Higher Temperatures in Socially Vulnerable US Communities Increasingly Limit Safe Use of Electric Fans for Cooling

As the globe warms, people will increasingly need affordable, safe methods to stay cool and minimize the worst health impacts of heat exposure. One of the cheapest cooling methods is electric fans. Recent research has recommended ambient air temperature thresholds for safe fan use in adults. Here we use hourly weather reanalysis data (1950-2021) to examine the temporal and spatial evolution of ambient climate conditions in the continental United States (CONUS) considered safe for fan use, focusing on high social vulnerability index (SVI) regions. We find that although most hours in the day are safe for fan use, there are regions that experience hundreds to thousands of hours per year that are too hot for safe fan use. Over the last several decades, the number of hours considered unsafe for fan use has increased across most of the CONUS (on average by ∼70%), with hotspots across the US West and South, suggesting that many individuals will increasingly need alternative cooling strategies. People living in high-SVI locations are 1.5-2 times more likely to experience hotter climate conditions than the overall US population. High-SVI locations also experience higher rates of warming that are approaching and exceeding important safety thresholds that relate to climate adaptation. These results highlight the need to direct additional resources to these communities for heat adaptive strategies.

Environmental Health, Racial/Ethnic Health Disparity, and Climate Impacts of Inter-Regional Freight Transport in the United States

We quantify and compare three environmental impacts from inter-regional freight transportation in the contiguous United States: total mortality attributable to PM2.5 air pollution, racial-ethnic disparities in PM2.5-attributable mortality, and CO2 emissions. We compare all major freight modes (truck, rail, barge, aircraft) and routes (∼30,000 routes). Our study is the first to comprehensively compare each route separately and the first to explore racial-ethnic exposure disparities by route and mode, nationally. Impacts (health, health disparity, climate) per tonne of freight are the largest for aircraft. Among nonaircraft modes, per tonne, rail has the largest health and health-disparity impacts and the lowest climate impacts, whereas truck transport has the lowest health impacts and greatest climate impacts─an important reminder that health and climate impacts are often but not always aligned. For aircraft and truck, average monetized damages per tonne are larger for climate impacts than those for PM2.5 air pollution; for rail and barge, the reverse holds. We find that average exposures from inter-regional truck and rail are the highest for White non-Hispanic people, those from barge are the highest for Black people, and those from aircraft are the highest for people who are mixed/other race. Level of exposure and disparity among racial-ethnic groups vary in urban versus rural areas.

The importance of internal climate variability in climate impact projections

Uncertainty in climate projections is driven by three components: scenario uncertainty, intermodel uncertainty, and internal variability. Although socioeconomic climate impact studies increasingly take into account the first two components, little attention has been paid to the role of internal variability, although underestimating this uncertainty may lead to underestimating the socioeconomic costs of climate change. Using large ensembles from seven coupled general circulation models with a total of 414 model runs, we partition the climate uncertainty in classic dose-response models relating county-level corn yield, mortality, and per-capita gross domestic product to temperature in the continental United States. The partitioning of uncertainty depends on the time frame of projection, the impact model, and the geographic region. Internal variability represents more than 50% of the total climate uncertainty in certain projections, including mortality projections for the early 21st century, although its relative influence decreases over time. We recommend including uncertainty due to internal variability for many projections of temperature-driven impacts, including early-century and midcentury projections, projections in regions with high internal variability such as the Upper Midwest United States, and impacts driven by nonlinear relationships.

Warming increased bark beetle-induced tree mortality by 30% during an extreme drought in California

Quantifying the responses of forest disturbances to climate warming is critical to our understanding of carbon cycles and energy balances of the Earth system. The impact of warming on bark beetle outbreaks is complex as multiple drivers of these events may respond differently to warming. Using a novel model of bark beetle biology and host tree interactions, we assessed how contemporary warming affected western pine beetle (Dendroctonus brevicomis) populations and mortality of its host, ponderosa pine (Pinus ponderosa), during an extreme drought in the Sierra Nevada, California, United States. When compared with the field data, our model captured the western pine beetle flight timing and rates of ponderosa pine mortality observed during the drought. In assessing the influence of temperature on western pine beetles, we found that contemporary warming increased the development rate of the western pine beetle and decreased the overwinter mortality rate of western pine beetle larvae leading to increased population growth during periods of lowered tree defense. We attribute a 29.9% (95% CI: 29.4%-30.2%) increase in ponderosa pine mortality during drought directly to increases in western pine beetle voltinism (i.e., associated with increased development rates of western pine beetle) and, to a much lesser extent, reductions in overwintering mortality. These findings, along with other studies, suggest each degree (°C) increase in temperature may have increased the number of ponderosa pine killed by upwards of 35%-40% °C^-1 if the effects of compromised tree defenses (15%-20%) and increased western pine beetle populations (20%) are additive. Due to the warming ability to considerably increase mortality through the mechanism of bark beetle populations, models need to consider climate's influence on both host tree stress and the bark beetle population dynamics when determining future levels of tree mortality.

Consumer strategies towards a more sustainable food system: insights from Switzerland

BACKGROUND

To improve the sustainability performance of food systems, both consumption- and production-side changes are needed.

OBJECTIVES

To this end, we assessed multiple sustainability impacts of 6 consumer strategies together with production-side aspects such as organic and circularity principles for Switzerland.

METHODS

Two strategies encompassed dietary changes: following a pescetarian diet and adhering to the national dietary guidelines. Two strategies employed alternative farming systems: increasing the share of organic production and, in addition, applying the circularity principle of avoiding feed-food competition by limiting livestock feed to low-opportunity-cost biomass. A fifth strategy reduced food waste. The sixth strategy increased the share of domestic produce. For all strategies, we assessed greenhouse gas emissions, land use, nitrogen surplus, social risks, diet quality, and diet costs.

RESULTS

The strategies revealed trade-offs between impact categories, unless combined in a synergistic way. Whereas dietary changes towards more plant-based diets reduced environmental impacts (≤51%) and increased diet quality (≤57%), they increased social risks due to increased sourcing from contexts with potentially bad labor conditions (≤19%). Further, when the share of organic produce was increased, land use and dietary costs were increased (≤33% and ≤42%, respectively). The effect on land use could, however, be reversed when circularity principles were introduced in addition to the organic production standard, resulting in reductions for all environmental indicators (≤75%). Reducing food waste and increasing the share of domestic produce led to better sustainability performance as well, but at lower orders of magnitude.

CONCLUSIONS

Combining all proposed strategies could lead to substantial favorable changes on all impact categories assessed, but would require a thorough transformation of the current food system. However, the sum of individual consumers each following only 1 of the strategies proposed would make an important contribution towards improving the sustainability performance of the Swiss food system.

Climate-Induced Tradeoffs in Planning and Operating Costs of a Regional Electricity System

Electricity grid planners design the system to supply electricity to end-users reliably and affordably. Climate change threatens both objectives through potentially compounding supply- and demand-side climate-induced impacts. Uncertainty surrounds each of these future potential impacts. Given long planning horizons, system planners must weigh investment costs against operational costs under this uncertainty. Here, we developed a comprehensive and coherent integrated modeling framework combining physically based models with cost-minimizing optimization models in the power system. We applied this modeling framework to analyze potential tradeoffs in planning and operating costs in the power grid due to climate change in the Southeast U.S. in 2050. We find that planning decisions that do not account for climate-induced impacts would result in a substantial increase in social costs associated with loss of load. These social costs are a result of under-investment in new capacity and capacity deratings of thermal generators when we included climate change impacts in the operation stage. These results highlight the importance of including climate change effects in the planning process.

The Potential of Deep Roots to Mitigate Impacts of Heatwaves and Declining Rainfall on Pastures in Southeast Australia

Declines in growing-season rainfall and increases in the frequency of heatwaves in southern Australia necessitate effective adaptation. The Sustainable Grazing Systems Pasture Model (SGS) was used to model the growth of three pasture species differing in root depth and root distribution under three different climate scenarios at two sites. The modelled metabolisable energy intake (in MJ) was used in a partial discounted net cash flow budget. Both the biophysical and economic modelling suggest that deep roots were advantageous in all climate scenarios at the long growing season site but provided no to little advantage at the short growing season site, likely due to the deep-rooted species drying out the soil profile earlier. In scenarios including climate change, the DM production of the deep-rooted species at the long growing season site averaged 386 kg/ha/year more than the more shallow-rooted species, while at the site with a shorter growing season it averaged 205 kg/ha/year less than the shallower-rooted species. The timing of the extra growth and pasture persistence strongly influenced the extent of the benefit. At the short growing season site other adaptation options such as summer dormancy will likely be necessary.

Large-scale interventions may delay decline of the Great Barrier Reef

On the iconic Great Barrier Reef (GBR), the cumulative impacts of tropical cyclones, marine heatwaves and regular outbreaks of coral-eating crown-of-thorns starfish (CoTS) have severely depleted coral cover. Climate change will further exacerbate this situation over the coming decades unless effective interventions are implemented. Evaluating the efficacy of alternative interventions in a complex system experiencing major cumulative impacts can only be achieved through a systems modelling approach. We have evaluated combinations of interventions using a coral reef meta-community model. The model consisted of a dynamic network of 3753 reefs supporting communities of corals and CoTS connected through ocean larval dispersal, and exposed to changing regimes of tropical cyclones, flood plumes, marine heatwaves and ocean acidification. Interventions included reducing flood plume impacts, expanding control of CoTS populations, stabilizing coral rubble, managing solar radiation and introducing heat-tolerant coral strains. Without intervention, all climate scenarios resulted in precipitous declines in GBR coral cover over the next 50 years. The most effective strategies in delaying decline were combinations that protected coral from both predation (CoTS control) and thermal stress (solar radiation management) deployed at large scale. Successful implementation could expand opportunities for climate action, natural adaptation and socioeconomic adjustment by at least one to two decades.

Climate change causes critical transitions and irreversible alterations of mountain forests

Mountain forests are at particular risk of climate change impacts due to their temperature limitation and high exposure to warming. At the same time, their complex topography may help to buffer the effects of climate change and create climate refugia. Whether climate change can lead to critical transitions of mountain forest ecosystems and whether such transitions are reversible remain incompletely understood. We investigated the resilience of forest composition and size structure to climate change, focusing on a mountain forest landscape in the Eastern Alps. Using the individual-based forest landscape model iLand, we simulated ecosystem responses to a wide range of climatic changes (up to a 6°C increase in mean annual temperature and a 30% reduction in mean annual precipitation), testing for tipping points in vegetation size structure and composition under different topography scenarios. We found that at warming levels above +2°C a threshold was crossed, with the system tipping into an alternative state. The system shifted from a conifer-dominated landscape characterized by large trees to a landscape dominated by smaller, predominantly broadleaved trees. Topographic complexity moderated climate change impacts, smoothing and delaying the transitions between alternative vegetation states. We subsequently reversed the simulated climate forcing to assess the ability of the landscape to recover from climate change impacts. The forest landscape showed hysteresis, particularly in scenarios with lower precipitation. At the same mean annual temperature, equilibrium vegetation size structure and species composition differed between warming and cooling trajectories. Here we show that even moderate warming corresponding to current policy targets could result in critical transitions of forest ecosystems and highlight the importance of topographic complexity as a buffering agent. Furthermore, our results show that overshooting ambitious climate mitigation targets could be dangerous, as ecological impacts can be irreversible at millennial time scales once a tipping point has been crossed.

Fossil Fuel Combustion Is Driving Indoor CO2 Toward Levels Harmful to Human Cognition

Human activities are elevating atmospheric carbon dioxide concentrations to levels unprecedented in human history. The majority of anticipated impacts of anthropogenic CO2 emissions are mediated by climate warming. Recent experimental studies in the fields of indoor air quality and cognitive psychology and neuroscience, however, have revealed significant direct effects of indoor CO2 levels on cognitive function. Here, we shed light on this connection and estimate the impact of continued fossil fuel emissions on human cognition. We conclude that indoor CO2 levels may indeed reach levels harmful to cognition by the end of this century, and the best way to prevent this hidden consequence of climate change is to reduce fossil fuel emissions. Finally, we offer recommendations for a broad, interdisciplinary approach to improving such understanding and prediction.

Natural Disasters Are Prejudiced Against Disadvantaged and Vulnerable Populations: The Lack of Publicly Available Health-Related Data Hinders Research at the Cusp of the Global Climate Crisis

Natural disasters often affect the most vulnerable countries/communities around the world. However, within the same countries/communities, the impact of natural disasters is far greater on disadvantaged populations. We investigate how wildfires affect asthma prevalence in different populations across California. Our results indicate that although there is no discernible relationship between wildfires and asthma prevalence for California's population as a whole, wildfires and asthma prevalence in Black and senior populations have a strong relationship. We believe there is an urgent need to make high-resolution health-related data publicly available for in-depth analyses of climate change impacts on society and disadvantage communities.

Climate variability reduces employment in New England fisheries

Beyond their value as a natural resource, marine fisheries employ an estimated 18.4 million commercial harvesters worldwide. Previous research describes how climate change can affect fish populations, but how it will impact fishing employment and communities is not yet understood. New England, which employs 34,000 commercial harvesters, has a well-documented management history and some of the world’s fastest-warming waters. This paper provides empirical evidence that fluctuations in a regional climate index reduced county-level fishing employment in New England by an average of 16% between 1996 and 2017. The findings cannot be extrapolated to other regions without further study, but they demonstrate how climate can be linked to fishing employment at a regional level via a biophysical pathway.

Climate change is already affecting fish productivity and distributions worldwide, yet its impact on fishing labor has not been examined. Here I directly link large-scale climate variability with fishery employment by studying the effects of sea-surface pressure changes in the North Atlantic region, whose waters are among the world’s fastest warming. I find that climate shocks reduce not only regional catch and revenue in the New England fishing sector, but also ultimately county-level wages and employment among commercial harvesters. Each SD increase from the climatic mean decreases county-level fishing employment by 13%, on average. The South Atlantic region serves as a control due to its different ecological response to climate. Overall, I estimate that climate variability from 1996 to 2017 is responsible for a 16% (95% CI: 10% to 22%) decline in county-level fishing employment in New England, beyond the changes in employment attributable to management or other factors. This quantitative evidence linking climate variability and fishing labor has important implications for management in New England, which employs 20% of US commercial harvesters. Because the results are mediated by the local biology and institutions, they cannot be directly extrapolated to other regions. But they show that climate can impact fishing outcomes in ways unaccounted by management and offer a template for study of this relationship in fisheries around the world.

Direct and indirect effects of regional and local climatic factors on trophic interactions in the Arctic tundra

Climate change can impact ecosystems by reshaping the dynamics of resource exploitation for predators and their prey. Alterations of these pathways could be especially intense in ecosystems characterized by a simple trophic structure and rapid warming trends, such as in the Arctic. However, quantifying the multiple direct and indirect pathways through which climate change is likely to alter trophic interactions and their relative strength remains a challenge. Here, we aim to identify direct and indirect causal mechanisms driven by climate affecting predator-prey interactions of species sharing a tundra food web. We based our study on relationships between one Arctic predator (Arctic fox) and its two main prey - lemmings (preferred prey) and snow geese (alternate prey) - which are exposed to variable local and regional climatic factors across years. We used a combination of models mapping multiple causal links among key variables derived from a long-term dataset (21 years). We obtained several possible scenarios linking regional climate factors (Arctic oscillations) and local temperature and precipitation to the breeding of species. Our results suggest that both regional and local climate factors have direct and indirect impacts on the breeding of foxes and geese. Local climate showed a positive causal link with goose nesting success, while both regional and local climate displayed contrasted effects on the proportion of fox breeding. We found no impact of climate on lemming abundance. We observed positive relationships between lemming, fox and goose reproduction highlighting numerical and functional responses of fox to the variability of lemming abundance. Our study measures causal links and strength of interactions in a food web, quantifying both numerical response of a predator and apparent interactions between its two main prey. These results improve our understanding of the complex effects of climate on predator-prey interactions and our capacity to anticipate food web response to ongoing climate change.

Challenges to natural and human communities from surprising ocean temperatures

Based on historical and lived experience, people expect certain conditions to prevail in the ecosystems they depend upon. Climate change is now introducing strong trends that push conditions beyond historic levels. Using ocean ecosystems as a case study, we show that the frequency of surprising temperatures is increasing faster than expected. We then use these events as motivation to develop a theory for how temperature trends and events will impact natural and human communities. The theory suggests that strong trends will decrease the abundance and productivity of natural communities. Increasing trends will also challenge how people make decisions, and our theory identifies the conditions under which there is a significant payoff for people to bet on the trend.

The community of species, human institutions, and human activities at a given location have been shaped by historical conditions (both mean and variability) at that location. Anthropogenic climate change is now adding strong trends on top of existing natural variability. These trends elevate the frequency of “surprises”—conditions that are unexpected based on recent history. Here, we show that the frequency of surprising ocean temperatures has increased even faster than expected based on recent temperature trends. Using a simple model of human adaptation, we show that these surprises will increasingly challenge natural modes of adaptation that rely on historical experience. We also show that warming rates are likely to shift natural communities toward generalist species, reducing their productivity and diversity. Our work demonstrates increasing benefits for individuals and institutions from betting that trends will continue, but this strategy represents a radical shift that will be difficult for many to make.

Storyline approach to the construction of regional climate change information

Climate science seeks to make statements of confidence about what has happened, and what will happen (conditional on scenario). The approach is effective for the global, thermodynamic aspects of climate change, but is ineffective when it comes to aspects of climate change related to atmospheric circulation, which are highly uncertain. Yet, atmospheric circulation strongly mediates climate impacts at the regional scale. In this way, the confidence framework, which focuses on avoiding type 1 errors (false alarms), raises the prospect of committing type 2 errors (missed warnings). This has ethical implications. At the regional scale, however, where information on climate change has to be combined with many other factors affecting vulnerability and exposure—most of which are highly uncertain—the societally relevant question is not ‘What will happen?’ but rather ‘What is the impact of particular actions under an uncertain regional climate change?’ This reframing of the question can cut the Gordian knot of regional climate change information, provided one distinguishes between epistemic and aleatoric uncertainties—something that is generally not done in climate projections. It is argued that the storyline approach to climate change—the identification of physically self-consistent, plausible pathways—has the potential to accomplish precisely this.

Effects of Increasing Aridity on Ambient Dust and Public Health in the U.S. Southwest Under Climate Change

The U.S. Southwest is projected to experience increasing aridity due to climate change. We quantify the resulting impacts on ambient dust levels and public health using methods consistent with the Environmental Protection Agency's Climate Change Impacts and Risk Analysis framework. We first demonstrate that U.S. Southwest fine (PM2.5) and coarse (PM2.5-10) dust levels are strongly sensitive to variability in the 2-month Standardized Precipitation-Evapotranspiration Index across southwestern North America. We then estimate potential changes in dust levels through 2099 by applying the observed sensitivities to downscaled meteorological output projected by six climate models following an intermediate (Representative Concentration Pathway 4.5, RCP4.5) and a high (RCP8.5) greenhouse gas concentration scenario. By 2080-2099 under RCP8.5 relative to 1986-2005 in the U.S. Southwest: (1) Fine dust levels could increase by 57%, and fine dust-attributable all-cause mortality and hospitalizations could increase by 230% and 360%, respectively; (2) coarse dust levels could increase by 38%, and coarse dust-attributable cardiovascular mortality and asthma emergency department visits could increase by 210% and 88%, respectively; (3) climate-driven changes in dust concentrations can account for 34-47% of these health impacts, with the rest due to increases in population and baseline incidence rates; and (4) economic damages of the health impacts could total $47 billion per year additional to the 1986-2005 value of $13 billion per year. Compared to national-scale climate impacts projected for other U.S. sectors using the Climate Change Impacts and Risk Analysis framework, dust-related mortality ranks fourth behind extreme temperature-related mortality, labor productivity decline, and coastal property loss.

Between progress and obstacles in urban climate interdisciplinary studies and knowledge transfer to society

Cities modify their local climate, and at the same time they suffer from the local impacts of climate change. Our paper discusses the progress and obstacles in three active research topics that contribute to increasing the capability within the urban climate research community for transferring local climate knowledge to society. The first is linked to the production of urban surface descriptions useful for urban climate studies. The concept of local climate zones is now widely used to represent urban climate variability at the neighborhood scale. Land-use, morphological, architectural, and social data are also needed, and those are being gathered using different approaches. The second is linked to the necessity for producing information directly connected to their effects on society. This requires a strong multidisciplinary approach, and nowadays impact studies are not limited to one dimension but instead cover multiple dimensions. The third is to transfer all this information to city practitioners, so that urban climate features are considered, among many other aspects, in city management. For urban planning, cartographic tools have been introduced to include urban climate diagnosis as well as recommendations for future urbanization.

Vulnerability of Arctic marine mammals to vessel traffic in the increasingly ice-free Northwest Passage and Northern Sea Route

The fabled Northwest Passage and Northern Sea Route that were once the quests of early Western explorers are now increasingly sea ice-free, with routine vessel transits expected by midcentury. The potential impacts of this novel vessel traffic on endemic Arctic marine mammal (AMM) species are unknown despite their critical social and ecological roles in the ecosystem and widely recognized susceptibility to ice loss. We developed a vulnerability assessment of 80 subpopulations of seven AMM species to vessel traffic during the ice-free season. Vulnerability scores were based on the combined influence of spatially explicit exposure to the sea routes and a suite of sensitivity variables. More than half of AMM subpopulations (42/80) are exposed to open-water vessel transits in the Arctic sea routes. Narwhals (Monodon monoceros) were estimated to be most vulnerable to vessel impacts, given their high exposure and sensitivity, and polar bears (Ursus maritimus) were estimated to be the least vulnerable because of their low exposure and sensitivity. Regions with geographic bottlenecks, such as the Bering Strait and eastern Canadian Arctic, were characterized by two to three times higher vulnerability than more remote regions. These pinch points are obligatory pathways for both vessels and migratory AMMs, and so represent potentially high conflict areas but also opportunities for conservation-informed planning. Some of the species and regions identified as least vulnerable were also characterized by high uncertainty, highlighting additional data and monitoring needs. Our quantification of the heterogeneity of risk across AMM species provides a necessary first step toward developing best practices for maritime industries poised to advance into this rapidly changing seascape.

Niche partitioning of intertidal seagrasses: evidence of the influence of substrate temperature

The influence of soil temperature on rhizome depths of four intertidal seagrass species was investigated in central Queensland, Australia. We postulated that certain intertidal seagrass species are soil temperature-sensitive and vertically stratify rhizome depths. Below-ground vertical stratification of intertidal seagrass rhizome depths was analysed based upon microclimate (soil temperature) and microhabitat (soil type). Soil temperature profiles exhibited heat transfer from surface layers to depth that varied by microhabitat, with vertical stratification of rhizome depths between species. Halodule uninervis rhizomes maintain a narrow median soil temperature envelope; compensating for high surface temperatures by occupying deeper, cooler soil substrates. Halophila decipiens, Halophila ovalis and Zostera muelleri rhizomes are shallow-rooted and exposed to fluctuating temperatures, with broader median temperature envelopes. Halodule uninervis appears to be a niche specialist, with the two Halophila species considered as generalist niche usage species. The implications of niche use based upon soil temperature profiles and rhizome rooting depths are discussed in the context of species' thermal tolerances and below-ground biomass O₂ demand associated with respiration and maintenance of oxic microshields. This preliminary evidence suggests that soil temperature interaction with rhizome rooting depths may be a factor that influences the distribution of intertidal seagrasses.

Climate vulnerability and resilience in the most valuable North American fishery

Managing natural resources in an era of increasing climate impacts requires accounting for the synergistic effects of climate, ecosystem changes, and harvesting on resource productivity. Coincident with recent exceptional warming of the northwest Atlantic Ocean and removal of large predatory fish, the American lobster has become the most valuable fishery resource in North America. Using a model that links ocean temperature, predator density, and fishing to population productivity, we show that harvester-driven conservation efforts to protect large lobsters prepared the Gulf of Maine lobster fishery to capitalize on favorable ecosystem conditions, resulting in the record-breaking landings recently observed in the region. In contrast, in the warmer southern New England region, the absence of similar conservation efforts precipitated warming-induced recruitment failure that led to the collapse of the fishery. Population projections under expected warming suggest that the American lobster fishery is vulnerable to future temperature increases, but continued efforts to preserve the stock's reproductive potential can dampen the negative impacts of warming. This study demonstrates that, even though global climate change is severely impacting marine ecosystems, widely adopted, proactive conservation measures can increase the resilience of commercial fisheries to climate change.

Causes of accelerating sea level on the East Coast of North America

The tide-gauge record from the North American East Coast reveals significant accelerations in sea level starting in the late twentieth century. The estimated post-1990 accelerations range from near zero to ∼0.3 mm yr^-2. We find that the observed sea level acceleration is well modeled using several processes: mass change in Greenland and Antarctica as measured by the Gravity Recovery and Climate Experiment satellites; ocean dynamic and steric variability provided by the GECCO2 ocean synthesis; and the inverted barometer effect. However, to achieve this fit requires estimation of an admittance for the dynamical and steric contribution, possibly due to the coarse resolution of this analysis or to simplifications associated with parameterization of bottom friction in the shallow coastal areas. The acceleration from ice loss alone is equivalent to a regional sea level rise in one century of 0.2 m in the north and 0.75 m in the south of this region.

Determining climate effects on US total agricultural productivity

The sensitivity of agricultural productivity to climate has not been sufficiently quantified. The total factor productivity (TFP) of the US agricultural economy has grown continuously for over half a century, with most of the growth typically attributed to technical change. Many studies have examined the effects of local climate on partial productivity measures such as crop yields and economic returns, but these measures cannot account for national-level impacts. Quantifying the relationships between TFP and climate is critical to understanding whether current US agricultural productivity growth will continue into the future. We analyze correlations between regional climate variations and national TFP changes, identify key climate indices, and build a multivariate regression model predicting the growth of agricultural TFP based on a physical understanding of its historical relationship with climate. We show that temperature and precipitation in distinct agricultural regions and seasons explain ∼70% of variations in TFP growth during 1981-2010. To date, the aggregate effects of these regional climate trends on TFP have been outweighed by improvements in technology. Should these relationships continue, however, the projected climate changes could cause TFP to drop by an average 2.84 to 4.34% per year under medium to high emissions scenarios. As a result, TFP could fall to pre-1980 levels by 2050 even when accounting for present rates of innovation. Our analysis provides an empirical foundation for integrated assessment by linking regional climate effects to national economic outcomes, offering a more objective resource for policy making.

Future sea level rise constrained by observations and long-term commitment

Sea level has been steadily rising over the past century, predominantly due to anthropogenic climate change. The rate of sea level rise will keep increasing with continued global warming, and, even if temperatures are stabilized through the phasing out of greenhouse gas emissions, sea level is still expected to rise for centuries. This will affect coastal areas worldwide, and robust projections are needed to assess mitigation options and guide adaptation measures. Here we combine the equilibrium response of the main sea level rise contributions with their last century's observed contribution to constrain projections of future sea level rise. Our model is calibrated to a set of observations for each contribution, and the observational and climate uncertainties are combined to produce uncertainty ranges for 21st century sea level rise. We project anthropogenic sea level rise of 28-56 cm, 37-77 cm, and 57-131 cm in 2100 for the greenhouse gas concentration scenarios RCP26, RCP45, and RCP85, respectively. Our uncertainty ranges for total sea level rise overlap with the process-based estimates of the Intergovernmental Panel on Climate Change. The "constrained extrapolation" approach generalizes earlier global semiempirical models and may therefore lead to a better understanding of the discrepancies with process-based projections.

Carbon choices determine US cities committed to futures below sea level

Anthropogenic carbon emissions lock in long-term sea-level rise that greatly exceeds projections for this century, posing profound challenges for coastal development and cultural legacies. Analysis based on previously published relationships linking emissions to warming and warming to rise indicates that unabated carbon emissions up to the year 2100 would commit an eventual global sea-level rise of 4.3-9.9 m. Based on detailed topographic and population data, local high tide lines, and regional long-term sea-level commitment for different carbon emissions and ice sheet stability scenarios, we compute the current population living on endangered land at municipal, state, and national levels within the United States. For unabated climate change, we find that land that is home to more than 20 million people is implicated and is widely distributed among different states and coasts. The total area includes 1,185-1,825 municipalities where land that is home to more than half of the current population would be affected, among them at least 21 cities exceeding 100,000 residents. Under aggressive carbon cuts, more than half of these municipalities would avoid this commitment if the West Antarctic Ice Sheet remains stable. Similarly, more than half of the US population-weighted area under threat could be spared. We provide lists of implicated cities and state populations for different emissions scenarios and with and without a certain collapse of the West Antarctic Ice Sheet. Although past anthropogenic emissions already have caused sea-level commitment that will force coastal cities to adapt, future emissions will determine which areas we can continue to occupy or may have to abandon.

Recent climate and air pollution impacts on Indian agriculture

Recent research on the agricultural impacts of climate change has primarily focused on the roles of temperature and precipitation. These studies show that India has already been negatively affected by recent climate trends. However, anthropogenic climate changes are a result of both global emissions of long-lived greenhouse gases (LLGHGs) and other short-lived climate pollutants (SLCPs). Two potent SLCPs, tropospheric ozone and black carbon, have direct effects on crop yields beyond their indirect effects through climate; emissions of black carbon and ozone precursors have risen dramatically in India over the past three decades. Here, to our knowledge for the first time, we present results of the combined effects of climate change and the direct effects of SLCPs on wheat and rice yields in India from 1980 to 2010. Our statistical model suggests that, averaged over India, yields in 2010 were up to 36% lower for wheat than they otherwise would have been, absent climate and pollutant emissions trends, with some densely populated states experiencing 50% relative yield losses. [Our point estimates for rice (-20%) are similarly large, but not statistically significant.] Upper-bound estimates suggest that an overwhelming fraction (90%) of these losses is due to the direct effects of SLCPs. Gains from addressing regional air pollution could thus counter expected future yield losses resulting from direct climate change effects of LLGHGs.

First look at changes in flood hazard in the Inter-Sectoral Impact Model Intercomparison Project ensemble

Climate change due to anthropogenic greenhouse gas emissions is expected to increase the frequency and intensity of precipitation events, which is likely to affect the probability of flooding into the future. In this paper we use river flow simulations from nine global hydrology and land surface models to explore uncertainties in the potential impacts of climate change on flood hazard at global scale. As an indicator of flood hazard we looked at changes in the 30-y return level of 5-d average peak flows under representative concentration pathway RCP8.5 at the end of this century. Not everywhere does climate change result in an increase in flood hazard: decreases in the magnitude and frequency of the 30-y return level of river flow occur at roughly one-third (20-45%) of the global land grid points, particularly in areas where the hydrograph is dominated by the snowmelt flood peak in spring. In most model experiments, however, an increase in flooding frequency was found in more than half of the grid points. The current 30-y flood peak is projected to occur in more than 1 in 5 y across 5-30% of land grid points. The large-scale patterns of change are remarkably consistent among impact models and even the driving climate models, but at local scale and in individual river basins there can be disagreement even on the sign of change, indicating large modeling uncertainty which needs to be taken into account in local adaptation studies.

Carbon-temperature-water change analysis for peanut production under climate change: a prototype for the AgMIP coordinated climate-crop modeling project (C3MP)

Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate-Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop modelers to explore the impacts of climate change via an investigation of crop responses to changes in carbon dioxide concentration ([CO2 ]), temperature, and water. As a demonstration of the C3MP protocols and enabled analyses, we apply the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Peanut crop model for Henry County, Alabama, to evaluate responses to the range of plausible [CO2 ], temperature changes, and precipitation changes projected by climate models out to the end of the 21st century. These sensitivity tests are used to derive crop model emulators that estimate changes in mean yield and the coefficient of variation for seasonal yields across a broad range of climate conditions, reproducing mean yields from sensitivity test simulations with deviations of ca. 2% for rain-fed conditions. We apply these statistical emulators to investigate how peanuts respond to projections from various global climate models, time periods, and emissions scenarios, finding a robust projection of modest (<10%) median yield losses in the middle of the 21st century accelerating to more severe (>20%) losses and larger uncertainty at the end of the century under the more severe representative concentration pathway (RCP8.5). This projection is not substantially altered by the selection of the AgMERRA global gridded climate dataset rather than the local historical observations, differences between the Third and Fifth Coupled Model Intercomparison Project (CMIP3 and CMIP5), or the use of the delta method of climate impacts analysis rather than the C3MP impacts response surface and emulator approach.

Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison

Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies.

Multimodel assessment of water scarcity under climate change

Water scarcity severely impairs food security and economic prosperity in many countries today. Expected future population changes will, in many countries as well as globally, increase the pressure on available water resources. On the supply side, renewable water resources will be affected by projected changes in precipitation patterns, temperature, and other climate variables. Here we use a large ensemble of global hydrological models (GHMs) forced by five global climate models and the latest greenhouse-gas concentration scenarios (Representative Concentration Pathways) to synthesize the current knowledge about climate change impacts on water resources. We show that climate change is likely to exacerbate regional and global water scarcity considerably. In particular, the ensemble average projects that a global warming of 2 °C above present (approximately 2.7 °C above preindustrial) will confront an additional approximate 15% of the global population with a severe decrease in water resources and will increase the number of people living under absolute water scarcity (<500 m(3) per capita per year) by another 40% (according to some models, more than 100%) compared with the effect of population growth alone. For some indicators of moderate impacts, the steepest increase is seen between the present day and 2 °C, whereas indicators of very severe impacts increase unabated beyond 2 °C. At the same time, the study highlights large uncertainties associated with these estimates, with both global climate models and GHMs contributing to the spread. GHM uncertainty is particularly dominant in many regions affected by declining water resources, suggesting a high potential for improved water resource projections through hydrological model development.

The multimillennial sea-level commitment of global warming

Global mean sea level has been steadily rising over the last century, is projected to increase by the end of this century, and will continue to rise beyond the year 2100 unless the current global mean temperature trend is reversed. Inertia in the climate and global carbon system, however, causes the global mean temperature to decline slowly even after greenhouse gas emissions have ceased, raising the question of how much sea-level commitment is expected for different levels of global mean temperature increase above preindustrial levels. Although sea-level rise over the last century has been dominated by ocean warming and loss of glaciers, the sensitivity suggested from records of past sea levels indicates important contributions should also be expected from the Greenland and Antarctic Ice Sheets. Uncertainties in the paleo-reconstructions, however, necessitate additional strategies to better constrain the sea-level commitment. Here we combine paleo-evidence with simulations from physical models to estimate the future sea-level commitment on a multimillennial time scale and compute associated regional sea-level patterns. Oceanic thermal expansion and the Antarctic Ice Sheet contribute quasi-linearly, with 0.4 m °C(-1) and 1.2 m °C(-1) of warming, respectively. The saturation of the contribution from glaciers is overcompensated by the nonlinear response of the Greenland Ice Sheet. As a consequence we are committed to a sea-level rise of approximately 2.3 m °C(-1) within the next 2,000 y. Considering the lifetime of anthropogenic greenhouse gases, this imposes the need for fundamental adaptation strategies on multicentennial time scales.

Incorporating uncertainty in predictive species distribution modelling

Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.

Mapping adaptation opportunities and activities in an interactive atlas

The need for transparency is taking more prominence in international climate negotiations as developed countries pledge large sums of money to foster adaptation efforts in developing countries. Tools that provide accurate and up-to-date spatial information that can be easily used and vetted by local practitioners may provide effective and affordable ways to improve transparency. The Global Adaptation Atlas is such a tool, combining vetted, publicly available climate impact data with timely maps of on the ground adaptation projects to highlight confluences of effects of climate change with actions taken to address those effects. Here, we describe the structure and general functions of the Global Adaptation Atlas and explain how it may be utilized to track short-term investments in adaptation. Over longer time scales, it may also help gauge the effectiveness of specific adaptation investments as well as reveal how different climate impacts affect long-term investment in differing regions.

Impacts of climate change on the world's most exceptional ecoregions

The current rate of warming due to increases in greenhouse gas (GHG) emissions is very likely unprecedented over the last 10,000 y. Although the majority of countries have adopted the view that global warming must be limited to <2 °C, current GHG emission rates and nonagreement at Copenhagen in December 2009 increase the likelihood of this limit being exceeded by 2100. Extensive evidence has linked major changes in biological systems to 20th century warming. The "Global 200" comprises 238 ecoregions of exceptional biodiversity [Olson DM, Dinerstein E (2002) Ann Mo Bot Gard 89:199-224]. We assess the likelihood that, by 2070, these iconic ecoregions will regularly experience monthly climatic conditions that were extreme in 1961-1990. Using >600 realizations from climate model ensembles, we show that up to 86% of terrestrial and 83% of freshwater ecoregions will be exposed to average monthly temperature patterns >2 SDs (2σ) of the 1961-1990 baseline, including 82% of critically endangered ecoregions. The entire range of 89 ecoregions will experience extreme monthly temperatures with a local warming of <2 °C. Tropical and subtropical ecoregions, and mangroves, face extreme conditions earliest, some with <1 °C warming. In contrast, few ecoregions within Boreal Forests and Tundra biomes will experience such extremes this century. On average, precipitation regimes do not exceed 2σ of the baseline period, although considerable variability exists across the climate realizations. Further, the strength of the correlation between seasonal temperature and precipitation changes over numerous ecoregions. These results suggest many Global 200 ecoregions may be under substantial climatic stress by 2100.

Implications of climate change for agricultural productivity in the early twenty-first century

This paper reviews recent literature concerning a wide range of processes through which climate change could potentially impact global-scale agricultural productivity, and presents projections of changes in relevant meteorological, hydrological and plant physiological quantities from a climate model ensemble to illustrate key areas of uncertainty. Few global-scale assessments have been carried out, and these are limited in their ability to capture the uncertainty in climate projections, and omit potentially important aspects such as extreme events and changes in pests and diseases. There is a lack of clarity on how climate change impacts on drought are best quantified from an agricultural perspective, with different metrics giving very different impressions of future risk. The dependence of some regional agriculture on remote rainfall, snowmelt and glaciers adds to the complexity. Indirect impacts via sea-level rise, storms and diseases have not been quantified. Perhaps most seriously, there is high uncertainty in the extent to which the direct effects of CO(2) rise on plant physiology will interact with climate change in affecting productivity. At present, the aggregate impacts of climate change on global-scale agricultural productivity cannot be reliably quantified.

An adaptability limit to climate change due to heat stress

Despite the uncertainty in future climate-change impacts, it is often assumed that humans would be able to adapt to any possible warming. Here we argue that heat stress imposes a robust upper limit to such adaptation. Peak heat stress, quantified by the wet-bulb temperature T(W), is surprisingly similar across diverse climates today. T(W) never exceeds 31 degrees C. Any exceedence of 35 degrees C for extended periods should induce hyperthermia in humans and other mammals, as dissipation of metabolic heat becomes impossible. While this never happens now, it would begin to occur with global-mean warming of about 7 degrees C, calling the habitability of some regions into question. With 11-12 degrees C warming, such regions would spread to encompass the majority of the human population as currently distributed. Eventual warmings of 12 degrees C are possible from fossil fuel burning. One implication is that recent estimates of the costs of unmitigated climate change are too low unless the range of possible warming can somehow be narrowed. Heat stress also may help explain trends in the mammalian fossil record.

Integrated approaches to climate-crop modelling: needs and challenges

This paper discusses the need for a more integrated approach to modelling changes in climate and crops, and some of the challenges posed by this. While changes in atmospheric composition are expected to exert an increasing radiative forcing of climate change leading to further warming of global mean temperatures and shifts in precipitation patterns, these are not the only climatic processes which may influence crop production. Changes in the physical characteristics of the land cover may also affect climate; these may arise directly from land use activities and may also result from the large-scale responses of crops to seasonal, interannual and decadal changes in the atmospheric state. Climate models used to drive crop models may, therefore, need to consider changes in the land surface, either as imposed boundary conditions or as feedbacks from an interactive climate-vegetation model. Crops may also respond directly to changes in atmospheric composition, such as the concentrations of carbon dioxide (CO2), ozone (03) and compounds of sulphur and nitrogen, so crop models should consider these processes as well as climate change. Changes in these, and the responses of the crops, may be intimately linked with meteorological processes so crop and climate models should consider synergies between climate and atmospheric chemistry. Some crop responses may occur at scales too small to significantly influence meteorology, so may not need to be included as feedbacks within climate models. However, the volume of data required to drive the appropriate crop models may be very large, especially if short-time-scale variability is important. Implementation of crop models within climate models would minimize the need to transfer large quantities of data between separate modelling systems. It should also be noted that crop responses to climate change may interact with other impacts of climate change, such as hydrological changes. For example, the availability of water for irrigation may be affected by changes in runoff as a direct consequence of climate change, and may also be affected by climate-related changes in demand for water for other uses. It is, therefore, necessary to consider the interactions between the responses of several impacts sectors to climate change. Overall, there is a strong case for a much closer coupling between models of climate, crops and hydrology, but this in itself poses challenges arising from issues of scale and errors in the models. A strategy is proposed whereby the pursuit of a fully coupled climate-chemistry-crop-hydrology model is paralleled by continued use of separate climate and land surface models but with a focus on consistency between the models.

Global and regional modelling of Arctic-boreal vegetation distribution and its sensitivity to altered forcing

Understanding the distribution and function of Arctic and boreal ecosystems under current conditions and their vulnerability to altered forcing is crucial to our assessment of future global environmental change. Such efforts can be facilitated by the development and application of ecological models that simulate realistic patterns of vegetation change at high latitudes. This paper reviews three classes of ecological models that have been implemented to extrapolate vegetation information in space (e.g. across the Arctic and adjacent domains) and over historical and future periods (e.g. under altered climate and other forcings). These are: (i) equilibrium biogeographical models; (ii) frame-based transient ecosystem models, and (iii) dynamic global vegetation models (DGVMs). The equilibrium response of high-latitude vegetation to scenarios of increased surface air temperatures projected by equilibrium biogeographical models is for tundra to be replaced by a northward shift of boreal woodland and forests. A frame-based model (ALFRESCO) indicates the same directional changes, but illustrates how response time depends on rate of temperature increase and concomitant changes in moisture regime and fire disturbance return period. Key disadvantages of the equilibrium models are that they do not simulate time-dependent responses of vegetation and the role of disturbance is omitted or highly generalized. Disadvantages of the frame-based models are that vegetation type is modelled as a set unit as opposed to an association of individually simulated plant functional types and that the role of ecosystem biogeochemistry in succession is not explicitly considered. DGVMs explicitly model disturbance (e.g. fire), operate on plant functional types, and incorporate constraints of nutrient availability on biomass production in the simulation of vegetation dynamics. Under changing climate, DGVMs detail conversion of tundra to tree-dominated boreal landscapes along with time-dependent responses of biomass, net primary production, and soil organic matter turnover--which all increase with warming. Key improvements to DGVMs that are needed to portray behaviour of arctic and boreal ecosystems adequately are the inclusion of anaerobic soil processes for inundated landscapes, permafrost dynamics, and moss-lichen layer biogeochemistry, as well as broader explicit accounting of disturbance regimes (including insect outbreaks and land management). Transient simulation of these landscapes can be further tailored to high-latitude processes and issues by spatially interactive, gridded application of arctic/boreal frame-based models and development of dynamic regional vegetation models (DRVMs) utilizing plant functional type schemes that capture the variety of high-latitude environments.