Personal harm and support for climate change mitigation policies: Evidence from 10 U.S. communities impacted by extreme weather

A growing body of research examines the role of extreme weather experience—as one of the most personal, visceral (and increasingly frequent and severe) impacts of climate change—in shaping views on climate change. A remaining question is whether the experience of an extreme weather event increases climate change concern via experiential learning or reinforces existing views via motivated reasoning. Building on this work, we explore the relationship between personal experience and climate change policy preferences using surveys in 10 communities that experienced extreme weather events (3 tornadoes, 3 floods, 2 wildfires, 1 hurricane and 1 landslide). We find that self-reported personal harm aligns with objective measures of event impacts and that personal harm (i.e., experience) is associated with higher levels of policy support. However, we do not find that objective measures of event impacts are related to policy support. Though political ideology (i.e., motivated reasoning) dominates our model of policy support in predictable ways, personal harm moderates this relationship suggesting that conservatives reporting higher levels of personal harm from the event are, on average, more likely to express support for climate policy than those reporting lower levels of harm. We postulate that while extreme weather events may serve as teachable moments on climate change, their lessons may only reach conservatives who feel personally harmed, even in the communities most affected.     

Mapping the shadow of experience of extreme weather events

Climate change will increase the frequency and/or intensity of certain extreme weather events, and perceived experience with extreme weather may influence climate change beliefs, attitudes, and behaviors. However, the aspects of extreme events that influence whether or not people perceive that they have personally experienced them remain unclear. We investigate (1) the correspondence of reported experience of extreme weather events with documented events, and (2) how characteristics of different extreme events shape the geographic area within which people are likely to report they have experienced it—the event’s perceived “shadow of experience.” We overlay geocoded survey responses indicating personal experience with hurricanes, tornadoes, and drought—from a 2012 nationally representative survey (N?=?1,008) of U.S. residents—on maps of recorded event impacts. We find that reported experiences correspond well with recorded event impacts, particularly for hurricanes and tornadoes. Reported experiences were related to event type, proximity, magnitude and duration. The results suggest locations where disaster preparedness efforts and climate change education campaigns could be most effective after an extreme weather event.     

Integrated assessment of abrupt climatic changes

One of the most controversial conclusions to emerge from many of the first generation of integrated assessment models (IAMs) of climate policy was the perceived economic optimality of negligible near-term abatement of greenhouse gases. Typically, such studies were conducted using smoothly varying climate change scenarios or impact responses. Abrupt changes observed in the climatic record and documented in current models could substantially alter the stringency of economically optimal IAM policies. Such abrupt climatic changes — or consequent impacts — would be less foreseeable and provide less time to adapt, and thus would have far greater economic or environmental impacts than gradual warming. We extend conventional, smooth IAM analysis by coupling a climate model capable of one type of abrupt change to a well-established energy–economy model (DICE). We compare the DICE optimal policy using the standard climate sub-model to our version that allows for abrupt change — and consequent enhanced climate damage — through changes in the strength (and possible collapse) of the North Atlantic thermohaline circulation (THC). We confirm the potential significance of abrupt climate change to economically optimal IAM policies, thus calling into question all previous work neglecting such possibilities — at the least for the wide ranges of relevant social and climate system parameters we consider. In addition, we obtain an emergent property of our coupled social–natural system model: “optimal policies” that do consider abrupt changes may, under relatively low discount rates, calculate emission control levels sufficient to avoid significant abrupt change, whereas “optimal policies” disregarding abrupt change would not prevent this non-linear event. However, there is a threshold in discount rate above which the present value of future damages is so low that even very large enhanced damages in the 22nd century, when a significant abrupt change such as a THC collapse would be most likely to occur, do not increase optimal control levels sufficiently to prevent such a collapse. Thus, any models not accounting for potential abrupt non-linear behavior and its interaction with the discounting formulation are likely to miss an important set of possibilities relevant to the climate policy debate.     

Impacts of different diffusion scenarios for mitigation technology options and of model representations regarding renewables intermittency on evaluations of CO2 emissions reductions

This paper evaluated the impacts of climate change mitigation technology options on CO₂ emission reductions and the effects of model representations regarding renewable intermittency on the assessment of reduction by using a world energy systems model. First, different diffusion scenarios for carbon dioxide capture and storage (CCS), nuclear power, and wind power and solar PV are selected from EMF27 scenarios to analyze their impacts on CO₂ emission reductions. These technologies are important for reducing CO₂ intensity of electricity, and the impacts of their diffusion levels on mitigation costs are significant, according to the analyses. Availability of CCS in particular, among the three kinds of technologies, has a large impact on the marginal CO₂ abatement cost. In order to analyze effects of model representations regarding renewables intermittency, four different representations are assumed within the model. A simplistic model representation that does not take into consideration the intermittency of wind power and solar PV evaluates larger contributions of the energy sources than those evaluated by a model representation that takes intermittency into consideration. Appropriate consideration of renewables intermittency within global energy systems models will be important for realistic evaluations of climate change mitigation scenarios.     

The role of renewable energy in climate stabilization: results from the EMF27 scenarios

This paper uses the EMF27 scenarios to explore the role of renewable energy (RE) in climate change mitigation. Currently RE supplies almost 20 % of global electricity demand. Almost all EMF27 mitigation scenarios show a strong increase in renewable power production, with a substantial ramp-up of wind and solar power deployment. In many scenarios, renewables are the most important long-term mitigation option for power supply. Wind energy is competitive even without climate policy, whereas the prospects of solar photovoltaics (PV) are highly contingent on the ambitiousness of climate policy. Bioenergy is an important and versatile energy carrier; however—with the exception of low temperature heat—there is less scope for renewables other than biomass for non-electric energy supply. Despite the important role of wind and solar power in climate change mitigation scenarios with full technology availability, limiting their deployment has a relatively small effect on mitigation costs, if nuclear and carbon capture and storage (CCS)—which can serve as substitutes in low-carbon power supply—are available. Limited bioenergy availability in combination with limited wind and solar power by contrast, results in a more substantial increase in mitigation costs. While a number of robust insights emerge, the results on renewable energy deployment levels vary considerably across the models. An in-depth analysis of a subset of EMF27 reveals substantial differences in modeling approaches and parameter assumptions. To a certain degree, differences in model results can be attributed to different assumptions about technology costs, resource potentials and systems integration.     

Climate change adaptation strategies for smallholder farmers in the Brazilian Sertão

Climate models agree that semi-arid regions around the world are likely to experience increased rainfall variability and longer droughts in the coming decades. In regions dependent on agriculture, such changes threaten to aggravate existing food insecurity and economic underdevelopment, and to push migration to urban areas. In the Brazilian semi-arid region, the Sertão, farmers’ vulnerability to climate—past, present, and future—stems from several factors, including low yielding production practices and reliance on scarce and seasonally variable water resources. Using interpolated local climate data, we show that, since 1962, in the Bacia do Jacuípe—one of the poorest regions in the Sertão of Bahía state—average temperatures have increased?~?2 °C and rainfall has decreased?~?350 mm. Over the same time period, average milk productivity—the main rural economic activity in the county—has fallen while in Brazil and in Bahía as a whole milk productivity has increased dramatically. This paper teases apart the drivers of climate vulnerability of the Bacia do Jacuípe in relation to the rest of Bahía. We then present the results of a suite of pilot projects by Adapta Sertão, a coalition of organizations working to improve the adaptive capacity of farmers living in the semi-arid region. By testing a number of different technologies and arrangements at the farm level, Adapta Sertão has shown that interventions focused on balanced animal diets and efficient irrigation systems can help reduce (but not eliminate) the dependence of production systems from climate. They are thus viable adaptation strategies that should be tested at a larger scale, with implications for semi-arid regions worldwide.     

Measuring whether municipal climate networks make a difference: the case of utility-scale solar PV investment in large global cities

With cities being responsible for up to 70% of energy-related carbon emissions, municipal governments worldwide are becoming increasingly aware of their responsibility to act. Many large cities have committed to mitigation by becoming member of a municipal climate network, such as the C40 or the Compact of Mayors. However, there is no consistent assessment of whether membership of such networks translates into measurable outcomes. To fill this gap, we propose the use of novel outcome variables, combining financial data with geospatial information. As a starting point, this paper compares utility-scale investment in photovoltaics (PV) within the administrative boundaries of large global cities, combining the Bloomberg New Energy Finance database with information from Google Maps. We analyse 512 global cities with a population of above 1 million, and consider the impact of 5 networks and 2 reporting platforms. The results suggest that membership of the C40 network has a positive effect on utility-scale solar PV investment, while no such evidence is found for any of the other networks or reporting platforms under study. Based on our findings, we recommend that municipal climate networks increase their efforts to trigger city regulation that is conducive to solar PV investment. More generally, measuring early indicators, such as low-carbon investment, can help municipal climate networks in their role as ‘commitment brokers’ for climate action on the ever-more important city level.

Key policy insights

• Cities have considerable policy space to foster utility-scale solar PV investment within their administrative boundaries.

• While some large global cities exhibited significant growth in utility-scale solar PV, many others with good solar potential did not have a single project by the end of 2016.

• Outside of China (where city boundaries often include rural areas), Tokyo tops the list with utility-scale solar PV projects by far, followed by San Diego and Rome.

• Membership of the C40 network appears to make a positive difference to PV investment, unlike other networks or reporting platforms.

• Outcome measures like low-carbon investment can be used more generally to assess the climate action performance of cities.

     

Semiquantitative Assessment of Regional Climate Vulnerability: The North-Rhine Westphalia Study

Climate change will bring about a sea change in environmental conditions worldwide during the 21th century. In particular, most of the extreme events and natural disaster regimes prevailing today will be transformed, thus exposing innumerable natural and socio-economic systems to novel risks that will be difficult to cope with. This crucial component of vulnerability to anthropogenic interference with the climate system is analyzed using powerful pattern recognition methods from statistical physics. The analysis is of intermediate character, with respect to spatial scale and complexity level respectively, and therefore allows a rapid regional assessment for any area of interest. The approach is based on a comprehensive inventory of all those ecological and socioeconomic assets in a region that are significantly sensitive to extreme weather (and climate) events. Advanced cluster analysis techniques are then employed to derive from the inventory a set of thematic maps that succinctly summarize – and visualize – the differential vulnerabilities characteristic of the area in question. This information can prepare decision makers and the general public for the climate change hazards to be faced and facilitates a precautionary climate change risk management. The semiquantitative methodology described and applied here can be easily extended to other aspects of climate change assessment.     

Climate change impacts on the energy system: a review of trends and gaps

Major transformation of the global energy system is required for climate change mitigation. However, energy demand patterns and supply systems are themselves subject to climate change impacts. These impacts will variously help and hinder mitigation and adaptation efforts, so it is vital they are well understood and incorporated into models used to study energy system decarbonisation pathways. To assess the current state of understanding of this topic and identify research priorities, this paper critically reviews the literature on the impacts of climate change on the energy supply system, summarising the regional coverage of studies, trends in their results and sources of disagreement. We then examine the ways in which these impacts have been represented in integrated assessment models of the electricity or energy system.Studies tend to agree broadly on impacts for wind, solar and thermal power stations. Projections for impacts on hydropower and bioenergy resources are more varied. Key uncertainties and gaps remain due to the variation between climate projections, modelling limitations and the regional bias of research interests. Priorities for future research include the following: further regional impact studies for developing countries; studies examining impacts of the changing variability of renewable resources, extreme weather events and combined hazards; inclusion of multiple climate feedback mechanisms in IAMs, accounting for adaptation options and climate model uncertainty.     

Extreme events in a changing climate: Variability is more important than averages

Extreme events act as a catalyst for concern about whether the climate is changing. Statistical theory for extremes is used to demonstrate that the frequency of such events is relatively more dependent on any changes in the variability (more generally, the scale parameter) than in the mean (more generally, the location parameter) of climate. Moreover, this sensitivity is relatively greater the more extreme the event. These results provide additional support for the conclusions that experiments using climate models need to be designed to detect changes in climate variability, and that policy analysis should not rely on scenarios of future climate involving only changes in means.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Adaptation to climate change in Africa: Challenges and opportunities identified from Ethiopia

Africa is widely held to be highly vulnerable to future climate change and Ethiopia is often cited as one of the most extreme examples. With this in mind we seek to identify entry points to integrate short- to medium-term climate risk reduction within development activities in Africa, drawing from experiences in Ethiopia. To achieve this we employ a range of data and methods. We examine the changing nature of climate risks using analysis of recent climate variability, future climate scenarios and their secondary impacts. We assess the effects of climate variability on agricultural production and national GDP. Entry points and knowledge gaps in relation to mainstreaming climate risks in Ethiopia are identified using the Government's plan for poverty reduction. We end with a case study incorporating climate risks through drought insurance within the current social protection programme in Ethiopia, which provides support to 8.3 million people.Rainfall behaviour in Ethiopia shows no marked emergent changes and future climate projections show continued warming but very mixed patterns of rainfall change. Economic analysis highlights sensitivities within the economy to large-scale drought, however, while the effects are clear in major drought years in other years the relationship is weak. For social protection fairly small positive and negative effects on the number of recipients and frequency of cash payments during drought occur under the extreme range of climate model rainfall projections (2020s).Our analysis highlights several important challenges and opportunities for addressing climate risks. Challenges primarily relate to the large uncertainties in climate projections for parts of Africa, a weak evidence base of complex, often non-deterministic, climate-society interactions and institutional issues. Opportunities relate to the potential for low-regrets measures to reduce vulnerability to current climate variability which can be integrated with relatively modest effort within a shift in Africa from a disaster-focused view of climate to a long-term perspective that emphasises livelihood security and vulnerability reduction.     

International low carbon technology transfer: Do intellectual property regimes matter?

Transfer of low carbon technologies to developing countries has been recognized as important in global efforts to limit climate change. Yet the mechanics of international technology transfer, especially around intellectual property rights, have remained a controversial issue in international negotiations. Using a new dataset on international partnerships in China and India in three key low carbon technologies—solar photovoltaics, electric vehicles, and coal gasification/integrated gasification combined cycle—and complementary expert interviews we study the dynamics of the transfer of intellectual property and the underlying drivers that guide the development of business strategies and partnerships in the context of transitioning intellectual property regimes in emerging markets. We find that weak intellectual property regimes are indeed a hindrance to the diffusion of certain classes of low carbon technologies: (i) for cutting-edge technologies, (ii) for fully-embodied (explicitly codified) technologies, and (iii) for small firms. However, we also find that intellectual property issues do not represent a barrier to the diffusion of the relatively mature and low to medium cost low carbon technologies that are materially (at scale) most important for carbon dioxide emissions reduction in the short to medium term. Competitive technology supply, shifting market dynamics, and increasingly vigorous domestic innovation coupled with mechanisms and opportunities to structure credible intellectual property deals allow for the diffusion of key low carbon technologies to occur within the context of existing business, political, and institutional structures.     

REGIONAL CLIMATE CHANGE SCENARIOS FOR VULNERABILITY AND ADAPTATION ASSESSMENTS

This paper describes the regional climate change scenarios that are recommended for use in the U.S. Country Studies Program (CSP) and evaluates how well four general circulation models (GCMs) simulate current climate over Europe. Under the umbrella of the CSP, 50 countries with varying skills and experience in developing climate change scenarios are assessing vulnerability and adaptation. We considered the use of general circulation models, analogue warm periods, and incremental scenarios as the basis for creating climate change scenarios. We recommended that participants in the CSP use a combination of GCM based scenarios and incremental scenarios. The GCMs, in spite of their many deficiencies, are the best source of information about regional climate change. Incremental scenarios help identify sensitivities to changes in a particular meteorological variable and ensure that a wide range of regional climate change scenarios are considered. We recommend using the period 1951–1980 as baseline climate because it was a relatively stable climate period globally. Average monthly changes from the GCMs and the incremental changes in climate variables are combined with the historical record to produce scenarios. The scenarios do not consider changes in interannual, daily, or subgrid scale variability. Countries participating in the Country Studies Program were encouraged to compare the GCMs' estimates of current climate with actual long-term climate means. In this paper, we compare output of four GCMs (CCCM, GFDL, UKMO, and GISS) with observed climate over Europe by performing a spatial correlation analysis for temperature and precipitation, by statistically comparing spatial patterns averaged climate estimates from the GCMs with observed climate, and by examining how well the models estimate seasonal patterns of temperature and precipitation. In Europe, the GISS and CCCM models best simulate current temperature, whereas the GISS and UK89 models, and the CCCM model, best simulate precipitation in defined northern and southern regions, respectively.     

Which downscaled rainfall data for climate change impact studies in urban areas? Review of current approaches and trends

Changes in extreme precipitation should be one of the primary impacts of climate change (CC) in urban areas. To assess these impacts, rainfall data from climate models are commonly used. The main goal of this paper is to report on the state of knowledge and recent works on the study of CC impacts with a focus on urban areas, in order to produce an integrated review of various approaches to which future studies can then be compared or constructed. Model output statistics (MOS) methods are increasingly used in the literature to study the impacts of CC in urban settings. A review of previous works highlights the non-stationarity nature of future climate data, underscoring the need to revise urban drainage system design criteria. A comparison of these studies is made difficult, however, by the numerous sources of uncertainty arising from a plethora of assumptions, scenarios, and modeling options. All the methods used do, however, predict increased extreme precipitation in the future, suggesting potential risks of combined sewer overflow frequencies, flooding, and back-up in existing sewer systems in urban areas. Future studies must quantify more accurately the different sources of uncertainty by improving downscaling and correction methods. New research is necessary to improve the data validation process, an aspect that is seldom reported in the literature. Finally, the potential application of non-stationarity conditions into generalized extreme value (GEV) distribution should be assessed more closely, which will require close collaboration between engineers, hydrologists, statisticians, and climatologists, thus contributing to the ongoing reflection on this issue of social concern.     

Present-day and future Amazonian precipitation in global climate models: CMIP5 versus CMIP3

The present study aims at evaluating and comparing precipitation over the Amazon in two sets of historical and future climate simulations based on phase 3 (CMIP3) and 5 (CMIP5) of the Coupled Model Intercomparison Project. Thirteen models have been selected in order to discuss (1) potential improvements in the simulation of present-day climate and (2) the potential reduction in the uncertainties of the model response to increasing concentrations of greenhouse gases. While several features of present-day precipitation—including annual cycle, spatial distribution and co variability with tropical sea surface temperature (SST)—have been improved, strong uncertainties remain in the climate projections. A closer comparison between CMIP5 and CMIP3 highlights a weaker consensus on increased precipitation during the wet season, but a stronger consensus on a drying and lengthening of the dry season. The latter response is related to a northward shift of the boreal summer intertropical convergence zone in CMIP5, in line with a more asymmetric warming between the northern and southern hemispheres. The large uncertainties that persist in the rainfall response arise from contrasted anomalies in both moisture convergence and evapotranspiration. They might be related to the diverse response of tropical SST and ENSO (El Niño Southern Oscillation) variability, as well as to spurious behaviours among the models that show the most extreme response. Model improvements of present-day climate do not necessarily translate into more reliable projections and further efforts are needed for constraining the pattern of the SST response and the soil moisture feedback in global climate scenarios.     

Climate change adaptation implications for drought risk mitigation: a perspective for India

There is a growing evidence that the climate change do has implications for drought vulnerable India with studies projecting future possible reductions in monsoon related rainfall in the country. The existing drought risk mitigation and response mechanisms were looked into and gaps were identified by drawing lessons from previous disasters and response mechanisms. In absence of reliable climate predictions at the scales that make them useful for policy level planning, the emphasis was on identifying no-regret adaptation options those would reduce current vulnerabilities while mainstreaming the adaptation in the long run. The most notable climate change implications for the drought vulnerable India are the enhanced preparedness with due emphasis to the community based preparedness planning, reviewing the existing monsoon and drought prediction methodologies, and establishing drought monitoring and early warning systems in association with a matching preparedness at the input level.     

Estimating economic effects of changes in climate and water availability

Social, economic, and environmental systems can be vulnerable to disruptions in water supplies that are likely to accompany future climate changes. Coupled with the challenges of tightening environmental regulations, population growth, economic development and fiscal constraints water supply systems are being pushed beyond the limits of their design and capacity for maintenance. In this paper we briefly review key economic concepts, various economic measures and metrics, and methods to estimate the economic effects on water resources from water supply changes that could accompany climate change. We survey some of the recent empirical literature that focuses on estimates developed for U.S. watersheds at both national and regional scales. Reported estimates of potential damage and loss associated with climate and water supply changes that we observe are significant, though often the metrics vary and make valid and consistent direct cross-comparisons difficult. Whether in terms of changes in GDP or in terms of estimated changes in economic welfare based on associated changes in economic costs and benefits, both national and regional estimates suggest that governments and organizations incorporate prudent steps to assess vulnerabilities to plausible future water supply and demand scenarios and develop responsive adaptation strategies.     

Scenarios that illuminate vulnerabilities and robust responses

Scenarios exist so that decision makers and those who provide them with information can make statements about the future that claim less confidence than do predictions, projections, and forecasts. Despite their prevalence, fundamental questions remain about how scenarios should best be developed and used. This paper proposes a particular conceptualization of scenarios that aims to address many of the challenges faced when using scenarios to inform contentious policy debates. The concept envisions scenarios as illuminating the vulnerabilities of proposed policies, that is, as concise summaries of the future states of the world in which a proposed policy would fail to meet its goals. Such scenarios emerge from a decision support process that begins with a proposed policy, seeks to understand the conditions under which it would fail, and then uses this information to identify and evaluate potential alternative policies that are robust over a wide range of future conditions. Statistical cluster analyses applied to databases of simulation model results can help identify scenarios as part of this process. Drawing on themes from the decision support literature, this paper first reviews difficulties faced when using scenarios to inform climate-related decisions, describes the proposed approach to address these challenges, illustrates the approach with applications for three different types of users, and concludes with some thoughts on implications for the provision of climate information and for future scenario processes.     

Integrated multi-scalar analysis of vulnerability to environmental hazards: Assessing extreme flooding in western Amazonia

Environmental change is significantly altering hydrological systems worldwide, with substantial impacts for the people who live on floodplains and depend on rivers for their livelihoods and lifeways. Amazonia is a region significantly affected by these changes, particularly more severe flooding. This paper proposes a multi-scalar approach to vulnerability, applying it empirically to the analysis of household vulnerability to the 2011 flood—the second largest flood event along the Ucayali River in 30 years—in terms of exposure, impacts, and responses. Locally relevant indicators for assets, social identity, and social networks at the community and household levels are used to examine their role in shaping flood vulnerability, the interplay of community-level and household-level factors, and differential vulnerability across exposure, impacts, and responses to the same hazard event. We find that the most common impacts of severe flooding in rural Amazonia are on agriculture and that fishing is the dominant response strategy. This study suggests that covariate shocks, like floods, can have distinct idiosyncratic impacts and responses among households. We demonstrate that more integrated approaches to vulnerability analysis offer potential for better understanding differential vulnerabilities within populations as well as for drawing comparisons across hazard events and different settings.     

Understanding Climatic Impacts, Vulnerabilities, and Adaptation in the United States: Building a Capacity for Assessment

Based on the experience of the U.S. National Assessment, we propose a program of research and analysis to advance capability for assessment of climate impacts, vulnerabilities, and adaptation options. We identify specific priorities for scientific research on the responses of ecological and socioeconomic systems to climate and other stresses; for improvement in the climatic inputs to impact assessments; and for further development of assessment methods to improve their practical utility to decision-makers. Finally, we propose a new institutional model for assessment, based principally on regional efforts that integrate observations, research, data, applications, and assessment on climate and linked environmental-change issues. The proposed program will require effective collaboration between scientists, resource managers, and other stakeholders, all of whose expertise is needed to define and prioritize key regional issues, characterize relevant uncertainties, and assess potential responses. While both scientifically and organizationally challenging, such an integrated program holds the best promise of advancing our capacity to manage resources and the economy adaptively under a changing climate.