Learning from integrated assessment of climate change

The objective of integrated assessment of climate change is to put available knowledge together in order to evaluate what has been learned, policy implications, and research needs. This paper summarizes insights gained from five years of integrated assessment activity at Carnegie Mellon. After an introduction, in Section 2 we ask: who are the climate decision makers? We conclude that they are a diffuse and often divergent group spread all over the world whose decisions are primarily driven by local non-climate considerations. Insights are illustrated with results from the ICAM-2 model. In Section 3 we ask: what is the climate problem? In addition to the conventional answer, we note that in a democracy the problem is whatever voters and their elected representatives think it is. Results from studies of public understanding are reported. Several other specific issues that define the problem, including the treatment of aerosols and alternative indices for comparing greenhouse gases, are discussed. In Section 4 we discuss studies of climate impacts, focusing on coastal zones, the terrestrial biosphere and human health. Particular attention is placed on the roles of adaptation, value change, and technological innovation. In Section 5 selected policy issues are discussed. We conclude by noting that equity has received too little attention in past work. We argue that many conventional tools for policy analysis are not adequate to deal with climate problems. Values that change, and mixed levels of uncertainty, pose particularly important challenges for the future.     

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.     

气候变化综合评估模型的损失函数研究进展

该研究从综合评估模型(IAM)的模型耦合视角出发,介绍了当前损失函数的研究进展,主要从损失函数的构建方法、损失函数与IAM气候模块和经济模块的耦合以及IAM与气候模式的耦合角度分析了损失函数的耦合功能及其存在的科学问题,探讨了损失函数的改进方向。通过文献梳理发现,损失函数的构建方法上,主要采用专家判断法、元分析法和统计学方法,但各有优缺点;与气候模式的耦合功能上,损失函数多以温升为气候变化因素,降水等气候变化信息无法表达,且由全球尺度的年平均值进行标定,不能体现区域的差异和季节的变化,无法直接描述极端气候事件造成的巨大损失;与经济模块的耦合功能上,基于生产部门的损失函数缺乏间接损失评估功能,缺乏对经济增长的动态影响机制。针对上述IAM中气候变化对经济影响的反馈机制的不足,需重点从细化区域气候变化因素影响和细分经济产业部门两个方向重构损失函数,紧密连接气候模式与经济模块,全面评估气候变化经济损失,并需要从技术上解决损失函数在耦合经济模块与气候模式时出现的时空尺度不匹配问题,最终为IAM与气候模式甚至地球系统模式的耦合提供重要的解决方案。     

The benefits of climate change mitigation in integrated assessment models: the role of the carbon cycle and climate component

Integrated Assessment Models (IAMs) are an important tool to compare the costs and benefits of different climate policies. Recently, attention has been given to the effect of different discounting methods and damage estimates on the results of IAMs. One aspect to which little attention has been paid is how the representation of the climate system may affect the estimated benefits of mitigation action. In that respect, we analyse several well-known IAMs, including the newest versions of FUND, DICE and PAGE. Given the role of IAMs in integrating information from different disciplines, they should ideally represent both best estimates and the ranges of anticipated climate system and carbon cycle behaviour (as e.g. synthesised in the IPCC Assessment reports). We show that in the longer term, beyond 2100, most IAM parameterisations of the carbon cycle imply lower CO₂ concentrations compared to a model that captures IPCC AR4 knowledge more closely, e.g. the carbon-cycle climate model MAGICC6. With regard to the climate component, some IAMs lead to much lower benefits of mitigation than MAGICC6. The most important reason for the underestimation of the benefits of mitigation is the failure in capturing climate dynamics correctly, which implies this could be a potential development area to focus on.     

Context and climate change: an integrated assessment for Barrow, Alaska

An intensive approach to Barrow, Alaska’s adaptations to climate change and variability during recent decades suggests reconsideration of the interconnected roles of science, policy, and decision-making structures. First, profound uncertainties are inherent in unique interactions among the many natural and human factors affecting Barrow’s vulnerability. Science cannot significantly reduce these uncertainties through extensive approaches, but intensive approaches can reconstruct and update local trends, clarify the underlying dynamics, and harvest experience for policy purposes. Second, sound policies to reduce Barrow’s vulnerability to coastal erosion and flooding must incorporate these profound uncertainties and the multiple values of the community. Minimizing vulnerability to climate change is only one of the community’s interests, and must compete with other interests for limited time, attention, funds and other resources. Third, the community itself is in the best position to understand its own context, to decide on sound policies, and to take responsibility for those decisions. In short, local context matters in science, policy, and decision-making structures for adaptation to climate change and variability. Overall, cognitive constraints may be the most important human dimension of climate change. Factoring the global problem into more tractable local problems would make the most of our cognitive capacity.     

On the added value of regional climate modeling in climate change assessment

Regional climate models represent a promising tool to assess the regional dimension of future climate change and are widely used in climate impact research. While the added value of regional climate models has been highlighted with respect to a better representation of land-surface interactions and atmospheric processes, it is still unclear whether radiative heating implies predictability down to the typical scale of a regional climate model. As a quantitative assessment, we apply an optimal statistical filter to compare the coherence between observed and simulated patterns of Mediterranean climate change from a global and a regional climate model. It is found that the regional climate model has indeed an added value in the detection of regional climate change, contrary to former assumptions. The optimal filter may also serve as a weighting factor in multi-model averaging.     

The oil industry and climate change: strategies and ethical dilemmas

This paper explores the different climate change strategies chosen by three major multinational oil corporations: ExxonMobil, TotalFinaElf and BP Amoco. They are referred to, as the ‘fight against emission constraints,’ ‘wait and see,’ and ‘proactive’ strategies, respectively. The justifications given to support these strategies are identified. They cover the business, scientific, political, economic, technological and social dimensions. In a business ethics framework, the issue of climate change brings forth an ethical dilemma for the oil industry, in the form of a tension between profits and CO₂ emissions. The strategies are analysed as three attitudes towards this dilemma: (i) placing priority on the business consequences while weakening the perception that anthropogenic greenhouse gas emissions are causing climate change; (ii) avoiding responsibility; and (iii) placing priority on the need for a modification of the business process while limiting the negative effect in terms of business consequences. In conclusion, we propose that beyond the ethical issues proper to climate change itself, additional ethical issues are raised if society at large is instrumentalised by an industry in its search for profit. Publicly gauging and valorising the ethical commitment of a corporation appear as ways of inducing more collaborative and proactive attitudes by business actors.     

Role of energy efficiency in climate change mitigation policy for India: assessment of co-benefits and opportunities within an integrated assessment modeling framework

Addressing the challenges of global warming requires interventions on both the energy supply and demand side. With the supply side responses being thoroughly discussed in the literature, our paper focuses on analyzing the role of end use efficiency improvements for Indian climate change mitigation policy and the associated co-benefits, within the integrated assessment modeling framework of Global Change Assessment Model (GCAM). Six scenarios are analyzed here in total- one no climate policy and two climate policy cases, and within each of these one scenario with reference end use energy technology assumptions and another with advance end use energy technology assumptions has been analyzed. The paper has some important insights. Final energy demand and emissions in India are significantly reduced with energy efficiency improvements, and the role of this policy is important especially for the building and transportation sector under both reference and climate policy scenarios. Though energy efficiency policy should be an integral part of climate policy, by itself it is not sufficient for achieving mitigation targets, and a climate policy is necessary for achieving mitigation goals. There are significant co-benefits of energy efficiency improvements. Energy security for India is improved with reduced oil, coal and gas imports. Significant reduction in local pollutant gases is found which is important for local health concerns. Capital investment requirement for Indian electricity generation is reduced, more so for the climate policy scenarios, and finally there are significant savings in terms of reduced abatement cost for meeting climate change mitigation goals.     

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.     

The bias of integrated assessment models that ignore climate catastrophes

Climate scientists currently predict there is a small but real possibility that climate change will lead to civilization threatening catastrophic events. Martin Weitzman has used this evidence along with his controversial “Dismal Theorem” to argue that integrated assessment models of climate change cannot be used to determine an optimal price for carbon dioxide. In this paper, I provide additional support for Weitzman’s conclusions by running numerical simulations to estimate risk premiums toward climate catastrophes. Compared to the assumptions found in most integrated assessment models, I incorporate into the model a more realistic range of uncertainty for both climate catastrophes and societal risk aversion. The resulting range of risk premiums indicates that the conclusions drawn from integrated assessment models that do not incorporate the potential for climate catastrophes are too imprecise to support any particular policy recommendation. The analysis of this paper is more straightforward and less technical than Weitzman’s, and therefore the conclusions should be accessible to a wider audience.     

Integrated assessment of changes in flooding probabilities due to climate change

An approach to considering changes in flooding probability in the integrated assessment of climate change is introduced. A reduced-form hydrological model for flood prediction and a downscaling approach suitable for integrated assessment modeling are presented. Based on these components, the fraction of world population living in river basins affected by changes in flooding probability in the course of climate change is determined. This is then used as a climate impact response function in order to derive emission corridors limiting the population affected. This approach illustrates the consideration of probabilistic impacts within the framework of the tolerable windows approach. Based on the change in global mean temperature, as calculated by the simple climate models used in integrated assessment, spatially resolved changes in climatic variables are determined using pattern scaling, while natural variability in these variables is considered using twentieth century deviations from the climatology. Driven by the spatially resolved climate change, the hydrological model then aggregates these changes to river basin scale. The hydrological model is subjected to a sensitivity analysis with regard to the water balance, and the uncertainty arising through the different projections of changes in mean climate by differing climate models is considered by presenting results based on different models. The results suggest that up to 20% of world population live in river basins that might inevitably be affected by increased flood events in the course of global warming, depending on the climate model used to estimate the regional distribution of changes in climate. This article is dedicated to the memory of the late Gerhard Petschel-Held. He was an inspiring colleague, as well as a good friend. His sudden departure leaves me deeply shocked, and I am sure he will sorely be missed by all who had the pleasure of meeting him. Thomas Kleinen     

The benefits of quantifying climate model uncertainty in climate change impacts assessment: an example with heat-related mortality change estimates

The majority of climate change impacts assessments account for climate change uncertainty by adopting the scenario-based approach. This typically involves assessing the impacts for a small number of emissions scenarios but neglecting the role of climate model physics uncertainty. Perturbed physics ensemble (PPE) climate simulations offer a unique opportunity to explore this uncertainty. Furthermore, PPEs mean it is now possible to make risk-based impacts estimates because they allow for a range of estimates to be presented to decision-makers, which spans the range of climate model physics uncertainty inherent from a given climate model and emissions scenario, due to uncertainty associated with the understanding of physical processes in the climate model. This is generally not possible with the scenario-based approach. Here, we present the first application of a PPE to estimate the impact of climate change on heat-related mortality. By using the estimated impacts of climate change on heat-related mortality in six cities, we demonstrate the benefits of quantifying climate model physics uncertainty in climate change impacts assessment over the more common scenario-based approach. We also show that the impacts are more sensitive to climate model physics uncertainty than they are to emissions scenario uncertainty, and least sensitive to whether the climate change projections are from a global climate model or a regional climate model. The results demonstrate the importance of presenting model uncertainties in climate change impacts assessments if the impacts are to be placed within a climate risk management framework.     

Expert assessment of vulnerability of permafrost carbon to climate change

Approximately 1700 Pg of soil carbon (C) are stored in the northern circumpolar permafrost zone, more than twice as much C than in the atmosphere. The overall amount, rate, and form of C released to the atmosphere in a warmer world will influence the strength of the permafrost C feedback to climate change. We used a survey to quantify variability in the perception of the vulnerability of permafrost C to climate change. Experts were asked to provide quantitative estimates of permafrost change in response to four scenarios of warming. For the highest warming scenario (RCP 8.5), experts hypothesized that C release from permafrost zone soils could be 19–45 Pg C by 2040, 162–288 Pg C by 2100, and 381–616 Pg C by 2300 in CO₂ equivalent using 100-year CH₄ global warming potential (GWP). These values become 50 % larger using 20-year CH₄ GWP, with a third to a half of expected climate forcing coming from CH₄ even though CH₄ was only 2.3 % of the expected C release. Experts projected that two-thirds of this release could be avoided under the lowest warming scenario (RCP 2.6). These results highlight the potential risk from permafrost thaw and serve to frame a hypothesis about the magnitude of this feedback to climate change. However, the level of emissions proposed here are unlikely to overshadow the impact of fossil fuel burning, which will continue to be the main source of C emissions and climate forcing.     

Confronting the challenge of integrated assessment of climate adaptation: a conceptual framework

Key limitations of integrated assessment models (IAMs) are their highly stylized and aggregated representation of climate damages and associated economic responses, as well as the omission of specific investments related to climate change adaptation. This paper proposes a framework for modeling climate impacts and adaptation that clarifies the relevant research issues and provides a template for making improvements. We identify five desirable characteristics of an ideal integrated assessment modeling platform, which we elaborate into a conceptual model that distinguishes three different classes of adaptation-related activities. Based on these elements we specify an impacts- and adaptation-centric IAM, whose optimality conditions are used to highlight the types of functional relationships necessary for realistic representations of adaptation-related decisions, the specific mechanisms by which these responses can be incorporated into IAMs, and the ways in which the inclusion of adaptation is likely to affect the simulations’ results.     

A global assessment of the impact of climate change on water scarcity

This paper presents a global scale assessment of the impact of climate change on water scarcity. Patterns of climate change from 21 Global Climate Models (GCMs) under four SRES scenarios are applied to a global hydrological model to estimate water resources across 1339 watersheds. The Water Crowding Index (WCI) and the Water Stress Index (WSI) are used to calculate exposure to increases and decreases in global water scarcity due to climate change. 1.6 (WCI) and 2.4 (WSI) billion people are estimated to be currently living within watersheds exposed to water scarcity. Using the WCI, by 2050 under the A1B scenario, 0.5 to 3.1 billion people are exposed to an increase in water scarcity due to climate change (range across 21 GCMs). This represents a higher upper-estimate than previous assessments because scenarios are constructed from a wider range of GCMs. A substantial proportion of the uncertainty in the global-scale effect of climate change on water scarcity is due to uncertainty in the estimates for South Asia and East Asia. Sensitivity to the WCI and WSI thresholds that define water scarcity can be comparable to the sensitivity to climate change pattern. More of the world will see an increase in exposure to water scarcity than a decrease due to climate change but this is not consistent across all climate change patterns. Additionally, investigation of the effects of a set of prescribed global mean temperature change scenarios show rapid increases in water scarcity due to climate change across many regions of the globe, up to 2 °C, followed by stabilisation to 4 °C.