Assessment Models Of Climate Change Research Articles

What are robust strategies in the face of uncertain climate threshold responses?

We use an integrated assessment model of climate change to analyze how alternative decision-making criteria affect preferred investments into greenhouse gas mitigation, the distribution of outcomes, the robustness of the strategies, and the economic value of information. We define robustness as trading a small decrease in a strategy’s expected performance for a significant increase in a strategy’s performance in the worst cases. Specifically, we modify the Dynamic Integrated model of Climate and the Economy (DICE-07) to include a simple representation of a climate threshold response, parametric uncertainty, structural uncertainty, learning, and different decision-making criteria. Economic analyses of climate change strategies typically adopt the expected utility maximization (EUM) framework. We compare EUM with two decision criteria adopted from the finance literature, namely Limited Degree of Confidence (LDC) and Safety First (SF). Both criteria increase the relative weight of the performance under the worst-case scenarios compared to EUM. We show that the LDC and SF criteria provide a computationally feasible foundation for identifying greenhouse gas mitigation strategies that may prove more robust than those identified by the EUM criterion. More robust strategies show higher near-term investments in emissions abatement. Reducing uncertainty has a higher economic value of information for the LDC and SF decision criteria than for EUM.

Evaluating Uncertain CO2 Abatement over the Very Long Term

Climate change research with the economic methodology of cost–benefit analysis is challenging because of valuation and ethical issues associated with the long delays between CO2 emissions and much of their potential damages, typically of several centuries. The large uncertainties with which climate change impacts are known today and the possibly temporary nature of some envisaged CO2 abatement options exacerbate this challenge. For example, potential leakage of CO2 from geological reservoirs, after this greenhouse gas has been stored artificially underground for climate control reasons, requires an analysis in which the uncertain climatic consequences of leakage are valued over many centuries. We here present a discussion of some of the relevant questions in this context and provide calculations with the top–down energy-environment-economy model DEMETER. Given the long-term features of the climate change conundrum as well as of technologies that can contribute to its solution, we considered it necessary extending DEMETER to cover a period from today until the year 3000, a time span so far hardly investigated with integrated assessment models of climate change.

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.

The economics (or lack thereof) of aerosol geoengineering

Anthropogenic greenhouse gas emissions are changing the Earth's cli- mate and impose substantial risks for current and future generations. What are scientifically sound, economically viable, and ethically defendable strategies to manage these climate risks? Ratified international agreements call for a reduction of greenhouse gas emissions to avoid dangerous anthropogenic interference with the climate system. Recent proposals, however, call for a different approach: to geoengineer climate by injecting aerosol precursors into the stratosphere. Published economic studies typically neglect the risks of aerosol geoengineering due to (i) the potential for a failure to sustain the aerosol forcing and (ii) the negative impacts associated with the aerosol forcing. Here we use a simple integrated assessment model of climate change to analyze potential economic impacts of aerosol geo- engineering strategies over a wide range of uncertain parameters such as climate sensitivity, the economic damages due to climate change, and the economic damages due to aerosol geoengineering forcing. The simplicity of the model provides the

The Social Evaluation of Intergenerational Policies and Its Application to Integrated Assessment Models of Climate Change

Abstract Assessment of climate change policies requires aggregation of costs and benefits over time and across generations, a process ordinarily done through discounting. Choosing the correct discount rate has proved to be controversial and highly consequential. To clarify past analysis and guide future work, we decompose discounting along two dimensions. First, we distinguish discounting by individuals, an empirical matter that determines their behavior in models, and discounting by an outside evaluator, an ethical matter involving the choice of a social welfare function. Second, for each type of discounting, we distinguish it due to pure time preference from that attributable to curvature of the pertinent function: utility functions (of consumption) for individuals and the social welfare function (of utilities) for the evaluator. We apply our analysis to leading integrated assessment models used to evaluate climate policies. We find that past work often confounds different sources of discounting, and we offer suggestions for avoiding these difficulties. Finally, we relate the standard intergenerational framework that combines considerations of efficiency and distribution to more familiar modes of analysis that assess most policies in terms of efficiency, leaving distributive concerns to the tax and transfer system.

Dynamics of the oil transition: Modeling capacity, depletion, and emissions

The global petroleum system is undergoing a shift to substitutes for conventional petroleum (SCPs). The Regional Optimization Model for Emissions from Oil Substitutes, or ROMEO, models this oil transition and its greenhouse gas impacts. ROMEO models the global liquid fuel market in an economic optimization framework, but in contrast to other models it solves each model year sequentially, with investment and production optimized under uncertainty about future prevailing prices or resource quantities. ROMEO includes more hydrocarbon resource types than integrated assessment models of climate change. ROMEO also includes the carbon intensities and costs of production of these resources. We use ROMEO to explore the uncertainty of future costs, emissions, and total fuel production under a number of scenarios. We perform sensitivity analysis on the endowment of conventional petroleum and future carbon taxes. Results show incremental emissions from production of oil substitutes of ≈ 0–30 gigatonnes (Gt) of carbon over the next 50 years (depending on the carbon tax). Also, demand reductions due to the higher cost of SCPs could reduce or eliminate these increases. Calculated emissions are highly sensitive to the endowment of conventional oil and less sensitive to a carbon tax.

Toward an integrated framework derived from a risk-management approach to climate change

Ackerman et al. (2009) criticize optimization applications of integrated assessment models of climate change on several grounds. First, they focus attention on contestable assumptions about the appropriate discount rate. Second, they worry that integrated assessment models base their damage estimates on incomplete information and questionable estimates of the value of human life and/or ecosystem services. Thirdly, they suggest that mitigation costs are systematically overestimated because they ignore technological innovation. So what good is economics in the climate arena? The authors suggest only one opportunity—investigate how the cost of achieving politically or hedging-based climate targets might be minimized. Their contribution provides a concise and internally consistent presentation of several sources of concern, but none is really new in their fundamental arguments. Antecedents of the points that they raise (and many others, for that matter) can be found in the established literature from the past 5 or 10 years; see, for example, Yohe (2003), Weitzman (2009) or Yohe and Tol (2008). This is not really a problem or a criticism for present purposes, though, because their discussion is so tightly articulated that it can be an effective springboard for discussions how improving economic analyses of climate change can do more than elaborate cost-minimizing strategies more thoroughly. On the one hand, dynamic cost–benefit frameworks cannot be discarded on the basis of what Ackerman, et al. or others say because official government agencies have not yet been convinced. Indeed, despite the now obvious concerns about the bases of estimates of the social cost of carbon derived from integrated assessment models, for example, such estimates are essential in bringing climate change to bear on a wide range of other policies and regulations. We cannot dismiss them, therefore; we must improve them and let practitioners know about their deficiencies. On the other hand, focusing on the economic underpinnings of risk-management techniques makes it clear that cost minimization is but of many roles for efficiency-based economic analysis.

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.

On Non-Marginal Cost-Benefit Analysis

Conventional cost-benefit analysis incorporates the normally reasonable assumption that the policy or project under examination is marginal in the sense that it will not significantly change relative prices. In particular, it is assumed that the policy or project does not change the underlying growth rate of the economy. However, these assumptions may be inappropriate in some important circumstances, such as large development projects in small economies, or large-scale infrastructure investment programmes. This paper develops the theory on the evaluation of non-marginal policies and projects, with an empirical application to the mitigation of global climate change. We examine the conditions under which evaluation of a non-marginal project using marginal methods may be both qualitatively and quantitatively wrong, and explore the magnitude of the potential error using a commonly employed integrated assessment model of climate change.

New roads to international environmental agreements: the case of global warming

We relax the single agreement and open membership assumptions that are implicit in the concept of internal and external stability, which has been widely used to analyze the formation of international environmental agreements (IEAs). By means of numerical simulations we investigate the impact of these changes using a dataset derived from an integrated assessment model of climate change. Our simulations show that multiple agreements are superior to a single agreement and exclusive membership is superior to open membership in ecological and welfare terms. Moreover, we demonstrate the importance of transfers for successful treaty making and we derive recommendations for the design of future IEAs.

Optimal Transfers and Participation Decisions in International Environmental Agreements

Transfers often play a crucial role in encouraging participation in international environmental agreements (IEAs). However, the economic literature on transfers is very limited and results achieved so far do not exploit the full potential of transfers for successful treaty-making. Therefore, in this paper, we develop a framework that enables us to study the role of transfers in a more systematic way. We propose a design for transfers using both internal and external financial resources and making welfare optimal agreements self-enforcing. To illustrate the relevance of our transfer scheme for actual treaty-making, we use a well-known integrated assessment model of climate change to show how appropriate transfers may be able to induce almost all countries into signing a self-enforcing climate treaty.

Abrupt non-linear climate change, irreversibility and surprise

Any discussion of the benefits of greenhouse gas (GHG) mitigation measures should take into consideration the full range of possible climate change outcomes, including impacts that remain highly uncertain, like surprises and other climate irreversibilities. Real-world coupling between complex systems can cause them to exhibit new collective behaviours that are not clearly demonstrable by models that do not include such coupling. Through examples from ocean circulation and atmosphere–biosphere interactions, this paper demonstrates that external forcings such as increases in GHG concentrations can push complex systems from one equilibrium state to another, with non-linear abrupt change as a possible consequence. Furthermore, the harder and faster a system is perturbed, the higher the likelihood of such surprises—a conclusion that has significant bearing on the assessment of the potential benefits of the timing and stringency of GHG abatement measures. The paper concludes with a perspective on how to better incorporate uncertainty and surprise into integrated assessment models of climate change.

The ICLIPS Impacts Tool: A Graphical User Interface to Climate Impact Response Functions for Integrated Assessments of Climate Change

This paper presents the ICLIPS Impacts Tool, a graphical user interface that provides access to a large set of climate impact response functions (CIRFs) from the ICLIPS model, an integrated assessment model of climate change. Its reduced-form impact module is comprised of CIRFs that depict the regional sensitivity of selected climate-sensitive impact sectors to changes in important climatic and atmospheric drivers in biophysical terms. The CIRFs were initially developed to enable the incorporation of thresholds for climate impacts in a tolerable windows analysis with the ICLIPS model. However, they are also a valuable source of information in their own right. The ICLIPS Impacts Tool provides convenient access to a large number (ca. 100,000) of impact diagrams for a wide range of impact indicators, geographical regions, and climate projections. The choice of Java as programming language enables the ICLIPS Impacts Tool, which is distributed on a CD-ROM, to run on the most common computer platforms, including Microsoft Windows, Mac OS X, Linux, Solaris, and AIX.

Methane Emission Reduction: An Application of FUND

Methane is, after carbon dioxide, the most important anthropogenic greenhouse gas. Governments plan to abate methane emissions. A crude set of estimates of reduction costs is included in FUND, an integrated assessment model of climate change. In a cost-benefit analysis, methane emission reduction is found to be instrumental in controlling the optimal rate of climate change. In a cost-effectiveness analysis, methane emission reduction largely replaces carbon dioxide emission reduction. Methane emission reduction reinforces the case for international cooperation in climate policy, but complicates the efficient allocation of emission reduction efforts. Methane emission reduction at the short run does not help to achieve the ultimate objective of the Framework Convention on Climate Change.

Incorporating Catastrophes into Integrated Assessment: Science, Impacts, and Adaptation

Incorporating potential catastrophic consequences into integrated assessment models of climate change has been a top priority of policymakers and modelers alike. We review the current state of scientific understanding regarding three frequently mentioned geophysical catastrophes, with a view toward their implications for integrated assessment modeling. This review finds inadequa- cies in widespread model assumptions regarding the nature of catastrophes themselves and climate change impacts more generally. The possibility of greatly postponed consequences from near- and medium-term actions suggests that standard discounting practices are inappropriate for the analysis of climate catastrophe. Careful consideration of paleoclimate and geophysical modeling evidence regarding the possibility of changes in ocean circulation suggests a reframing of the source of climate change damages in economic models, placing changes in climate predictability, rather than gradual changes in mean values, at the focus of economic damage assessments. The implications of decreases in predictability for the modeling of adaptation are further discussed.

Reevaluation and renegotiation of climate change coalitions—a sequential closed-loop game approach

Major international environmental problems can be characterized as stock externality phenomena. Long-term international environmental coalitions are subject to unexpected shocks. Certain shocks might have strong impacts on regional environmental policies and their commitments to the coalition. The open-loop solutions in optimal control problems and differential games cannot capture regions’ reactions to those shocks. In this paper, we develop a feasible modeling approach that uses the closed-loop strategies to study the issues of reevaluation and renegotiation of climate change coalitions. For the purpose, we design an algorithm that decomposes a closed-loop strategy into a sequence of open-loop equilibria and implement the algorithm in the RICE model (Am. Econ. Rev. 86 (1996) 741), an integrated assessment model of climate change and economies. We analyze policy and methodological implications of the closed-loop strategies through simulations of the RICE model.

Malthus and Climate Change: Betting on a Stable Population

A standard assumption in integrated assessment models of climate change is that population and productivity are growing, but at a decreasing rate. We explore the significance of the assumption of population and productivity growth for greenhouse gas abatement. After all, there has been no long run slowdown in the growth of productivity over the past few centuries, and the rate of population growth has actually been increasing for the past 19 centuries. Even if either of these growth rates were expected to slow, by how much is subject to great uncertainty. We show computationally that such continued growth greatly increases the severity of climate change. Indeed we find that climate change is a problem in large part “caused” by exogenous population and productivity growth. Rapid reductions in growth make climate change a small problem; smaller reductions in growth imply climate change is a very serious problem indeed. Analogously, reductions in the growth rate of population can be effective in controlling climate change.

Climate impact response functions for terrestrial ecosystems

We introduce climate impact response functions as a means for summarizing and visualizing the responses of climate-sensitive sectors to changes in fundamental drivers of global climate change. In an inverse application, they allow the translation of thresholds for climate change impacts (‘impact guard-rails’) into constraints for climate and atmospheric composition parameters (‘climate windows’). It thus becomes feasible to specify long-term objectives for climate protection with respect to the impacts of climate change instead of crude proxy variables, like the change in global mean temperature. We apply the method to assess impacts on terrestrial ecosystems, using the threat to protected areas as the central impact indicator. Future climate states are characterized by geographically and seasonally explicit climate change patterns for temperature, precipitation and cloud cover, and by their atmospheric CO2 concentration. The patterns are based on the results of coupled general circulation models. We study the sensitivity of the impact indicators and the corresponding climate windows to the spatial coverage of the analysis and to different climate change projections. This enables us to identify the most sensitive biomes and regions, and to determine those factors which significantly influence the results of the impact assessment. Based on the analysis, we conclude that climate impact response functions are a valuable means for the representation of climate change impacts across a wide range of plausible futures. They are particularly useful in integrated assessment models of climate change based on optimizing or inverse approaches where the on-line simulation of climate impacts by sophisticated impact models is infeasible due to their high computational demand.

On the representation of impact in integrated assessment models of climate change

The paper provides an overview of attempts to represent climate change impact in over twenty integrated assessment models (IAMs) of climate change. Focusing on policy optimization IAMs, the paper critically compares modeling solutions, discusses alternatives and outlines important areas for improvement. Perhaps the most crucial area of improvement concerns the dynamic representation of impact, where more credible functional forms need to be developed to express time-dependent damage as a function of changing socio-economic circumstances, vulnerability, degree of adaptation, and the speed as well as the absolute level of climate change.

On the optimal control of carbon dioxide emissions: an application of FUND

This paper presents the Climate Framework for Uncertainty, Negotiation and Distribution (FUND), an integrated assessment model of climate change, and discusses selected results. FUND is a nine-region model of the world economy and its interactions with climate, running in time steps of one year from 1990 to 2200. The model consists of scenarios for economy and population, which are perturbed by climate change and greenhouse gas emission reduction policy. Each region optimizes its net present welfare. Policy variables are energy and carbon efficiency improvement, and sequestering carbon dioxide in forests. It is found that reducing conventional air pollution is a major reason to abate carbon dioxide emissions. Climate change is an additional reason to abate emissions. Reducing and changing energy use is preferred as an option over sequestering carbon. Under non-cooperation, free riding as well as assurance behaviour is observed in the model. The scope for joint implementation is limited. Under cooperation, optimal emission abatement is (slightly) higher than under non-cooperation, but the global coalition is not self-enforcing while side payments are insufficient. Optimal emission control under non-cooperation is less than currently discussed under the Framework Convention on Climate Change, but higher than observed in practice.