Climate Change Risk Perception and Communication: Addressing a Critical Moment?

Climate change is an increasingly salient issue for societies and policy‐makers worldwide. It now raises fundamental interdisciplinary issues of risk and uncertainty analysis and communication. The growing scientific consensus over the anthropogenic causes of climate change appears to sit at odds with the increasing use of risk discourses in policy: for example, to aid in climate adaptation decision making. All of this points to a need for a fundamental revision of our conceptualization of what it is to do climate risk communication. This Special Collection comprises seven papers stimulated by a workshop on “Climate Risk Perceptions and Communication” held at Cumberland Lodge Windsor in 2010. Topics addressed include climate uncertainties, images and the media, communication and public engagement, uncertainty transfer in climate communication, the role of emotions, localization of hazard impacts, and longitudinal analyses of climate perceptions. Climate change risk perceptions and communication work is critical for future climate policy and decisions.     

Addressing Climate Change as an Emerging Risk to Infrastructure Systems

The consequences that climate change could have on infrastructure systems are potentially severe but highly uncertain. This should make risk analysis a natural framework for climate adaptation in infrastructure systems. However, many aspects of climate change, such as weak background knowledge and societal controversy, make it an emerging risk where traditional approaches for risk assessment and management cannot be confidently employed. A number of research developments aimed at addressing these issues have emerged in recent years, such as the development of probabilistic climate projections, climate services, and robust decision frameworks. However, additional research is needed to improve the suitability of these methods for infrastructure planning. In this perspective, we outline some of the challenges in addressing climate change risks to infrastructure and summarize new developments aimed at meeting these challenges. We end by highlighting needs for future research, many of which could be well‐served by expertise within the risk analysis community.     

Rural Nevada and Climate Change: Vulnerability,Beliefs, and Risk Perception

In this article, we present the results of a study investigating the influence of vulnerability to climate change as a function of physical vulnerability, sensitivity, and adaptive capacity on climate change risk perception. In 2008/2009, we surveyed Nevada ranchers and farmers to assess their climate change‐related beliefs, and risk perceptions, political orientations, and socioeconomic characteristics. Ranchers’ and farmers’ sensitivity to climate change was measured through estimating the proportion of their household income originating from highly scarce water‐dependent agriculture to the total income. Adaptive capacity was measured as a combination of the Social Status Index and the Poverty Index. Utilizing water availability and use, and population distribution GIS databases; we assessed water resource vulnerability in Nevada by zip code as an indicator of physical vulnerability to climate change. We performed correlation tests and multiple regression analyses to examine the impact of vulnerability and its three distinct components on risk perception. We find that vulnerability is not a significant determinant of risk perception. Physical vulnerability alone also does not impact risk perception. Both sensitivity and adaptive capacity increase risk perception. While age is not a significant determinant of it, gender plays an important role in shaping risk perception. Yet, general beliefs such as political orientations and climate change‐specific beliefs such as believing in the anthropogenic causes of climate change and connecting the locally observed impacts (in this case drought) to climate change are the most prominent determinants of risk perception.     

Variability and Uncertainty Meet Risk Management and Risk Communication

In the past decade, the use of probabilistic risk analysis techniques to quantitatively address variability and uncertainty in risks increased in popularity as recommended by the 1994 National Research Council that wrote Science and Judgment in Risk Assessment. Under the 1996 Food Quality Protection Act, for example, the U.S. EPA supported the development of tools that produce distributions of risk demonstrating the variability and/or uncertainty in the results. This paradigm shift away from the use of point estimates creates new challenges for risk managers, who now struggle with decisions about how to use distributions in decision making. The challenges for risk communication, however, have only been minimally explored. This presentation uses the case studies of variability in the risks of dying on the ground from a crashing airplane and from the deployment of motor vehicle airbags to demonstrate how better characterization of variability and uncertainty in the risk assessment lead to better risk communication. Analogies to food safety and environmental risks are also discussed. This presentation demonstrates that probabilistic risk assessment has an impact on both risk management and risk communication, and highlights remaining research issues associated with using improved sensitivity and uncertainty analyses in risk assessment.     

A Disciplinary Perspective on the Epistemological Status of Risk

A unique multidisciplinary perspective on the risk literature is used to establish a fresh and provocative argument regarding the epistemological understanding and definition of risk. Building on economic conceptualizations that distinguish risk from uncertainty and argue that risk is an ordered application of knowledge to the unknown, the survey identifies each of the disciplines as having a particular knowledge approach with which they confront the unknown so as to order its randomness and convert it into a risk proposition. This epistemological approach suggests the concept of risk can act as a mirror, reflecting the preoccupations, strengths, and weaknesses of each discipline as they grapple with uncertainty. The conclusion suggests that the different disciplines can, and desirably should, act in concert toward a cumulative appreciation of risk that progresses our understanding of the concept. One way in which the article challenges risk experts to join disciplinary forces in a collaborative effort is to holistically appreciate and articulate the concept of political risk calculation.     

Integrated Analysis: Combining Risk and Economic Assessments While Preserving the Separation of Powers

This article presents a process for an integrated policy analysis that combines risk assessment and benefit-cost analysis. This concept, which explicitly combines the two types of related analyses, seems to contradict the long-accepted risk analysis paradigm of separating risk assessment and risk management since benefit-cost analysis is generally considered to be a part of risk management. Yet that separation has become a problem because benefit-cost analysis uses risk assessment results as a starting point and considerable debate over the last several years focused on the incompatibility of the use of upper bounds or "safe" point estimates in many risk assessments with benefit-cost analysis. The problem with these risk assessments is that they ignore probabilistic information. As advanced probabilistic techniques for risk assessment emerge and economic analysts receive distributions of risks instead of point estimates, the artificial separation between risk analysts and the economic/decision analysts complicates the overall analysis. In addition, recent developments in countervailing risk theory suggest that combining the risk and benefit-cost analyses is required to fully understand the complexity of choices and tradeoffs faced by the decisionmaker. This article also argues that the separation of analysis and management is important, but that benefit-cost analysis has been wrongly classified into the risk management category and that the analytical effort associated with understanding the economic impacts of risk reduction actions need to be part of a broader risk assessment process.     

Comparative Risk and Policy Analysis in Environmental Health

There is increasing interest in the integration of quantitative risk analysis with benefit-cost and cost-effectiveness methods to evaluate environmental health policy making and perform comparative analyses. However, the combined use of these methods has revealed deficiencies in the available methods, and the lack of useful analytical frameworks currently constrains the utility of comparative risk and policy analyses. A principal issue in integrating risk and economic analysis is the lack of common performance metrics, particularly when conducting comparative analyses of regulations with disparate health endpoints (e.g., cancer and noncancer effects or risk-benefit analysis) and quantitative estimation of cumulative risk, whether from exposure to single agents with multiple health impacts or from exposure to mixtures. We propose a general quantitative framework and examine assumptions required for performing analyses of health risks and policies. We review existing and proposed risk and health-impact metrics for evaluating policies designed to protect public health from environmental exposures, and identify their strengths and weaknesses with respect to their use in a general comparative risk and policy analysis framework. Case studies are presented to demonstrate applications of this framework with risk-benefit and air pollution risk analyses. Through this analysis, we hope to generate discussions regarding the data requirements, analytical approaches, and assumptions required for general models to be used in comparative risk and policy analysis.     

Three Conceptions of Quantified Societal Risk

In several European countries efforts are undertaken, in particular with regard to fixed industrial installations and transport of dangerous substances, to quantify the "societal risk" (SR) of accidents that may cause more than one victim at a time. This article explores the nature of such efforts. SR-models are essentially ways to structure the distribution of potential social costs of decisions about hazardous activities (e.g., costs of risk reduction, of land use forgone). First, the various ways to describe SR quantitatively, and to set limits to SR will be presented in short. Next, using a scheme developed by Fischhoff and colleagues, the various approaches will be placed in broad categories of reaching acceptable risk decisions: bootstrapping, formal analysis, and professional judgment. Each of the three categories offers a particular appreciation of the risks as 'external costs'. This has important political implications. In the discussion it is argued that local SR-limits, by the very nature of SR, should be set in a way that creates consistency with any potential supra-local interests involved. Second, particular attention is paid to the validity of claims that SR-limits should reflect a strong risk aversion.     

Risk Communication and Foodborne Illness: Message Sponsorship and Attempts to Stimulate Perceptions of Risk

Foodborne illness represents a serious health hazard in the United States. Since foodborne illness can often be prevented by an individual's behavior, messages aimed at promoting safe food-handling behaviors should be a major tool to reduce the incidence of foodborne illness. This article argues that to achieve adoption of safe food-handling practices in the home, food-safety messages should both stimulate risk perceptions and promote self-efficacy, feelings that one can successfully enact recommended behaviors. A content analysis of nationally distributed food-safety messages questioned if messages incorporated these features. Since food-safety communicators operate in complex environments with multiple and sometimes competing objectives, this study also questioned if sponsorship of foodborne illness prevention messages was related to the amount of content designed to alter risk perceptions associated with foodborne illness. Results of the quantitative content analysis found that copywriters generally included content designed to stimulate risk perception about foodborne illness but virtually ignored self-efficacy needs of the audience. A marked difference in tendencies to stimulate risk perceptions was found based on sponsorship. Both in volume and proportion, results show that governmentally sponsored messages more aggressively attempted to heighten risk perceptions associated with foodborne illness than did messages sponsored by privately funded communicators.     

Risk Communication,Public Engagement,and Climate Change: A Role for Emotions

This article discusses the potential role that emotions might play in enticing a lifestyle that diminishes climate change. Climate change is an important challenge for society. There is a growing consensus that climate change is due to our behavior, but few people are willing to significantly adapt their lifestyle. Empirical studies show that people lack a sense of urgency: they experience climate change as a problem that affects people in distant places and in a far future. Several scholars have claimed that emotions might be a necessary tool in communication about climate change. This article sketches a theoretical framework that supports this hypothesis, drawing on insights from the ethics of risk and the philosophy of emotions. It has been shown by various scholars that emotions are important determinants in risk perception. However, emotions are generally considered to be irrational states and are hence excluded from communication and political decision making about risky technologies and climate change, or they are used instrumentally to create support for a position. However, the literature on the ethics of risk shows that the dominant, technocratic approach to risk misses the normative‐ethical dimension that is inherent to decisions about acceptable risk. Emotion research shows that emotions are necessary for practical and moral decision making. These insights can be applied to communication about climate change. Emotions are necessary for understanding the moral impact of the risks of climate change, and they also paradigmatically provide for motivation. Emotions might be the missing link in effective communication about climate change.     

The Politicization of Risk: Party Cues,Polarization, and Public Perceptions of Climate Change Risk

Previous research shows that public perceptions of climate change risk are strongly related to the individual willingness to support climate mitigation and adaptation policy. In this article, I investigate how public perceptions of climate change risk are affected by communications from political parties and the degree of polarization among them. Specifically, using survey data from Sweden, Norway, Australia, and New Zealand, I study the relationship between party source cues, perceived polarization, and public perceptions of climate change risk. The results reveal a positive relationship between party cues and perceptions of climate change risk, indicating that individuals adjust their risk perceptions to align with their party preference. Furthermore, a negative relationship between perceived polarization and individual risk perceptions is also discovered, showing that individuals tend to be less concerned with climate change the more polarization they perceive. However, the effect of perceived polarization is found to be limited to more abstract perceptions of risk, while being unrelated to perceptions of concrete risks. Even with some contextual variance, the results generally hold up well across the four countries.     

Parenthood and Worrying About Climate Change: The Limitations of Previous Approaches

The present study considers the correlation between parenthood and worry about the consequences of climate change. Two approaches to gauging people's perceptions of the risks of climate change are compared: the classic approach, which measures risk perception, and the emotion‐based approach, which measures feelings toward a risk object. The empirical material is based on a questionnaire‐based survey of 3,529 people in Sweden, of whom 1,376 answered, giving a response rate of 39%. The results show that the correlation of parenthood and climate risk is significant when the emotional aspect is raised, but not when respondents were asked to do cognitive estimates of risk. Parenthood proves significant in all three questions that measure feelings, demonstrating that it is a determinant that serves to increase worry about climate change.     

Perception of Climate Risk among Rural Farmers in Vietnam: Consistency within Households and with the Empirical Record

Rural farmers in Vietnamese communes perceive climate risk and potential impacts on livelihood within a complex context that may influence individual and household decisions. In a primary survey of 1,145 residents of the Thach Ha district of Ha Tinh province, we gathered data regarding perception about stability in climate, potential risks to livelihood, demographic characteristics, orientation toward risk, and interest in expanding economic activity. Temporal analysis of meteorological and economic indicator data forms an empirical basis for comparison with human perception. We ask the basic question: Are rural farmers’ perceptions of climate consistent with the historical record and reproducible within households? We find that respondents do perceive climate anomalies, with some anchoring on recent extreme events as revealed by climate observational data, and further that spouses disproportionately share perceptions relative to randomly simulated pairings. To put climate‐related risk perception in a larger context, we examine patterns across a range of risks to livelihood faced by farmers (livestock disease, pests, markets, health), using dimension reduction techniques. We find that our respondents distinguish among potential causes of low economic productivity, with substantial emphasis on climate‐related impacts. They do not express uniform concern across risks, but rather average patterns reveal common modes and distinguish climate concern. Still, among those expressing concern about climate‐related risks to livelihood we do not find an association with expressed intention to pursue changes in economic activity as a risk management response.     

Game Theory and Risk Analysis

Risk analysts often analyze adversarial risks from terrorists or other intelligent attackers without mentioning game theory. Why? One reason is that many adversarial situations—those that can be represented as attacker‐defender games, in which the defender first chooses an allocation of defensive resources to protect potential targets, and the attacker, knowing what the defender has done, then decides which targets to attack—can be modeled and analyzed successfully without using most of the concepts and terminology of game theory. However, risk analysis and game theory are also deeply complementary. Game‐theoretic analyses of conflicts require modeling the probable consequences of each choice of strategies by the players and assessing the expected utilities of these probable consequences. Decision and risk analysis methods are well suited to accomplish these tasks. Conversely, game‐theoretic formulations of attack‐defense conflicts (and other adversarial risks) can greatly improve upon some current risk analyses that attempt to model attacker decisions as random variables or uncertain attributes of targets (“threats”) and that seek to elicit their values from the defender's own experts. Game theory models that clarify the nature of the interacting decisions made by attackers and defenders and that distinguish clearly between strategic choices (decision nodes in a game tree) and random variables (chance nodes, not controlled by either attacker or defender) can produce more sensible and effective risk management recommendations for allocating defensive resources than current risk scoring models. Thus, risk analysis and game theory are (or should be) mutually reinforcing.     

Expert and Layperson Perceptions of Ecosystem Risk

This research examines and compares perceptions held by laypeople and ecologists about risks to ecosystems, particularly risk from global climate change (GCC). A survey elicited perceptions of 31 risk characteristics for 13 GCC and 12 non-GCC risks to ecosystems. Factor analysis was used to examine the structure of layperson and expert risk perceptions. Both experts and laypeople tend to perceive GCC risks to ecosystems as less avoidable and more acceptable than risks from other causes. Compared to laypeople's perceptions, though, experts perceived GCC risks to have slightly lower impacts, be less avoidable, more acceptable, and less understandable than non-GCC risks to ecosystems. These findings may help guide efforts to communicate with laypeople about ecological risks from climate change.     

The [R]Evolving Relationship Between Risk Assessment and Risk Management

In Science and Decisions: Advancing Risk Assessment, the National Research Council recommends improvements in the U.S. Environmental Protection Agency's approach to risk assessment. The recommendations aim to increase the utility of these assessments, embedding them within a new risk‐based decision‐making framework. The framework involves first identifying the problem and possible options for addressing it, conducting related analyses, then reviewing the results and making the risk management decision. Experience with longstanding requirements for regulatory impact analysis provides insights into the implementation of this framework. First, neither the Science and Decisions framework nor the framework for regulatory impact analysis should be viewed as a static or linear process, where each step is completed before moving on to the next. Risk management options are best evaluated through an iterative and integrative procedure. The extent to which a hazard has been previously studied will strongly influence analysts’ ability to identify options prior to conducting formal analyses, and these options will be altered and refined as the analysis progresses. Second, experience with regulatory impact analysis suggests that legal and political constraints may limit the range of options assessed, contrary to both existing guidance for regulatory impact analysis and the Science and Decisions recommendations. Analysts will need to work creatively to broaden the range of options considered. Finally, the usefulness of regulatory impact analysis has been significantly hampered by the inability to quantify many health impacts of concern, suggesting that the scientific improvements offered within Science and Decisions will fill an crucial research gap.     

An Emerging New Risk Analysis Science: Foundations and Implications

To solve real‐life problems—such as those related to technology, health, security, or climate change—and make suitable decisions, risk is nearly always a main issue. Different types of sciences are often supporting the work, for example, statistics, natural sciences, and social sciences. Risk analysis approaches and methods are also commonly used, but risk analysis is not broadly accepted as a science in itself. A key problem is the lack of explanatory power and large uncertainties when assessing risk. This article presents an emerging new risk analysis science based on novel ideas and theories on risk analysis developed in recent years by the risk analysis community. It builds on a fundamental change in thinking, from the search for accurate predictions and risk estimates, to knowledge generation related to concepts, theories, frameworks, approaches, principles, methods, and models to understand, assess, characterize, communicate, and (in a broad sense) manage risk. Examples are used to illustrate the importance of this distinct/separate risk analysis science for solving risk problems, supporting science in general and other disciplines in particular.     

Risk and Climate Change: Perceptions of Key Policy Actors in Canada

This article examines factors that predict perceptions of risk associated with global climate change. The research focuses on the perceptions of those associated with climate change policy making in the prairie region of Canada. The data are from an online survey ( n = 851) of those policy actors. The analysis integrates several dominant approaches to the study of risk perception: psychometric approaches that examine the effects of cognitive structure; demographic assessments that examine, for example, differences in perception based on gender or family status; and political approaches that suggest that one's position in the policy process may affect his or her perceived risk. Attitudes toward climate change are to a degree predicted by all of these factors, but only when indirect effects are observed. Sociodemographic characteristics have little direct effect on perceived risk, but do affect general beliefs that affect risk perceptions. Perceived risk is related more strongly to these general beliefs or world views than to more specific beliefs about the effects of climate change on weather patterns. Position within the policy process also contributes to our understanding of perceptions, with industry and governmental actors demonstrating similar attitudes, which contrast with environmental groups and university researchers.     

Cyber Risk Management for Critical Infrastructure: A Risk Analysis Model and Three Case Studies

Managing cyber security in an organization involves allocating the protection budget across a spectrum of possible options. This requires assessing the benefits and the costs of these options. The risk analyses presented here are statistical when relevant data are available, and system‐based for high‐consequence events that have not happened yet. This article presents, first, a general probabilistic risk analysis framework for cyber security in an organization to be specified. It then describes three examples of forward‐looking analyses motivated by recent cyber attacks. The first one is the statistical analysis of an actual database, extended at the upper end of the loss distribution by a Bayesian analysis of possible, high‐consequence attack scenarios that may happen in the future. The second is a systems analysis of cyber risks for a smart, connected electric grid, showing that there is an optimal level of connectivity. The third is an analysis of sequential decisions to upgrade the software of an existing cyber security system or to adopt a new one to stay ahead of adversaries trying to find their way in. The results are distributions of losses to cyber attacks, with and without some considered countermeasures in support of risk management decisions based both on past data and anticipated incidents.     

Heuristic-Systematic Information Processing and Risk Judgment

The heuristic-systematic information processing model (HSM) holds that individuals will use one or both of these modes of information processing when attempting to evaluate information in order to arrive at a judgment. Systematic processing is defined by effortful scrutiny and comparison of information, whereas heuristic processing is defined by the use of cues to arrive more easily at a judgment. Antecedents to the two processing modes include information sufficiency, motivation, and self-efficacy. Structural equation modeling is used to examine competing configuration of this model and to evaluate the model as appropriate for predicting risk judgment. The model also is evaluated across three groups that vary with respect to their level of concern. These analyses are executed within a case study involving an epidemiological investigation of a suspected cancer cluster. The analysis confirms the HSM's theoretically proposed structure and shows it to be a useful vehicle for evaluating risk judgment. In the overall analysis, antecedent variables generally function as specified by theory. Systematic processing is predicted by greater motivation. Heuristic processing is predicted by information sufficiency. Self-efficacy is a significant predictor of both processing modes. And heuristic processing is shown to be associated with judgment of less risk. However, when the analysis is contrasted across three groups (those concerned about cancer, not concerned and uncertain) it is shown that the model is significantly more robust for the uncertain group. This finding may have implications for the use of the HSM in risk research specifically, and in field research generally.