Why Do We Care About Integrated Assessment Models
Essay prepared for SEDAC by:
Peter M. Morrisette
Environmental Research Consultant
P.O. Box 684
Victor, ID 83455
- Understanding the Problem and Dealing With Complexity
- What Are Integrated Assessment Models and How Do They Work
- What Are the Uses of Integrated Assessment Models
Why do we care about integrated assessment models (IAMs) of climate change? The prospect of global climate change is a particularly difficult problem to deal with because it is global in scale, highly complex, not full understood by science, and not only lacks an obvious solution but also fundamentally challenges the problem-solving capacity of existing institutions. In order to address the climate change problem from a policy perspective, there is a need to understand many factors such as trends in the emissions of greenhouse gases, long-term changes in land use and land cover, the potential effect of changes in greenhouse gas emissions and changes in land use/cover on climate, and the potential effect of changes in climate on natural ecosystems and human activities.
In the coming years decision makers at all levels of government and in the private sector will be increasingly confronted with the need to make decisions about what to do about global climate change. Already, national decision makers are dealing with the implementation of the 1992 United Nations Framework Convention on Climate Change. Decisions about how to respond to climate change will have far reaching effects on economic acitivty and environmental quality across the globe.
Integrated assessment models are useful tools for organizing and assessing knowledge about climate change, identifying and understanding uncertainties and knowledge gaps, and informing judgments about impacts and possible response strategies. IAMs are not prescriptive models--they cannot tell policy makers how to respond to climate change; nevertheless, the results of IAMs are beginning to influence the debate about how to respond to climate change. For example, IAMs influenced the conclusions of the most recent assessment of the climate change problem by the Intergovernmenatal Panel on Climate Change (Watson et al. 1996; Bruce, Lee, and Haites 1996), and the Dutch government used the results of an IAM to help formulate its position on emission control strategies at a recent meeting pertaining to the United Nations Framework Convention on Climate Change (Alcamo and Kreileman 1996). This essay will briefly introduce the topic of integrated assessment modeling and the role it can play in helping scientists and policy makers understand the climate change problem.
In the past several years a great deal of attention has been directed toward the issue of how to respond to a global climate change that may take place in the next century as a result of increasing global mean temperature. Human activities such as the burning of fossil fuels, deforestation, and agriculture have led to a build up of trace gases in the atmosphere commonly referred to as greenhouse gases. These greenhouse gases which include carbon dioxide, methane, and nitrous oxide trap solar radiation in the atmosphere which over time could lead to an increase in the mean temperature of the Earth. An increase in global mean temperature of several degrees celsius could result in significant regional changes in temperature and precipitation, which could have a profound impact on natural and managed ecosystems, coastlines, water resources, agriculture, and human health and welfare.
One of the great difficulties in dealing with the problem of global climate change is that it is not fully understood by science. There is uncertainty about how increasing concentrations of greenhouse gases might affect climate and how ecosystems might be affected by changes in climate. In addition, there is uncertainty about what these changes might mean for humans and whether action taken now to avoid the problem (e.g., cutting back on the use of fossil fuels) will make a difference. In addition, there is also much uncertainty about the economic costs associated with different options for responding to the climate change problem.
Despite all of this uncertainty, there are aspects about the climate change problem on which scientist agree. For example, there is little question that the atmospheric concentration of greenhouse gases such as carbon dioxide are increasing and that this is due in part to human activities. There is also general agreement that if the Earth does warm over the next century, impacts will vary regionally across the globe depending on how the climate changes. In addition, it is also anticipated that developed countries will have an easier time dealing with the impacts of a global climate change than developing countries. The recent work of the Intergovernmental Panel on Climate Change (IPCC) outlines the current state-of-the-knowledge about global climate change (see Houghton et al. 1996; Watson et al. 1996).
In order to better understand the complex problems that shape the climate change issue, scientists have increasingly relied on interdisciplinary approaches and tools for understanding both the physical and social aspects of the problem. For example, physical scientists have developed very complex computer models of the Earth's atmosphere and oceans (general circulation models or GCMs) for assessing changes in atmospheric chemistry and global climate.
Another tool that both physical and social scientists, as well as decision makers have been turning to for assessing the climate change problem is integrated assessment. In general terms, an integrated assessment brings together a broader set of perspectives and information about a problem than would normally result from efforts within a single research discipline. In the context of climate change, this involves developing a perspective for integrating knowledge about the physical climate system, natural ecosystems, and human activities and welfare. Because integrated assessments bring together and summarize information from diverse fields of study, they are useful tools for helping decision makers understand very complex environmental problems such as climate change. Indeed, most integrated assessment activities are designed to aid the decision-making process.
Integrated assessment of climate change can accomplish several objectives. In their state-of-the-art overview of the field of climate change integrated assessment modeling, Rotmans, Dowlatabadi, and Parson (1996) outline five key advantages of integrated assessment techniques:
- Place global climate change in the context of other global change problems such as stratospheric ozone depletion and land degradation, and to underscore the interrelationships.
- Help assess potential preventive or adaptive responses to climate change.
- Provides a framework for structuring scientific knowledge about climate change.
- Translate the concept of uncertainty into terms that are useful for decision makers.
- Help prioritize research activities and to identify areas where knowledge is lacking.
The terms "integrated assessment" and "integrated assessment modeling" are often confused. Integrated assessment refers to the activity of bring together and summarizing diverse types of information about a complex problem. An integrated assessment model is a tool for conducting integrated assessments. Most climate change integrated assessment activities that are currently underway are developing an integrated assessment model. The Thematic Guide essay In Search of Integrated Assessment describes many of the over twenty IAM efforts. However, there have been some recent integrated assessment activities that have not relied on developing an IAM. Notable examples include the MINK study undertaken by Resources for the Future and the MacKenzie Basin Impact Study sponsored by the Canadian government (Rosenberg 1993; Cohen 1995). Both studies are regionally based, multi-sector assessments of potential climate change impacts and adjustments.
A climate change integrated assessment model is a mathematical computer model based on explicit assumptions about how the modeled system behaves. The strength of an IAM is its ability to calculate the consequences of different assumptions and to interrelate may factors simultaneously. Rotmans, Dowlatabadi, and Parson (1996) note that climate change IAMs attempt to quantify as much as possible of the cause-effect relationships of the climate change problem and the cross-linkages and interactions between different issues.
Climate change IAMs are composed of sub-models or meta-models that cover the climate system, biosphere, and economic activity. IAMs must rely on using sub-models or meta-models because limitations in computing power make it impossible to fully incorporate a state-of-the-art climate or bioshpere model into an IAM. A climate general circulation model (GCM), for example, already stretches the limit of super computing technology. These sub-models or meta-models are simpler, reformulated versions of the larger models derived from the scientific literature (see Rotmans, Dowlatabadi, and Parson 1996).
IAMs can approach the climate change issue from vary different perspectives. Dowlatabadi (1995) has developed a three category taxonomy of IAMs based on the decision framing of the models--i.e., how policies are chosen. The three categories are: 1) policies based on cost-effectiveness, 2) policies based on a limit to acceptable physical impacts, and 3) policies based on cost-benefit framing. A modified version of Dowlatabadi's IAM taxonomy is available online via SEDAC's MVA Service. Dowlatabadi (1995) notes that cost-effectiveness and cost-impact models tend to be more narrowly focused than cost-benefit models which require integration of social and natural systems in order to fully assess impacts and responses.
Even among cost-benefit models there is considerable variation between models including differences in the scale (e.g., global vs. regional) and scope (e.g., number of economic sectors examined), and in the assumptions that underlie the models. No single IAM model can capture the full range of issues and complexities that characterize the climate change problem. Instead, different IAMs focus on different questions and issues. There are significant advantages to this approach. For example, it provides decision makers with different perspectives on the climate change problem, and it facilitates the identification of knowledge gaps and uncertainties.
In assessing the uses and merits of climate change IAMs, it is essential to understand that IAMs are not prescriptive models. IAMs cannot predict impacts, nor can they tell policy makers how to respond. This is due to limits in our knowledge of the climate change problem, modeling approaches, and computer technology. If IAMs cannot provide specific answers to policy questions, what can they do?
Despite the limitations of IAMs, they can provide some general insights regarding the climate change problem. It should be noted, however, that the modeling community has tended to ascribe low levels of confidence to many of these findings and insights. The Usage Guide essay on insights by Risbey and Kandlikar and the essay on policy uses by Agrawala, as well as the state-of-the-art overview by Rotmans, Dowlatabadi, and Parson (1996) summarize many of these insights which include a suggestion that a short (e.g., 10 year) delay in the implementation of greenhouse gas emission control strategies may not make much of difference in society's long-term ability to deal with climate change, cooperation among nations in developing response strategies is likely to produce better results than nations acting on their own, and the overall impact of climate change on the global economy may be relatively modest. As noted above, these findings and insights are not robust enough to form the basis for specific policies and actions, but they do inform and shape the ongoing debate about how to deal with the problem of global climate change.
A more direct use of IAMs is as a tool for organizing and assessing knowledge about the climate change problem, and identifying uncertainties and knowledge gaps. IAMs can inform us about what we do not know about the climate change problem. This is key information for establishing research priorities and for understanding the limitations of response strategies. IAMs can also be a valuable learning tool for both scientists and policy makers. IAMs provide a different perspective on the climate change problem than is available through either GCMs or more narrow disciplinary approaches. Gaining new perspectives is important for understanding the complex interaction between natural and social systems that underlie the climate change problem. There are no easy answers to the climate change problem. No model or approach can predict what will happen or can tell decision makers what to do to solve the problem. IAMs, however, offer a very useful way of looking at and assessing the climate change problem.
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CIESIN URL: http://sedac.ciesin.org/mva/iamcc.tg/TGHP.html