Risks of synchronized low yields are underestimated in climate and crop model projections.

Simultaneous harvest failures across major crop-producing regions are a threat to global food security. Concurrent weather extremes driven by a strongly meandering jet stream could trigger such events, but so far this has not been quantified. Specifically, the ability of state-of-the art crop and climate models to adequately reproduce such high impact events is a crucial component for estimating risks to global food security. Here we find an increased likelihood of concurrent low yields during summers featuring meandering jets in observations and models. While climate models accurately simulate atmospheric patterns, associated surface weather anomalies and negative effects on crop responses are mostly underestimated in bias-adjusted simulations. Given the identified model biases, future assessments of regional and concurrent crop losses from meandering jet states remain highly uncertain. Our results suggest that model-blind spots for such high-impact but deeply-uncertain hazards have to be anticipated and accounted for in meaningful climate risk assessments.

Contrasting impacts of dry versus humid heat on US corn and soybean yields.

The impact of extreme heat on crop yields is an increasingly pressing issue given anthropogenic climate warming. However, some of the physical mechanisms involved in these impacts remain unclear, impeding adaptation-relevant insight and reliable projections of future climate impacts on crops. Here, using a multiple regression model based on observational data, we show that while extreme dry heat steeply reduced U.S. corn and soy yields, humid heat extremes had insignificant impacts and even boosted yields in some areas, despite having comparably high dry-bulb temperatures as their dry heat counterparts. This result suggests that conflating dry and humid heat extremes may lead to underestimated crop yield sensitivities to extreme dry heat. Rainfall tends to precede humid but not dry heat extremes, suggesting that multivariate weather sequences play a role in these crop responses. Our results provide evidence that extreme heat in recent years primarily affected yields by inducing moisture stress, and that the conflation of humid and dry heat extremes may lead to inaccuracy in projecting crop yield responses to warming and changing humidity.

Mitigation and adaptation emissions embedded in the broader climate transition.

Climate change necessitates a global effort to reduce greenhouse gas emissions while adapting to increased climate risks. This broader climate transition will involve large-scale global interventions including renewable energy deployment, coastal protection and retreat, and enhanced space cooling, all of which will result in CO2 emissions from energy and materials use. Yet, the magnitude of the emissions embedded in these interventions remains unconstrained, opening the potential for underaccounting of emissions and conflicts or synergies between mitigation and adaptation goals. Here, we use a suite of models to estimate the CO2 emissions embedded in the broader climate transition. For a gradual decarbonization pathway limiting warming to 2 °C, selected adaptation-related interventions will emit ∼1.3 GtCO2 through 2100, while emissions from energy used to deploy renewable capacity are much larger at ∼95 GtCO2. Together, these emissions are equivalent to over 2 y of current global emissions and 8.3% of the remaining carbon budget for 2 °C. Total embedded transition emissions are reduced by ∼80% to 21.2 GtCO2 under a rapid pathway limiting warming to 1.5 °C. However, they roughly double to 185 GtCO2 under a delayed pathway consistent with current policies (2.7 °C warming by 2100), mainly because a slower transition relies more on fossil fuel energy. Our results provide a holistic assessment of carbon emissions from the transition itself and suggest that these emissions can be minimized through more ambitious energy decarbonization. We argue that the emissions from mitigation, but likely much less so from adaptation, are of sufficient magnitude to merit greater consideration in climate science and policy.

Arctic sea-ice loss is projected to lead to more frequent strong El Niño events.

Arctic sea ice has decreased substantially and is projected to reach a seasonally ice-free state in the coming decades. Little is known about whether dwindling Arctic sea ice is capable of influencing the occurrence of strong El Niño, a prominent mode of climate variability with global impacts. Based on time slice coupled model experiments, here we show that no significant change in the occurrence of strong El Niño is found in response to moderate Arctic sea-ice loss that is consistent with satellite observations to date. However, as the ice loss continues and the Arctic becomes seasonally ice-free, the frequency of strong El Niño events increases by more than one third, as defined by gradient-based indices that remove mean tropical Pacific warming induced by the seasonally ice-free Arctic. By comparing our time slice experiments with greenhouse warming experiments, we conclude that at least 37-48% of the increase of strong El Niño near the end of the 21st century is associated specifically with Arctic sea-ice loss. Further separation of Arctic sea-ice loss and greenhouse gas forcing only experiments implies that the seasonally ice-free Arctic might play a key role in driving significantly more frequent strong El Niño events.

Stronger temperature-moisture couplings exacerbate the impact of climate warming on global crop yields.

Rising air temperatures are a leading risk to global crop production. Recent research has emphasized the critical role of moisture availability in regulating crop responses to heat and the importance of temperature-moisture couplings in driving concurrent heat and drought. Here, we demonstrate that the heat sensitivity of key global crops depends on the local strength of couplings between temperature and moisture in the climate system. Over 1970-2013, maize and soy yields dropped more during hotter growing seasons in places where decreased precipitation and evapotranspiration more strongly accompanied higher temperatures, suggestive of compound heat-drought impacts on crops. On the basis of this historical pattern and a suite of climate model projections, we show that changes in temperature-moisture couplings in response to warming could enhance the heat sensitivity of these crops as temperatures rise, worsening the impact of warming by -5% (-17 to 11% across climate models) on global average. However, these changes will benefit crops where couplings weaken, including much of Asia, and projected impacts are highly uncertain in some regions. Our results demonstrate that climate change will impact crops not only through warming but also through changing drivers of compound heat-moisture stresses, which may alter the sensitivity of crop yields to heat as warming proceeds. Robust adaptation of cropping systems will need to consider this underappreciated risk to food production from climate change.

Adaptation in U.S. Corn Belt increases resistance to soil carbon loss with climate change.

Increasing the amount of soil organic carbon (SOC) has agronomic benefits and the potential to mitigate climate change. Previous regional predictions of SOC trends under climate change often ignore or do not explicitly consider the effect of crop adaptation (i.e., changing planting dates and varieties). We used the DayCent biogeochemical model to examine the effect of adaptation on SOC for corn and soybean production in the U.S. Corn Belt using climate data from three models. Without adaptation, yields of both corn and soybean tended to decrease and the decomposition of SOC tended to increase leading to a loss of SOC with climate change compared to a baseline scenario with no climate change. With adaptation, the model predicted a substantially higher crop yield. The increase in yields and associated carbon input to the SOC pool counteracted the increased decomposition in the adaptation scenarios, leading to similar SOC stocks under different climate change scenarios. Consequently, we found that crop management adaptation to changing climatic conditions strengthen agroecosystem resistance to SOC loss. However, there are differences spatially in SOC trends. The northern part of the region is likely to gain SOC while the southern part of the region is predicted to lose SOC.

Modeling Coastal Flood Risk and Adaptation Response under Future Climate Conditions.

The National Coastal Property Model (NCPM) simulates flood damages resulting from sea level rise and storm surge along the contiguous U.S. coastline. The model also projects local-level investments in a set of adaptation measures under the assumption that these measures will be adopted when benefits exceed the costs over a 30-year period. However, it has been observed that individuals and communities often underinvest in adaptive measures relative to standard cost-benefit assumptions due to financial, psychological, sociopolitical, and technological factors. This study applies an updated version of the NCPM to incorporate improved cost-benefit tests and to approximate observed sub-optimal flood risk reduction behavior. The updated NCPM is tested for two multi-county sites: Virginia Beach, VA and Tampa, FL. Sub-optimal adaptation approaches slow the implementation of adaptation measures throughout the 100-year simulation and they increase the amount of flood damages, especially early in the simulation. The net effect is an increase in total present value cost of $1.1 to $1.3 billion (2015 USD), representing about a 10% increase compared to optimal adaptation approaches. Future calibrations against historical data and incorporation of non-economic factors driving adaptation decisions could prove useful in better understanding the impacts of continued sub-optimal behavior.

The emergence of heat and humidity too severe for human tolerance.

Humans' ability to efficiently shed heat has enabled us to range over every continent, but a wet-bulb temperature (TW) of 35°C marks our upper physiological limit, and much lower values have serious health and productivity impacts. Climate models project the first 35°C TW occurrences by the mid-21st century. However, a comprehensive evaluation of weather station data shows that some coastal subtropical locations have already reported a TW of 35°C and that extreme humid heat overall has more than doubled in frequency since 1979. Recent exceedances of 35°C in global maximum sea surface temperature provide further support for the validity of these dangerously high TW values. We find the most extreme humid heat is highly localized in both space and time and is correspondingly substantially underestimated in reanalysis products. Our findings thus underscore the serious challenge posed by humid heat that is more intense than previously reported and increasingly severe.

Projections of Temperature-related Non-accidental Mortality in Nanjing, China.

The health effects of climatic changes constitute an important research area, yet few researchers have reported city- or region-specific projections of temperature-related deaths based on assumptions about mitigation and adaptation. Herein, we provide quantitative projections for the number of additional deaths expected in the future, owing to the cold and heat in the city of Nanjing, China, based on 31 global circulation models (GCMs), two representative concentration pathways (RCPs) (RCP4.5 and RCP8.5), and three population scenarios [a constant scenario and two shared socioeconomic pathways (SSPs) (SSP2 and SSP5)], for the periods of 2010-2039, 2040-2069, and 2070-2099. The results show that for the period 2070-2099, the net number of temperature-related deaths can be comparable in the cases of RCP4.5/SSP2 and RCP8.5/SSP5 owing to the offsetting effects attributed to the increase of heat related deaths and the decrease of cold-related deaths. In consideration of this adaptation, we suggest that RCP4.5/SSP2 is a better future development pathway/scenario.

Rising Sea Levels: Helping Decision-Makers Confront the Inevitable.

Sea-level rise (SLR) is not just a future trend; it is occurring now in most coastal regions across the globe. It thus impacts not only long-range planning in coastal environments, but also emergency preparedness. Its inevitability and irreversibility on long time scales, in addition to its spatial non-uniformity, uncertain magnitude and timing, and capacity to drive non-stationarity in coastal flooding on planning and engineering timescales, create unique challenges for coastal risk-management decision processes. This review assesses past United States federal efforts to synthesize evolving SLR science in support of coastal risk management. In particular, it outlines the: (1) evolution in global SLR scenarios to those using a risk-based perspective that also considers low-probability but high-consequence outcomes, (2) regionalization of the global scenarios, and (3) use of probabilistic approaches. It also describes efforts to further contextualize regional scenarios by combining local mean sea-level changes with extreme water level projections. Finally, it offers perspectives on key issues relevant to the future uptake, interpretation, and application of sea-level change scenarios in decision-making. These perspectives have utility for efforts to craft standards and guidance for preparedness and resilience measures to reduce the risk of coastal flooding and other impacts related to SLR.

Towards reliable Arctic sea ice prediction using multivariate data assimilation.

Rapid declines in Arctic sea ice have captured attention and pose significant challenges to a variety of stakeholders. There is a rising demand for Arctic sea ice prediction at daily to seasonal time scales, which is partly a sea ice initial condition problem. Thus, a multivariate data assimilation that integrates sea ice observations to generate realistic and skillful model initialization is needed to improve predictive skill of Arctic sea ice. Sea ice data assimilation is a relatively new research area. In this review paper, we focus on two challenges for implementing multivariate data assimilation systems for sea ice forecast. First, to address the challenge of limited spatiotemporal coverage and large uncertainties of observations, we discuss sea ice parameters derived from satellite remote sensing that (1) have been utilized for improved model initialization, including concentration, thickness and drift, and (2) are currently under development with the potential for enhancing the predictability of Arctic sea ice, including melt ponds and sea ice leads. Second, to strive to generate the "best" estimate of sea ice initial conditions by combining model simulations/forecasts and observations, we review capabilities and limitations of different data assimilation techniques that have been developed and used to assimilate observed sea ice parameters in dynamical models.

Temperature and humidity based projections of a rapid rise in global heat stress exposure during the 21st century.

As a result of global increases in both temperature and specific humidity, heat stress is projected to intensify throughout the 21st century. Some of the regions most susceptible to dangerous heat and humidity combinations are also among the most densely populated. Consequently, there is the potential for widespread exposure to wet bulb temperatures that approach and in some cases exceed postulated theoretical limits of human tolerance by mid- to late-century. We project that by 2080 the relative frequency of present-day extreme wet bulb temperature events could rise by a factor of 100 - 250 (approximately double the frequency change projected for temperature alone) in the tropics and parts of the mid-latitudes, areas which are projected to contain approximately half the world's population. In addition, population exposure to wet bulb temperatures that exceed recent deadly heat waves may increase by a factor of five to ten, with 150 - 750 million person-days of exposure to wet bulb temperatures above those seen in today's most severe heat waves by 2070 - 2080. Under RCP 8.5, exposure to wet bulb temperatures above 35°C - the theoretical limit for human tolerance - could exceed a million person-days per year by 2080. Limiting emissions to follow RCP 4.5 entirely eliminates exposure to that extreme threshold. Some of the most affected regions, especially Northeast India and coastal West Africa, currently have scarce cooling infrastructure, relatively low adaptive capacity, and rapidly growing populations. In the coming decades heat stress may prove to be one of the most widely experienced and directly dangerous aspects of climate change, posing a severe threat to human health, energy infrastructure, and outdoor activities ranging from agricultural production to military training.

Long-term projections of temperature-related mortality risks for ischemic stroke, hemorrhagic stroke, and acute ischemic heart disease under changing climate in Beijing, China.

BACKGROUND: Changing climates have been causing variations in the number of global ischemic heart disease and stroke incidences, and will continue to affect disease occurrence in the future. OBJECTIVES: To project temperature-related mortality for acute ischemic heart disease, and ischemic and hemorrhagic stroke with concomitant climate warming. METHODS: We estimated the exposure-response relationship between daily cause-specific mortality and daily mean temperature in Beijing. We utilized outputs from 31 downscaled climate models and two representative concentration pathways (RCPs) for the 2020s, 2050s, and 2080s. This strategy was used to estimate future net temperature along with heat- and cold-related deaths. The results for predicted temperature-related deaths were subsequently contrasted with the baseline period. RESULTS: In the 2080s, using the RCP8.5 and no population variation scenarios, the net total number of annual temperature-related deaths exhibited a median value of 637 (with a range across models of 434-874) for ischemic stroke; this is an increase of approximately 100% compared with the 1980s. The median number of projected annual temperature-related deaths was 660 (with a range across models of 580-745) for hemorrhagic stroke (virtually no change compared with the 1980s), and 1683 (with a range across models of 1351-2002) for acute ischemic heart disease (a slight increase of approximately 20% compared with the 1980s). In the 2080s, the monthly death projection for hemorrhagic stroke and acute ischemic heart disease showed that the largest absolute changes occurred in summer and winter while the largest absolute changes for ischemic stroke occurred in summer. CONCLUSIONS: We projected that the temperature-related mortality associated with ischemic stroke will increase dramatically due to climate warming. However, projected temperature-related mortality pertaining to acute ischemic heart disease and hemorrhagic stroke should remain relatively stable over time.

Assessing ecosystem service provision under climate change to support conservation and development planning in Myanmar.

Inclusion of ecosystem services (ES) information into national-scale development and climate adaptation planning has yet to become common practice, despite demand from decision makers. Identifying where ES originate and to whom the benefits flow-under current and future climate conditions-is especially critical in rapidly developing countries, where the risk of ES loss is high. Here, using Myanmar as a case study, we assess where and how ecosystems provide key benefits to the country's people and infrastructure. We model the supply of and demand for sediment retention, dry-season baseflows, flood risk reduction and coastal storm protection from multiple beneficiaries. We find that locations currently providing the greatest amount of services are likely to remain important under the range of climate conditions considered, demonstrating their importance in planning for climate resilience. Overlap between priority areas for ES provision and biodiversity conservation is higher than expected by chance overall, but the areas important for multiple ES are underrepresented in currently designated protected areas and Key Biodiversity Areas. Our results are contributing to development planning in Myanmar, and our approach could be extended to other contexts where there is demand for national-scale natural capital information to shape development plans and policies.

Impact of climate change on heat-related mortality in Jiangsu Province, China.

A warming climate is anticipated to increase the future heat-related total mortality in urban areas. However, little evidence has been reported for cause-specific mortality or nonurban areas. Here we assessed the impact of climate change on heat-related total and cause-specific mortality in both urban and rural counties of Jiangsu Province, China, in the next five decades. To address the potential uncertainty in projecting future heat-related mortality, we applied localized urban- and nonurban-specific exposure response functions, six population projections including a no population change scenario and five Shared Socioeconomic Pathways (SSPs), and 42 temperature projections from 21 global-scale general circulation models and two Representative Concentration Pathways (RCPs). Results showed that projected warmer temperatures in 2016-2040 and 2041-2065 will lead to higher heat-related mortality for total non-accidental, cardiovascular, respiratory, stroke, ischemic heart disease (IHD), and chronic obstructive pulmonary disease (COPD) causes occurring annually during May to September in Jiangsu Province, China. Nonurban residents in Jiangsu will suffer from more excess heat-related cause-specific mortality in 2016-2065 than urban residents. Variations across climate models and RCPs dominated the uncertainty of heat-related mortality estimation whereas population size change only had limited influence. Our findings suggest that targeted climate change mitigation and adaptation measures should be taken in both urban and nonurban areas of Jiangsu Province. Specific public health interventions should be focused on the leading causes of death (stroke, IHD, and COPD), whose health burden will be amplified by a warming climate.

Towards More Comprehensive Projections of Urban Heat-Related Mortality: Estimates for New York City under Multiple Population, Adaptation, and Climate Scenarios.

BACKGROUND: High temperatures have substantial impacts on mortality and, with growing concerns about climate change, numerous studies have developed projections of future heat-related deaths around the world. Projections of temperature-related mortality are often limited by insufficient information to formulate hypotheses about population sensitivity to high temperatures and future demographics. OBJECTIVES: The present study derived projections of temperature-related mortality in New York City by taking into account future patterns of adaptation or demographic change, both of which can have profound influences on future health burdens. METHODS: We adopted a novel approach to modeling heat adaptation by incorporating an analysis of the observed population response to heat in New York City over the course of eight decades. This approach projected heat-related mortality until the end of the 21st century based on observed trends in adaptation over a substantial portion of the 20th century. In addition, we incorporated a range of new scenarios for population change until the end of the 21st century. We then estimated future heat-related deaths in New York City by combining the changing temperature-mortality relationship and population scenarios with downscaled temperature projections from the 33 global climate models (GCMs) and two Representative Concentration Pathways (RCPs). RESULTS: The median number of projected annual heat-related deaths across the 33 GCMs varied greatly by RCP and adaptation and population change scenario, ranging from 167 to 3,331 in the 2080s compared with 638 heat-related deaths annually between 2000 and 2006. CONCLUSIONS: These findings provide a more complete picture of the range of potential future heat-related mortality risks across the 21st century in New York City, and they highlight the importance of both demographic change and adaptation responses in modifying future risks. Citation: Petkova EP, Vink JK, Horton RM, Gasparrini A, Bader DA, Francis JD, Kinney PL. 2017. Towards more comprehensive projections of urban heat-related mortality: estimates for New York City under multiple population, adaptation, and climate scenarios. Environ Health Perspect 125:47-55; http://dx.doi.org/10.1289/EHP166.

TOTAL AND EXTREME PRECIPITATION CHANGES OVER THE NORTHEASTERN UNITED STATES.

The Northeastern United States has experienced a large increase in precipitation over recent decades. Annual and seasonal changes of total and extreme precipitation from station observations in the Northeast are assessed over multiple time periods spanning 1901-2014. Spatially averaged, both annual total and extreme precipitation across the Northeast have increased significantly since 1901, with changepoints occurring in 2002 and 1996, respectively. Annual extreme precipitation has experienced a larger increase than total precipitation; extreme precipitation from 1996-2014 was 53% higher than from 1901-1995. Spatially, coastal areas received more total and extreme precipitation on average, but increases across the changepoints are distributed fairly uniformly across the domain. Increases in annual total precipitation across the 2002 changepoint have been driven by significant total precipitation increases in fall and summer, while increases in annual extreme precipitation across the 1996 changepoint have been driven by significant extreme precipitation increases in fall and spring. The ability of gridded observed and reanalysis precipitation data to reproduce station observations was also evaluated. Gridded observations perform well in reproducing averages and trends of annual and seasonal total precipitation, but extreme precipitation trends show significantly different spatial and domain-averaged trends than station data. North American Regional Reanalysis generally underestimates annual and seasonal total and extreme precipitation means and trends relative to station observations, and also shows substantial differences in the spatial pattern of total and extreme precipitation trends within the Northeast.