Uncertainty and assessment of the issues posed by urgent climate change. An editorial comment

Climate change raises a number of difficult issues concerning the management of scientific uncertainty. Urgent decisions seem to call for quantified probability statements as the basis of rational policy-making. Yet the answers to many important questions such as the likely rate of sea level rise are not easily quantified, and the utilization of any estimates based on ‘collective subjective probability’ necessarily depends on value-laden judgments about burden-of-proof and the distribution of risk. We suggest that there is a need for a new form of risk assessment that is based in, but not limited to, the scientific community, in which rapid but credible processes address the critical questions that we are now facing.     

Key themes in the Working Group II contribution to the Intergovernmental Panel on Climate Change 5th assessment report

Assessments conducted by the Intergovernmental Panel on Climate Change (IPCC) are significant undertakings that require input from experts and practitioners in multiple scientific disciplines, integrating local to international information across spatial and temporal scales. An IPCC report is a unique collaboration between the scientific community and policymakers, with governments (through their Focal Points) providing guidance and input to the scientists conducting an assessment at several stages during the process. This commentary reviews the IPCC mandate and process; summarizes key themes to be addressed in the Working Group II contribution to the 5th assessment report; discusses challenges for the WGII report when assessing qualitative literature, incorporating local knowledge, and identifying particularly vulnerable groups; and touches on the expertise and commitment of the WGII authors. Active engagement of the wider scientific community in IPCC assessments through publication and review will enhance their relevance to decision- and policy-makers.     

Linking global and local scales: designing dynamic assessment and management processes

This paper identifies challenges inherent in addressing multi-scale environmental problems, and outlines tentative guidelines for addressing such challenges and linking science and policy across scales. The study and practice of environmental assessment and management increasingly recognize the importance of scale and cross-scale dynamics in understanding and addressing global environmental change. These ongoing efforts, however, lack a systematic way of thinking about and addressing the challenges involved in integrating science and policy across multiple scales, for example, in the design of policy-relevant, scientific assessments of problems such as climate change. These challenges include matching scales of biogeophysical systems with scales of management systems, avoiding scale discordance (matching the scale of the assessment with the scale of management), and accounting for cross-scale dynamics. In this paper we propose tentative guidelines for meeting such challenges for both assessors and decision-makers: (1) utilize boundary organizations — institutions which serve to mediate between scientists and decision-makers, and between these actors at different scales; (2) utilize scale-dependent comparative advantages — coordinating the allocation of resources, technical expertise, and decision-making authority to best capitalize on scale-specific capabilities; and (3) employ adaptive assessment and management strategies — constructing long-term, iterative, experiment-based processes of integrated assessment and management.     

Global models meet global policy: How can global and regional modellers connect with environmental policy makers? What has hindered them? What has helped?

Global modelling has developed over the last two decades largely because of the needs of policymaking, yet it has not yet realized its full potential in assisting policymaking. While the first wave of global models in the 1970s had a clear influence on policy discourse, these models were eventually undermined by attacks on their scientific underpinning. The second wave of global models in the 1990s had a stronger scientific footing than the first wave because they were built on a much larger base of knowledge about the global system. Although the improved scientific credibility of global models has increased their use in policymaking, a more subtle yet important factor has been the direct contact of global model developers with policymakers. Taking an example from the field of climate policy, a global modelling team has conducted formal workshops with a group of international climate policymakers with the aim to increase the relevance of modeling activities to policy issues. This interaction has inspired policyrelevant uses of a global model (IMAGE 2) and spawned the development of a new policy concept ‘Safe Emission Corridors’, which has been discussed in the frame of international climate negotiations. A preliminary conclusion is that both improved scientific credibility and improved interaction between modelers and policymakers are critical ingredients for enhancing the policy-relevance of global models.     

Benchmarking sustainability in cities: The role of indicators and future scenarios

Scenarios are a useful tool to help think about and visualise the future and, as such, are utilised by many policymakers and practitioners. Future scenarios have not been used to explore the urban context in much depth, yet have the potential to provide valuable insights into the robustness of decisions being made today in the name of sustainability. As part of a major research project entitled Urban Futures, a toolkit has been developed in the UK to facilitate the use of scenarios in any urban context and at any scale relevant to that context. The toolkit comprises two key components, namely, (i) a series of indicators comprising both generic and topic area-specific indicators (e.g., air quality, biodiversity, density, water) that measure sustainability performance and (ii) a list of characteristics (i.e., 1–2-sentence statements about a feature, issue or small set of issues) that describe four future scenarios. In combination, these two components enable us to measure the performance of any given sustainability indicator, and establish the relative sensitivity or vulnerability of that indicator to the different future scenarios. An important aspect of the methodology underpinning the toolkit is that it is flexible enough to incorporate new scenarios, characteristics and indicators, thereby allowing the long-term performance of our urban environments to be considered in the broadest possible sense.     

Precaution and proportionality in the management of global environmental change

The precautionary principle is a mandate to tread cautiously when managing novel threats to the environment or human health. A major obstacle when applying the principle at the international level is disagreement about how precautionary efforts should be constrained to ensure that policy costs are proportional to the attained level of protection. Proportionality is an unresolved question when preliminary evidence precludes decision-makers from assigning probabilities over future events. The paper suggests practical analytical tools for communicating ex ante trade-offs when probabilities are unavailable. The tools could be used to facilitate discussion and compromise when implementing precautionary decisions in international settings where cooperation is important. The approach is demonstrated in an application to climate policy that uses the integrated assessment model DICE (Nordhaus, 2008). The paper also situates the task of precautionary decision-making within the broader context of implementing a precautionary response at the international level.     

Multiple scales and regulatory gaps in environmental change: the case of salmon aquaculture

The significance of multiple scales within processes of global environmental change has attracted increasing attention. Yet the fundamental tasks of linking multiple levels at which regulatory decisions are required to multiple scales of impacts have only recently been identified. This paper addresses the importance of attention to multiple scales in regulatory decisions, how those decisions should link together across scales of governance or decision-making, and how mismatches among scales of impact and scales of regulation can lead to regulatory gaps and breakdowns. This paper begins by presenting a definition of a cross-scale regulatory problem, building on the concept of an externality. It argues that virtually all-significant environmental regulatory problems involve multiple scales at which decisions are required, and that coordination of these decisions is one of the major issues in regulatory design. The paper provides a generalization of what is needed for effective cross-scale regulation, and then discusses the example of salmon aquaculture in British Columbia to illustrate these points. In our view, gaps and mismatches in the regulatory framework across institutional scales appear to contribute to social controversy over salmon aquaculture. These gaps include (i) the site-by-site orientation of the current regulatory process, even though the major impacts are cumulative, and regional in significance, and (ii) the degree to which limitations on the extent of salmon aquaculture are implemented by local governments, even though provincial and federal governments have the mandate and expertise to address these questions.     

Knowledge gaps and climate adaptation policy: a comparative analysis of six Latin American countries

ABSTRACT

This article identifies and analyzes some of the main knowledge gaps that affect the development of climate adaptation policies in the Latin American context. It is based on a comparative analysis of online survey results conducted among government officials working on climate adaptation in six countries of the region: Argentina, Brazil, Chile, Costa Rica, Paraguay and Uruguay. The article addresses four key issues. First, it identifies some of the critical knowledge deficits (missing or incomplete information) that affect climate adaptation policy making and implementation. Second, it addresses the obstacles and difficulties facing collaborative processes of knowledge production (co-production) between scientists and public policy actors. Third, it analyzes factors affecting knowledge uptake and use by policymakers. Finally, it identifies some of the main knowledge deficits specifically affecting the monitoring and assessment of climate adaptation policies and measures. Overall, the article provides a diagnosis of the main knowledge gaps facing climate adaptation policy in the Latin American countries studied. The results of this diagnosis can serve as input for a research and action agenda aiming to strength the interaction between science and policy on climate adaptation in Latin American countries.

Key policy insights

• The countries covered by the study suffer strong knowledge deficits related to the design, implementation and evaluation of adaptation policy.

• Collaborative modes of knowledge production in the field of climate adaptation do not tend to sustain over time. Climate change co-production processes tend to be project based, linked to specific initiatives rather than to institutionalized long-term policymaking or planning processes.

• The fragmentation and lack of integration of the knowledge available on the different aspects of climate adaptation issues deeply affect their usability in policy processes.

• Weak state capabilities to co-produce, manage and use knowledge in the policy process constitute a main barrier affecting the science-policy interface on climate adaptation issues.

     

Data and processes linking vulnerability assessment to adaptation decision-making on climate change in Norway

The article focuses on the use of climate change vulnerability assessments in a local decision-making context, with particular reference to recent studies in Norway. We focus on two aspects of vulnerability assessments that we see as key to local decision-making: first, the information generated through the assessments themselves, and second, the institutional linkages to local level decision-making processes. Different research approaches generate different types of data. This is rarely made explicit, yet it has important implications for decision-making. In addressing these challenges we propose a dialectic approach based on exchange, rather than integration of data from different approaches. The focus is on process over product, and on the need for anchoring vulnerability assessments in local decision-making processes. In conclusion, we argue that there is unlikely to be one single ‘correct’ assessment tool or indicator model to make vulnerability assessments matter at a local level.     

Operationalizing longitudinal approaches to climate change vulnerability assessment

The past decade has seen a proliferation of community-scale climate change vulnerability assessments globally. Much of this work has employed frameworks informed by scholarship in the vulnerability field, which draws upon interviews with community members to identify and characterize climatic risks and adaptive responses. This scholarship has developed a baseline understanding of vulnerability in specific places and industries at particular times. However, given the dynamic nature of vulnerability new methodologies are needed to generate insights on how climate change is experienced and responded to over time. Longitudinal approaches have long been used in sociology and the health sciences to capture the dynamism of human processes, but their penetration into vulnerability research has been limited. In this article, we describe the application of two longitudinal approaches, cohort and trend studies, in climate change vulnerability assessment by analyzing three case studies from the Arctic where the authors applied these approaches. These case studies highlight how longitudinal approaches can be operationalized to capture the dynamism of vulnerability by identifying climate anomalies and trends, and how adaptations develop over time, including insights on themes such as social learning and adaptive pathways.     

Citizen preferences on private-public co-regulation in environmental governance: Evidence from Switzerland

Environmental policy is touching on ever more aspects of corporate and individual behavior, and there is much debate over what combinations of top-down (government-imposed) and bottom-up (voluntary private sector) measures to use. In democratic societies, citizens’ preferences over such combinations are crucial because they shape the political mandates based on which policymakers act. We argue that policy designs that involve private-public co-regulation receive more citizen support if they are based on inclusive decision-making, use strong transparency and monitoring mechanisms, and include a trigger for government intervention in case of ineffectiveness. Survey experiments in Switzerland (N = 1941) provide strong support for these arguments. Our research demonstrates that differences in co-regulation design have major implications for public support. Another key finding is that there seems to be a contradiction between inclusiveness and democratic accountability for policy outcomes. The findings are surprisingly consistent across two very different green economy issues we focus on empirically (decarbonization of finance, pesticides). This suggests that our study design offers a useful template for research that explores public opinion on green economy policy designs for other issues and in other countries.     

基于IEC 62305-2的雷电灾害风险管理系统设计

介绍了一种基于国际标准IEC62305-2雷击灾害风险评估方法的雷击灾害风险管理系统的功能和结构。系统基于基础数据库,实现雷电灾害信息的检索与查询、数据统计以及输出,可为防灾减灾提供依据。整个系统主要由评价分析模块、基础数据库模块、决策支持模块和输出模块等组成。风险评估分析模块具有雷灾风险识别、风险评价、风险等级划分功能。决策支持模块能够快速、准确提供雷电灾害的评价结果,提出灾害防护措施,计算灾害补偿的范围和数额,以及对防灾工程和拟建防灾工程进行评价。     

Strategies to adapt to an uncertain climate change

Many decisions concerning long-lived investments already need to take into account climate change. But doing so is not easy for at least two reasons. First, due to the rate of climate change, new infrastructure will have to be able to cope with a large range of changing climate conditions, which will make design more difficult and construction more expensive. Second, uncertainty in future climate makes it impossible to directly use the output of a single climate model as an input for infrastructure design, and there are good reasons to think that the needed climate information will not be available soon. Instead of optimizing based on the climate conditions projected by models, therefore, future infrastructure should be made more robust to possible changes in climate conditions. This aim implies that users of climate information must also change their practices and decision-making frameworks, for instance by adapting the uncertainty-management methods they currently apply to exchange rates or R&D outcomes. Five methods are examined: (i) selecting “no-regret” strategies that yield benefits even in absence of climate change; (ii) favouring reversible and flexible options; (iii) buying “safety margins” in new investments; (iv) promoting soft adaptation strategies, including long-term prospective; and (v) reducing decision time horizons. Moreover, it is essential to consider both negative and positive side-effects and externalities of adaptation measures. Adaptation–mitigation interactions also call for integrated design and assessment of adaptation and mitigation policies, which are often developed by distinct communities.     

Communicating climate change risks in a skeptical world

The Intergovernmental Panel on Climate Change (IPCC) has been extraordinarily successful in the task of knowledge synthesis and risk assessment. However, the strong scientific consensus on the detection, attribution, and risks of climate change stands in stark contrast to widespread confusion, complacency and denial among policymakers and the public. Risk communication is now a major bottleneck preventing science from playing an appropriate role in climate policy. Here I argue that the ability of the IPCC to fulfill its mission can be enhanced through better understanding of the mental models of the audiences it seeks to reach, then altering the presentation and communication of results accordingly. Few policymakers are trained in science, and public understanding of basic facts about climate change is poor. But the problem is deeper. Our mental models lead to persistent errors and biases in complex dynamic systems like the climate and economy. Where the consequences of our actions spill out across space and time, our mental models have narrow boundaries and focus on the short term. Where the dynamics of complex systems are conditioned by multiple feedbacks, time delays, accumulations and nonlinearities, we have difficulty recognizing and understanding feedback processes, underestimate time delays, and do not understand basic principles of accumulation or how nonlinearities can create regime shifts. These problems arise not only among laypeople but also among highly educated elites with significant training in science. They arise not only in complex systems like the climate but also in familiar contexts such as filling a bathtub. Therefore they cannot be remedied merely by providing more information about the climate, but require different modes of communication, including experiential learning environments such as interactive simulations.     

Multilevel risk governance and urban adaptation policy

Despite a flurry of activity in cities on climate change and growing interest in the research community, climate policy at city-scale remains fragmented and basic tools to facilitate good decision-making are lacking. This paper draws on an interdisciplinary literature review to establish a multilevel risk governance conceptual framework. It situates the local adaptation policy challenge and action within this to explore a range of institutional questions associated with strengthening local adaptation and related functions of local government. It highlights the value of institutional design to include analytic-deliberative practice, focusing on one possible key tool to support local decision-making—that of boundary organizations to facilitate local science-policy assessment. After exploring a number of examples of boundary organisations in place today, the authors conclude that a number of institutional models are valid. A common feature across the different approaches is the establishment of a science-policy competence through active deliberation and shared analysis engaging experts and decision-makers in an iterative exchange of information. Important features that vary include the geographic scope of operation and the origin of funding, the level and form of engagement of different actors, and the relationship with “producers” of scientific information. National and sub-national (regional) governments may play a key role to provide financial and technical assistance to support the creation of such boundary organizations with an explicit mandate to operate at local levels; in turn, in a number of instances boundary organizations have been shown to be able to facilitate local partnerships, engagement and decision-making on adaptation. While the agenda for multi-level governance of climate change is inevitably much broader than this, first steps by national governments to work with sub-national governments, urban authorities and other stakeholders to advance capacity in this area could be an important step for local adaptation policy agenda.     

Unexploited opportunities in understanding liveable and biodiverse cities. A review on urban biodiversity perception and valuation

Many researchers and policymakers from various disciplines highlight the role of urban biodiversity in delivering ecosystem services to enhance human wellbeing in a rapidly urbanising world. This suggests powerful synergies between approaches that are often disciplinarily separated, aiming either at human wellbeing or biodiversity conservation. Strategies towards liveable and biodiverse cities would gain support from insights into the people-biodiversity interface in cities. Yet, the question of which scale of biodiversity (from ecosystems to genes) benefits urban people in general and different socio-cultural groups in particular, remains largely open. To assess the current scientific knowledge as well as potential for further research, we systematically reviewed literature on people’s perception and valuation of urban biodiversity (200 studies). We also quantified the outcomes of studies in terms of the effects of biodiversity on valuation for studies that addressed biodiversity valuation below the ecosystem scale. We found that the current literature is critically biased in four ways. (1) Most studies cover temperate climates, while regions with the most pronounced urban growth are underrepresented. (2) Studies focus on urban forests and parks while important informal greenspaces are largely neglected. (3) Biodiversity is mostly addressed at the ecosystem scale (habitat or land-use types) while diversity at the species community or gene scale—key issues in biodiversity conservation—is covered to a much lesser extent. Most studies below the ecosystem scale show positive biodiversity effects, but universal patterns are not apparent due to the scarcity and low comparability of research. (4) Almost no studies consider the cultural diversity of urban residents by systematically targeting people from different socio-economic and cultural backgrounds or specific age groups. Our review reveals critical knowledge gaps about the people-biodiversity interface in cities, both in approaching cultural and biological diversity (‘biocultural diversity’). This shows unexploited opportunities and future directions in linking usually separated strategies on enhancing human wellbeing and biodiversity conservation in sustainable cities.     

Seasonal and Inter-Annual Climate Forecasting: The New Tool for Increasing Preparedness to Climate Variability and Change In Agricultural Planning And Operations

Climate variability and change affects individuals and societies. Within agricultural systems, seasonal climate forecasting can increase preparedness and lead to better social, economic and environmental outcomes. However, climate forecasting is not the panacea to all our problems in agriculture. Instead, it is one of many risk management tools that sometimes play an important role in decision-making. Understanding when, where and how to use this tool is a complex and multi-dimensional problem. To do this effectively, we suggest a participatory, cross-disciplinary research approach that brings together institutions (partnerships), disciplines (e.g., climate science, agricultural systems science, rural sociology and many other disciplines) and people (scientist, policy makers and direct beneficiaries) as equal partners to reap the benefits from climate knowledge. Climate science can provide insights into climatic processes, agricultural systems science can translate these insights into management options and rural sociology can help determine the options that are most feasible or desirable from a socio-economic perspective. Any scientific breakthroughs in climate forecasting capabilities are much more likely to have an immediate and positive impact if they are conducted and delivered within such a framework. While knowledge and understanding of the socio-economic circumstances is important and must be taken into account, the general approach of integrated systems science is generic and applicable in developed as well as in developing countries. Examples of decisions aided by simulation output ranges from tactical crop management options, commodity marketing to policy decisions about future land use. We also highlight the need to better understand temporal- and spatial-scale variability and argue that only a probabilistic approach to outcome dissemination should be considered. We demonstrated how knowledge of climatic variability (CV), can lead to better decisions in agriculture, regardless of geographical location and socio-economic conditions.     

Is robustness really robust? How different definitions of robustness impact decision-making under climate change

Robust decision-making is being increasingly used to support environmental resources decisions and policy analysis under changing climate and society. In this context, a robust decision is a decision that is as much as possible insensitive to a large degree of uncertainty and ensures certain performance across multiple plausible futures. Yet, the concept of robustness is neither unique nor static. Multiple robustness metrics, such as maximin, optimism-pessimism, max regret, have been proposed in the literature, reflecting diverse optimistic/pessimistic attitudes by the decision maker. Further, these attitudes can evolve in time as a response to sequences of favorable (or adverse) events, inducing possible dynamic changes in the robustness metrics. In this paper, we explore the impact of alternative definitions of robustness and their evolution in time for a case of water resources system management under changing climate. We study the decisions of the Lake Como operator, who is called to regulate the lake by balancing irrigation supply and flood control, under an ensemble of climate change scenarios. Results show a considerable variability in the system performance across multiple robustness metrics. In fact, the mis-definition of the actual decision maker’s attitude biases the simulation of its future decisions and produces a general underestimation of the system performance. The analysis of the dynamic evolution of the decision maker’s preferences further confirms the potentially strong impact of changing robustness definition on the decision-making outcomes. Climate change impact assessment studies should therefore include the definition of robustness among the uncertain parameters of the problem in order to analyze future human decisions under uncertainty.     

Limitations of integrated assessment models of climate change

The integrated assessment models (IAMs) that economists use to analyze the expected costs and benefits of climate policies frequently suggest that the “optimal” policy is to go slowly and to do relatively little in the near term to reduce greenhouse gas emissions. We trace this finding to the contestable assumptions and limitations of IAMs. For example, they typically discount future impacts from climate change at relatively high rates. This practice may be appropriate for short-term financial decisions but its extension to intergenerational environmental issues rests on several empirically and philosophically controversial hypotheses. IAMs also assign monetary values to the benefits of climate mitigation on the basis of incomplete information and sometimes speculative judgments concerning the monetary worth of human lives and ecosystems, while downplaying scientific uncertainty about the extent of expected damages. In addition, IAMs may exaggerate mitigation costs by failing to reflect the socially determined, path-dependent nature of technical change and ignoring the potential savings from reduced energy utilization and other opportunities for innovation. A better approach to climate policy, drawing on recent research on the economics of uncertainty, would reframe the problem as buying insurance against catastrophic, low-probability events. Policy decisions should be based on a judgment concerning the maximum tolerable increase in temperature and/or carbon dioxide levels given the state of scientific understanding. The appropriate role for economists would then be to determine the least-cost global strategy to achieve that target. While this remains a demanding and complex problem, it is far more tractable and epistemically defensible than the cost-benefit comparisons attempted by most IAMs.     

Some thoughts on the value added from a new round of climate change damage estimates

This paper offers some thoughts on the value added of new economic estimates of climate change damages. We begin with a warning to beware of analyses that are so narrow that they miss a good deal of the important economic ramifications of the full suite of manifestations of climate change. Our second set of comments focuses attention on one of the most visible products of integrated assessment modeling—estimates of the social cost of carbon which we take as one example of aggregate economic indicators that have been designed to summarize climate risk in policy deliberations. Our point is that these estimates are so sensitive to a wide range of parameters that improved understanding of economic damages across many (if not all) climate sensitive sectors may offer only limited value added. Having cast some doubt on the ability of improved estimates of economic damages to increase the value of economic damage estimates in integrated assessment modeling designed to inform climate policy deliberations, we offer an alternative approach—describing implicitly a research agenda that could (a) effectively inform mitigation decisions while, at the same time, (b) providing economic estimates for aggregate indicators like the social cost of carbon.