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Showing papers in "Earth’s Future in 2018"


Journal ArticleDOI
TL;DR: In this paper, the authors demonstrate links between increased upper ocean heat content due to global warming with the extreme rainfalls from recent hurricanes and show that record high ocean heat values not only increased the fuel available to sustain and intensify Harvey but also increased its flooding rains on land.
Abstract: While hurricanes occur naturally, human-caused climate change is supercharging them and exacerbating the risk of major damage. Here using ocean and atmosphere observations, we demonstrate links between increased upper ocean heat content due to global warming with the extreme rainfalls from recent hurricanes. Hurricane Harvey provides an excellent case study as it was isolated in space and time. We show that prior to the beginning of northern summer of 2017, ocean heat content was the highest on record both globally and in the Gulf of Mexico, but the latter sharply decreased with hurricane Harvey via ocean evaporative cooling. The lost ocean heat was realized in the atmosphere as moisture, and then as latent heat in record-breaking heavy rainfalls. Accordingly, record high ocean heat values not only increased the fuel available to sustain and intensify Harvey but also increased its flooding rains on land. Harvey could not have produced so much rain without human-induced climate change. Results have implications for the role of hurricanes in climate. Proactive planning for the consequences of human-caused climate change is not happening in many vulnerable areas, making the disasters much worse. Plain Language Summary Human-induced climate change continues to warm the oceans which provide the memory of past accumulated effects. The resulting environment, including higher ocean heat content and sea surface temperatures, invigorates tropical cyclones to make them more intense, bigger, and longer lasting and greatly increases their flooding rains. The main example here is Hurricane Harvey in August 2017, which can be reasonably isolated in terms of influences on and by the environment. Hurricanes keep tropical oceans cooler as a consequence of their strong winds that increase evaporation. Here we show for the first time that the rainfall likely matches the evaporation and the corresponding ocean heat loss. Planning for such supercharged hurricanes (adaptation) by increasing resilience (e.g., better building codes and flood protection) and preparing for contingencies (such as evacuation routes, power cuts, and so forth) is essential but not adequate in many areas, including Texas, Florida, and Puerto Rico where Harvey, Irma, and Maria took their toll.

200 citations


Journal ArticleDOI
TL;DR: Applications of the LHASA system are discussed, including how it is used to estimate long-term trends in potential landslide activity at a nearly global scale and how it can be used as a tool to support disaster risk assessment.
Abstract: Determining the time, location, and severity of natural disaster impacts is fundamental to formulating mitigation strategies, appropriate and timely responses, and robust recovery plans. A Landslide Hazard Assessment for Situational Awareness (LHASA) model was developed to indicate potential landslide activity in near real-time. LHASA combines satellite-based precipitation estimates with a landslide susceptibility map derived from information on slope, geology, road networks, fault zones, and forest loss. Precipitation data from the Global Precipitation Measurement (GPM) mission are used to identify rainfall conditions from the past seven days. When rainfall is considered to be extreme and susceptibility values are moderate to very high, a nowcast is issued to indicate the times and places where landslides are more probable. When LHASA nowcasts were evaluated with a Global Landslide Catalog, the probability of detection (POD) ranged from 8 to 60%, depending on the evaluation period, precipitation product used, and the size of the spatial and temporal window considered around each landslide point. Applications of the LHASA system are also discussed, including how LHASA is used to estimate long-term trends in potential landslide activity at a nearly global scale and how it can be used as a tool to support disaster risk assessment. LHASA is intended to provide situational awareness of landslide hazards in near real-time, providing a flexible, open source framework that can be adapted to other spatial and temporal scales based on data availability.

161 citations


Journal ArticleDOI
TL;DR: In this article, the authors extend a large dimensional intertemporal CGE trade model to account for the various effects of global warming (e.g., loss in agricultural productivity, sea level rise, and health effects) on Gross Domestic Product (GDP) growth and levels for 139 countries, by decade and over the long term.
Abstract: Computable general equilibrium (CGE) models are a standard tool for policy analysis and forecasts of economic growth. Unfortunately, due to computational constraints, many CGE models are dimensionally small, aggregating countries into an often limited set of regions or using assumptions such as static price-level expectations, where next period’s price is conditional only on current or past prices. This is a concern for climate change modeling, since the effects of global warming by country, in a fully disaggregated and global trade model, are needed, and the known future effects of global warming should be included in forward-looking forecasts for prices and profitability. This work extends a large dimensional intertemporal CGE trade model to account for the various effects of global warming (e.g., loss in agricultural productivity, sea level rise, and health effects) on Gross Domestic Product (GDP) growth and levels for 139 countries, by decade and over the long term, where producers look forward and adjust price expectations and capital stocks to account for future climate effects. The potential economic gains from complying with the Paris Accord are also estimated, showing that even with a limited set of possible damages from global warming, these gains are substantial. For example, with the comparative case of Representative Concentration Pathway 8.5 (4∘C), the global gains from complying with the 2∘C target (Representative Concentration Pathway 4.5) are approximately US$17,489 billion per year in the long run (year 2100). The relative damages from not complying to Sub-Sahara Africa, India, and Southeast Asia, across all temperature ranges, are especially severe.

156 citations


Journal ArticleDOI
TL;DR: Treating infrastructure as SETS shows promise for increasing the adaptive capacity of infrastructure systems by highlighting how lock‐in and vulnerabilities evolve and how multidisciplinary strategies can be deployed to address these challenges by broadening the options for adaptation.
Abstract: Traditional infrastructure adaptation to extreme weather events (and now climate change) has typically been techno-centric and heavily grounded in robustness—the capacity to prevent or minimize disruptions via a risk-based approach that emphasizes control, armoring, and strengthening (e.g., raising the height of levees). However, climate and nonclimate challenges facing infrastructure are not purely technological. Ecological and social systems also warrant consideration to manage issues of overconfidence, inflexibility, interdependence, and resource utilization—among others. As a result, techno-centric adaptation strategies can result in unwanted tradeoffs, unintended consequences, and underaddressed vulnerabilities. Techno-centric strategies that lock-in today’s infrastructure systems to vulnerable future design, management, and regulatory practices may be particularly problematic by exacerbating these ecological and social issues rather than ameliorating them. Given these challenges, we develop a conceptual model and infrastructure adaptation case studies to argue the following: (1) infrastructure systems are not simply technological and should be understood as complex and interconnected social, ecological, and technological systems (SETSs); (2) infrastructure challenges, like lock-in, stem from SETS interactions that are often overlooked and underappreciated; (3) framing infrastructure with a SETS lens can help identify and prevent maladaptive issues like lock-in; and (4) a SETS lens can also highlight effective infrastructure adaptation strategies that may not traditionally be considered. Ultimately, we find that treating infrastructure as SETS shows promise for increasing the adaptive capacity of infrastructure systems by highlighting how lock-in and vulnerabilities evolve and how multidisciplinary strategies can be deployed to address these challenges by broadening the options for adaptation. Plain Language Summary Instead of thinking of infrastructure as purely technological artifacts, we instead propose considering infrastructure as linked social, ecological, and technological systems (SETS). Adopting a SETS lens can help identify vulnerabilities that develop within infrastructure systems over time. Ultimately, adopting this SETS perspective will not only help us better understand our infrastructure systems, but also aid in the development strategies for adapting to the many challenges that our infrastructure will continue to face (climate change, interdependencies, technological evolution, growing complexity, etc.)

147 citations


Journal ArticleDOI
TL;DR: In this article, the authors review 10 years of academic literature and use text analysis to elucidate how six major disciplines (climatology, earth sciences, ecology, engineering, hydrology, and social sciences) define and communicate extreme events.
Abstract: Extreme events are of interest worldwide given their potential for substantial impacts on social, ecological, and technical systems. Many climate-related extreme events are increasing in frequency and/or magnitude due to anthropogenic climate change, and there is increased potential for impacts due to the location of urbanization and the expansion of urban centers and infrastructures. Many disciplines are engaged in research and management of these events. However, a lack of coherence exists in what constitutes and defines an extreme event across these fields, which impedes our ability to holistically understand and manage these events. Here, we review 10 years of academic literature and use text analysis to elucidate how six major disciplines--climatology, earth sciences, ecology, engineering, hydrology, and social sciences--define and communicate extreme events. Our results highlight critical disciplinary differences in the language used to communicate extreme events. Additionally, we found a wide range in definitions and thresholds, with more than half of examined papers not providing an explicit definition, and disagreement over whether impacts are included in the definition. We urge distinction between extreme events and their impacts, so that we can better assess when responses to extreme events have actually enhanced resilience. Additionally, we suggest that all researchers and managers of extreme events be more explicit in their definition of such events as well as be more cognizant of how they are communicating extreme events. We believe clearer and more consistent definitions and communication can support transdisciplinary understanding and management of extreme events.

147 citations


Journal ArticleDOI
TL;DR: A conceptual framework describing when relative robustness values of decision alternatives obtained using different metrics are likely to agree and disagree is introduced, used as a measure of how “stable” the ranking of decision alternative is when determined using different robustness metrics.
Abstract: Robustness is being used increasingly for decision analysis in relation to deep uncertainty and many metrics have been proposed for its quantification. Recent studies have shown that the application of different robustness metrics can result in different rankings of decision alternatives, but there has been little discussion of what potential causes for this might be. To shed some light on this issue, we present a unifying framework for the calculation of robustness metrics, which assists with understanding how robustness metrics work, when they should be used, and why they sometimes disagree. The framework categorizes the suitability of metrics to a decision-maker based on (1) the decision-context (i.e., the suitability of using absolute performance or regret), (2) the decision-maker's preferred level of risk aversion, and (3) the decision-maker's preference toward maximizing performance, minimizing variance, or some higher-order moment. This article also introduces a conceptual framework describing when relative robustness values of decision alternatives obtained using different metrics are likely to agree and disagree. This is used as a measure of how “stable” the ranking of decision alternatives is when determined using different robustness metrics. The framework is tested on three case studies, including water supply augmentation in Adelaide, Australia, the operation of a multipurpose regulated lake in Italy, and flood protection for a hypothetical river based on a reach of the river Rhine in the Netherlands. The proposed conceptual framework is confirmed by the case study results, providing insight into the reasons for disagreements between rankings obtained using different robustness metrics.

140 citations


Journal ArticleDOI
TL;DR: In this article, the authors introduce a quantitative framework to assess global aggregate ecosystem services from existing vegetation in cities and an intensive urban agriculture adoption scenario based on data-driven estimates of urban morphology and vacant land.
Abstract: Though urban agriculture (UA), defined here as growing of crops in cities, is increasing in popularity and importance globally, little is known about the aggregate benefits of such natural capital in built-up areas. Here, we introduce a quantitative framework to assess global aggregate ecosystem services from existing vegetation in cities and an intensive UA adoption scenario based on data-driven estimates of urban morphology and vacant land. We analyzed global population, urban, meteorological, terrain, and Food and Agriculture Organization (FAO) datasets in Google Earth Engine to derive global scale estimates, aggregated by country, of services provided by UA. We estimate the value of four ecosystem services provided by existing vegetation in urban areas to be on the order of $33 billion annually. We project potential annual food production of 100–180 million tonnes, energy savings ranging from 14 to 15 billion kilowatt hours, nitrogen sequestration between 100,000 and 170,000 tonnes, and avoided storm water runoff between 45 and 57 billion cubic meters annually. In addition, we estimate that food production, nitrogen fixation, energy savings, pollination, climate regulation, soil formation and biological control of pests could be worth as much as $80–160 billion annually in a scenario of intense UA implementation. Our results demonstrate significant country-to-country variability in UA-derived ecosystem services and reduction of food insecurity. These estimates represent the first effort to consistently quantify these incentives globally, and highlight the relative spatial importance of built environments to act as change agents that alleviate mounting concerns associated with global environmental change and unsustainable development.

140 citations


Journal ArticleDOI
TL;DR: In this paper, a cross-sectoral assessment of the potential impacts at a pan-European scale is presented and key messages communicated, which indicate that the world is likely to pass the +1.5°C threshold in the coming decades.
Abstract: The Paris Agreement of the United Nations Framework Convention on Climate Change aims not only at avoiding +2°C warming (and even limit the temperature increase further to +1.5°C), but also sets long-term goals to guide mitigation. Therefore, the best available science is required to inform policymakers on the importance of and the adaptation needs in a +1.5°C warmer world. Seven research institutes from Europe and Turkey integrated their competencies to provide a cross-sectoral assessment of the potential impacts at a pan-European scale. The initial findings of this initiative are presented and key messages communicated. The approach is to select periods based on global warming thresholds rather than the more typical approach of selecting time periods (e.g., end of century). The results indicate that the world is likely to pass the +1.5°C threshold in the coming decades. Cross-sectoral dimensions are taken into account to show the impacts of global warming that occur in parallel in more than one sector. Also, impacts differ across sectors and regions. Alongside the negative impacts for certain sectors and regions, some positive impacts are projected. Summer tourism in parts of Western Europe may be favored by climate change; electricity demand decreases outweigh increases over most of Europe and catchment yields in hydropower regions will increase. However, such positive findings should be interpreted carefully as we do not take into account exogenous factors that can and will influence Europe such as migration patterns, food production, and economic and political instability.

134 citations



Journal ArticleDOI
TL;DR: The greening of the South China Karst has been studied in this article, where the authors find a major increase in growing season vegetation cover from 69% in 1999 to 81% in 2017 occurring over 1.4 million km.
Abstract: Above-ground vegetation biomass is one of the major carbon sinks and provides both provisioning (e.g., forestry products) and regulating ecosystem services (by sequestering carbon). Continuing deforestation and climate change threaten this natural resource but can effectively be countered by national conservation policies. Here we present time series (1999–2017) derived from complementary satellite systems to describe a phenomenon of global significance: the greening of South China Karst. We find a major increase in growing season vegetation cover from 69% in 1999 to 81% in 2017 occurring over ~1.4 million km. Over 1999–2012, we report one of the globally largest increases in biomass to occur in the South China Karst region (on average +4% over 0.9 million km), which accounts for ~5% of the global areas characterized with increases in biomass. These increases in southern China’s vegetation have occurred despite a decline in rainfall ( 8%) and soil moisture ( 5%) between 1999 and 2012 and are derived from effects of forestry and conservation activities at an unprecedented spatial scale in human history (~20,000 km yr 1 since 2002). These findings have major implications for the provisioning of ecosystem services not only for the Chinese karst ecosystem (e.g., carbon storage, water filtration, and timber production) but also for the study of global carbon cycles.

119 citations



Journal ArticleDOI
TL;DR: The authors used a finer ecological classification and fire-relevant climate predictors, and created statistical models linking climate and wildfire area burned for ecosections, which are geographic delineations based on biophysical variables.
Abstract: We developed ecologically based climate-fire projections for the western United States. Using a finer ecological classification and fire-relevant climate predictors, we created statistical models linking climate and wildfire area burned for ecosections, which are geographic delineations based on biophysical variables. The results indicate a gradient from purely fuel-limited (antecedent positive water balance anomalies or negative energy balance anomalies) to purely flammability-limited (negative water balance anomalies or positive energy balance anomalies) fire regimes across ecosections. Although there are other influences (such as human ignitions and management) on fire occurrence and area burned, seasonal climate significantly explains interannual fire area burned. Differences in the role of climate across ecosections are not random, and the relative dominance of climate predictors allows objective classification of ecosection climate-fire relationships. Expected future trends in area burned range from massive increases, primarily in flammability limited systems near the middle of the water balance deficit distribution, to substantial decreases, in fuel-limited nonforested systems. We predict increasing area burned in most flammability-limited systems but predict decreasing area burned in primarily fuel-limited systems with a flammability-limited (“hybrid”) component. Compared to 2030–2059 (2040s), projected area burned for 2070–2099 (2080s) increases much more in the flammability and flammability-dominated hybrid systems than those with equal control and continues to decrease in fuel-limited hybrid systems. Exceedance probabilities for historical 95th percentile fire years are larger in exclusively flammability-limited ecosections than in those with fuel controls. Filtering the projected results using a fire-rotation constraint minimizes overprojection due to static vegetation assumptions, making projections more conservative. Plain Language Summary Most people, including many familiar with fire ecology and future climate, assume that the area burned by wildfire will increase in a warmer climate. This depends a lot on what kind of ecosystem wemean. In all ecosystems, fuels must be available to fire for fires to get very big, but the climate controls on those fuels vary widely with vegetation. In wetter forests, it takes an abnormally warm, dry year to make normally wet fuels available. But in many drier ecosystems, fuels are dry enough to burn most years—whether fires get big depends also on whether there is sufficient fuel available to carry fires over large areas. In this kind of vegetation, abnormally wet years in the year prior to fire can create larger or more connected fuels that then lead to larger fires. In this study, we use this concept to investigate how future area burned might be affected by climate change. We found that some ecosystems will burn much more, just as expected. But some will actually burn less. We characterized these futures for 70 different ecosystems around the West. The similarities and differences illustrate the range of futures that might be expected under climate change.

Journal ArticleDOI
TL;DR: In this article, structural decomposition analysis (SDA) and environmentally extended input output analysis (EEIOA) were used to decompose China's energy consumption changes during 2005-2012 into five factors: population, efficiency, production structure, consumption patterns, and consumption volume.
Abstract: Energy consumption is one of main reasons for global warming and highly correlated with economic development. As the largest energy consumer worldwide, China has entered a new economic development model – the "new normal". This study aims to explore the pattern shift in China's energy consumption growth in this new development phase. We use structural decomposition analysis (SDA) and environmentally extended input‐output analysis (EEIOA) to decompose China's energy consumption changes during 2005‐2012 into five factors: population, efficiency, production structure, consumption patterns, and consumption volume. During the period of the global financial crisis, the energy consumption generated by China's exports dropped, while the energy consumption generated by capital formation grew rapidly. Over three quarters of China's energy consumption growth was caused by capital formation during 2007‐2010. This growth is mainly because of China's economic stimulus measures in response to the global recession, with a focus on infrastructure construction. In the new normal, the strongest factors offsetting China's energy consumption have been shifting from efficiency gains to structural changes. Efficiency gains were the strongest factor offsetting China's energy consumption in traditional development model and offset 42% of energy consumption between 2005 and 2010 by keeping other driving forces constant. Since 2010, however, their effects offsetting energy have become weak. The production structure and consumption patterns both drove China's energy consumption growth in the traditional development model and drove energy consumption growth by 31% and 12% between 2005 and 2010, respectively. Since 2010, however, both factors have started to offset China's energy consumption.

Journal ArticleDOI
TL;DR: Analysis of the highest temperature of the year for approximately 9000 stations globally, focusing on quantifying spatially explicit exceedance probabilities during the recent 50‐ and 30‐year periods, shows a global increase of 0.19°C per decade during the past 50 years (through 2015) accelerated to 0.25°C each year during the last 30 years, a faster increase than in the mean annual temperature.
Abstract: Trends in short-lived high-temperature extremes record a different dimension of change than the extensively studied annual and seasonal mean daily temperatures. They also have important socioeconomic, environmental, and human health implications. Here, we present analysis of the highest temperature of the year for approximately 9000 stations globally, focusing on quantifying spatially explicit exceedance probabilities during the recent 50- and 30-year periods. A global increase of 0.19°C per decade during the past 50 years (through 2015) accelerated to 0.25°C per decade during the last 30 years, a faster increase than in the mean annual temperature. Strong positive 30-year trends are detected in large regions of Eurasia and Australia with rates higher than 0.60°C per decade. In cities with more than 5 million inhabitants, where most heat-related fatalities occur, the average change is 0.33°C per decade, while some east Asia cities, Paris, Moscow, and Houston have experienced changes higher than 0.60°C per decade.

Journal ArticleDOI
TL;DR: In this article, a multilevel model for yield prediction at the country level is developed and demonstrated, and the structural relationships between average yield and climate attributes as well as trends are estimated simultaneously.
Abstract: During the last few decades, the global agricultural production has risen and technology enhancement is still contributing to yield growth. However, population growth, water crisis, deforestation, and climate change threaten the global food security. An understanding of the variables that caused past changes in crop yields can help improve future crop prediction models. In this article, we present a comprehensive global analysis of the changes in the crop yields and how they relate to different large-scale and regional climate variables, climate change variables and technology in a unified framework. A new multilevel model for yield prediction at the country level is developed and demonstrated. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. El Nino-southern oscillation (ENSO), Palmer drought severity index (PDSI), geopotential height anomalies (GPH), historical carbon dioxide (CO2) concentration and country-based time series of GDP per capita as an approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2013. Results indicate that these variables can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications. While some countries were not generally affected by climatic factors, PDSI and GPH acted both positively and negatively in different regions for crop yields in many countries.

Journal ArticleDOI
TL;DR: In this paper, the authors focus on estimating the air pollution in the Arctic caused by local emission sources, and present-day inventories show a large spread in the amount and location of emissions representing a significant source of uncertainty in model predictions that often deviate significantly from observations.
Abstract: Air pollution in the Arctic caused by local emission sources is a challenge that is important but often overlooked. Local Arctic air pollution can be severe and significantly exceed air quality standards, impairing public health and affecting ecosystems. Specifically in the wintertime, pollution can accumulate under inversion layers. However, neither the contributing emission sources are well identified and quantified nor the relevant atmospheric mechanisms forming pollution are well understood. In the summer, boreal forest fires cause high levels of atmospheric pollution. Despite the often high exposure to air pollution, there are neither specific epidemiological nor toxicological health impact studies in the Arctic. Hence, effects on the local population are difficult to estimate at present. Socioeconomic development of the Arctic is already occurring and expected to be significant in the future. Arctic destination shipping is likely to increase with the development of natural resource extraction, and tourism might expand. Such development will not only lead to growth in the population living in the Arctic but will likely increase emission types and magnitudes. Present‐day inventories show a large spread in the amount and location of emissions representing a significant source of uncertainty in model predictions that often deviate significantly from observations. This is a challenge for modeling studies that aim to assess the impacts of within Arctic air pollution. Prognoses for the future are hence even more difficult, given the additional uncertainty of estimating emissions based on future Arctic economic development scenarios.


Journal ArticleDOI
TL;DR: In this paper, the authors used the Dynamic Interactive Vulnerability Assessment (DIVA) modeling framework to project land and population exposed in the 1 in 100 year coastal flood plain under sea-level rise and population change.
Abstract: We use multiple synthetic mitigation sea-level scenarios, together with a non-mitigation sea-level scenario from the Warming Acidification and Sea-level Projector model. We find sea-level rise continues to accelerate post 2100 for all but the most aggressive mitigation scenarios indicative of 1.5°C and 2.0°C. Using the Dynamic Interactive Vulnerability Assessment modelling framework, we project land and population exposed in the 1 in 100 year coastal flood plain under sea-level rise and population change. In 2000, the flood plain is estimated at 540 x103 km2. By 2100, under the mitigation scenarios, it ranges between 610 x103 km2 and 640 x103 km2 [580 x103 km2 and 700 x103 km2 for the 5th and 95th percentiles]. Thus differences between the mitigation scenarios are small in 2100. However, in 2300, flood plains are projected to increase to between 700 x103 km2 and 960 x103 km2 in 2300 [610 x103 km2 and 1,290 x103 km2] for the mitigation scenarios, but 1,630 x103 km2 [1,190 x103 km2 and 2,220 x103 km2] for the non-mitigation scenario. The proportion of global population exposed to sea-level rise in 2300 is projected to be between 1.5% and 5.4% [1.2% to 7.6%] (assuming no population growth after 2100) for the aggressive mitigation and the non-mitigation scenario, respectively. Hence over centennial timescales there are significant benefits to climate change mitigation and temperature stabilization. However, sea-levels will continue to rise albeit at lower rates. Thus potential impacts will keep increasing necessitating adaptation to existing coastal infrastructure and the careful planning of new coastal developments. Plain Language Summary If we reduce greenhouse gas emissions and stabilize global temperatures, sea‐level rise (SLR) will continue at a reduced rate for centuries. This is because changes to the ocean and cryosphere (ice) which contribute to SLR take very long timescales to respond to changes in global warming. Early and aggressive climate change mitigation will be most effective to reduce flood risk, particularly after the 21st century. Even with climate change mitigation, the land area exposed to coastal flooding will continue to increase for centuries. Adapting the coast to cope with rising sea levels is inevitably required. The long‐term implications for coastal habitation need to be considered.


Journal ArticleDOI
TL;DR: In this article, an integrated approach for assessing past and future agricultural drought risks that relies on multimodel ensemble simulations calibrated for rice, maize, and wheat (RMW) in China is proposed.
Abstract: Agricultural food production in China is deeply vulnerable to extreme droughts. Although there are many studies to evaluate this issue from different aspects, comprehensive assessments with full consideration of climate change, crop rotations, irrigation effects, and socioeconomic factors in broad scales have not been well addressed. Considering both the probability of drought occurrence and the consequential yield losses, here we propose an integrated approach for assessing past and future agricultural drought risks that relies on multimodel ensemble simulations calibrated for rice, maize, and wheat (RMW) in China. Our results show that irrigation has reduced drought-related yield losses by 31 ± 2\%; the largest reductions in food production were primarily attributable to socioeconomic factors rather than droughts during 1955–2014. Unsustainable water management, especially groundwater management, could potentially cause disastrous consequences in both food production and water supply in extreme events. Our simulations project a rise of 2.5 3.3\% in average rice, maize, and wheat productivity before 2050 but decrease thereafter if climate warming continues. The frequency of extreme agricultural droughts in China is projected to increase under all examined Representative Concentration Pathway (RCP). A current 100-year drought is projected to occur once every 30 years under RCP 2.6, once every 13 years under RCP 4.5, and once every 5 years under RCP 8.5. This increased occurrence of severe droughts would double the rate of drought-induced yield losses in the largest warming scenario. Policies for future food security should prioritize sustainable intensification and conservation of groundwater, as well as geographically balanced water resource and food production.

Journal ArticleDOI
TL;DR: It is concluded that some relatively simple policies could protect a solar geoengineering system against most of the plausible drivers, and should be resilient against all but the most extreme catastrophes.
Abstract: If solar geoengineering were to be deployed so as to mask a high level of global warming, and then stopped suddenly, there would be a rapid and damaging rise in temperatures. This effect is often referred to as termination shock, and it is an influential concept. Based on studies of its potential impacts, commentators often cite termination shock as one of the greatest risks of solar geoengineering. However, there has been little consideration of the likelihood of termination shock, so that conclusions about its risk are premature. This paper explores the physical characteristics of termination shock, then uses simple scenario analysis to plot out the pathways by which different driver events (such as terrorist attacks, natural disasters, or political action) could lead to termination. It then considers where timely policies could intervene to avert termination shock. We conclude that some relatively simple policies could protect a solar geoengineering system against most of the plausible drivers. If backup deployment hardware were maintained and if solar geoengineering were implemented by agreement among just a few powerful countries, then the system should be resilient against all but the most extreme catastrophes. If this analysis is correct, then termination shock should be much less likely, and therefore much less of a risk, than has previously been assumed. Much more sophisticated scenario analysis—going beyond simulations purely of worst-case scenarios—will be needed to allow for more insightful policy conclusions.


Journal ArticleDOI
TL;DR: In this article, the authors investigate the effects of 1.5°C and 2.0°C global warming on the Asian-Australian monsoon region (AAMR) using five models from the Half a degree Additional Warming, Prognosis and Projected Impacts (HAPPI) project.
Abstract: In light of the Paris Agreement, it is essential to identify regional impacts of half a degree additional global warming to inform climate adaptation and mitigation strategies. We investigate the effects of 1.5°C and 2.0°C global warming above pre-industrial conditions, relative to present day (2006-2015), over the Asian-Australian monsoon region (AAMR) using five models from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project. There is considerable inter-model variability in projected changes to mean climate and extreme events in 2.0°C and 1.5°C scenarios. There is high confidence in projected increases to mean and extreme surface temperatures over AAMR, as well as more-frequent persistent daily temperature extremes over East Asia, Australia and northern India with an additional 0.5°C warming, which are likely to occur. Mean and extreme monsoon precipitation amplify over AAMR, except over Australia at 1.5°C where there is uncertainty in the sign of the change. Persistent daily extreme precipitation events are likely to become more frequent over parts of East Asia and India with an additional 0.5°C warming. There is lower confidence in projections of precipitation change than in projections of surface temperature change. These results highlight the benefits of limiting the global-mean temperature change to 1.5°C above pre-industrial, as the severity of the above effects increases with an extra 0.5°C warming.

Journal ArticleDOI
TL;DR: In this paper, the authors applied the multimodel ensemble mean of COORDinated Regional climate Downscaling EXperiment-Africa regional climate model projections to investigate future changes in heat stress and the proportion of human population at risk under 1.5 °C and 2 °C global warming scenarios over West Africa.
Abstract: Heat and discomfort indices are applied to the multimodel ensemble mean of COordinated Regional climate Downscaling EXperiment‐Africa regional climate model projections to investigate future changes in heat stress and the proportion of human population at risk under 1.5 °C and 2 °C global warming scenarios over West Africa. The results show that heat stress of category Extreme Caution is projected to extend spatially (up to 25%) over most of the Gulf of Guinea, Sahel, and Sahara desert areas, with different regional coverage during the various seasons. Similarly, the projected seasonal proportion of human population at discomfort substantially increases to more than 50% over most of the region. In particular, in June–August over the Sahel and the western Sahara desert, new areas (15% of West Africa) where most of the population is at risk emerge. This indicates that from 50% to almost everyone over most of the Sahel countries and part of the western Sahara desert is at risk of possible heat cramp, heat exhaustion, and heat stroke in future climate scenarios. These conditions become more frequent and are accompanied by the emergence of days with dangerous heat stress category during which everyone feels discomfort and is vulnerable to a likely heat cramp and heat exhaustion. In general, all the above features are more extended and more frequent in the 2 °C than in the 1.5 °C scenario. Protective measures are thus required for outdoor workers, occupational settings in hot environments, and people engaged in strenuous activities.

Journal ArticleDOI
TL;DR: A large database of climate change futures that can support “bottom‐up” scenario generation techniques that capture a broader array of consequences than those that emerge from limited sampling of a few reference scenarios is contributed.



Journal ArticleDOI
TL;DR: In this article, the authors presented a techno-economic and life-cycle assessment for co-locating a 121-ha algae facility with a 2,680-ha eucalyptus forest for BECCS.
Abstract: Bioenergy Carbon Capture and Storage (BECCS) has been proposed to reduce atmospheric CO2 concentrations, but concerns remain about competition for arable land and freshwater. The synergistic integration of algae production, which does not require arable land or freshwater, with BECCS (called “ABECCS”) can reduce CO2 emissions without competing with agriculture. This study presents a techno-economic and life-cycle assessment for co-locating a 121-ha algae facility with a 2,680-ha eucalyptus forest for BECCS. The eucalyptus biomass fuels combined heat and power generation (CHP) with subsequent amine based carbon capture and storage (CCS). A portion of the captured CO2 is used for growing algae and the remainder is sequestered. Biomass combustion supplies CO2, heat, and electricity, thus increasing the range of sites suitable for algae cultivation. Economic, energetic, and environmental impacts are considered. The system yields as much protein as soybeans while generating 61.5 TJ of electricity and sequestering 29,600 t of CO2 per year. More energy is generated than consumed and the freshwater footprint is roughly equal to that for soybeans. Financial break-even is achieved for product value combinations ranging from 1) algal biomass sold for $1,780/t without a carbon credit to 2) algal biomass sold for $100/t with a carbon credit of $396/t. Sensitivity analysis shows significant reductions to the cost of carbon sequestration are possible. The ABECCS system represents a unique technology for negative emissions without reducing protein production or increasing water demand, and should therefore be included in the suite of technologies being considered to address global sustainability.

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TL;DR: Overall, the midcentury drought is observed to be significantly worse, with many more extreme heat days, record‐low snowpack, increased soil drying, and record‐high forest mortality.
Abstract: The California drought of 2012-2016 was a record-breaking event with extensive social, political, and economic repercussions. The impacts were widespread and exposed the difficulty in preparing for the effects of prolonged dry conditions. Although the lessons from this drought drove important changes to state law and policy, there is little doubt that climate change will only exacerbate future droughts. To understand the character of future drought, this paper examines this recent drought period retrospectively and prospectively, that is, as it occurred historically and if similar dynamical conditions to the historical period were to arise 30 years later (2042-2046) subject to the effects of climate change. Simulations were conducted using the Weather Research and Forecasting model using the pseudo global warming method. The simulated historical and future droughts are contrasted in terms of temperature, precipitation, snowpack, soil moisture, evapotranspiration, and forest health. Overall, the midcentury drought is observed to be significantly worse, with many more extreme heat days, record-low snowpack, increased soil drying, and record-high forest mortality. With these findings in mind, the data sets developed in this study provide a means to structure future drought planning around a drought scenario that is realistic and modeled after a memorable historical analog.

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TL;DR: In the field of participatory modeling, the implicit and explicit knowledge of stakeholders to create formalized and shared representations of reality has evolved into a field of study as well as a practice.
Abstract: Participatory modeling engages the implicit and explicit knowledge of stakeholders to create formalized and shared representations of reality and has evolved into a field of study as well as a practice. Participatory modeling researchers and practitioners who focus specifically on environmental resources met at the National Socio-Environmental Synthesis Center (SESYNC) in Annapolis, Maryland, over the course of 2 years to discuss the state of the field and future directions for participatory modeling. What follows is a description of 12 overarching groups of questions that could guide future inquiry.