) under the Hadley III model.