Temperature response gtven 2x(COz] (K)
Figure 6.1. Box plots of elicited probability distributions of climate sensitivity» the change in globalh averaged surface temperature for a doubling of (X)> (2x [G0>1 forcing), Horizontal line denotes range from minimum (1%) to maximum (99%) assessed possible values. Vertical lick marks indicate locations of lower (5) and upper (95) percentiles. Box indicates interval spanned by 50% confidence interval Solid dot is the mean, and open dot is the median. The two columns of numbers on right-hand side of the figure report values of mean and standard deviation of the distributions. From Morgan and Keith, 1095.
scientist 5, is the lack of variance in his estimates, suggesting a very high confidence level in this scientist's mind thai he understands how all the complex interactions within the Earth System described above will work. None of the other scientists displayed that confidence, nor did the Lead Authors of IPCC. However, several scientists interviewed by Morgan and Keith expressed concern for "surprise" scenarios; for example, scientists 2 and 4 explicitly display this possibility in Figure 6.1, whereas several other scientists -myself among them - implicitly allow for both positive and negative surprises inasmuch as they assigned a considerable amount of their cumulative subjective probabilities for climate sensitivity outside the standard 1.5 to 4.5 range. This concern for surprises is consistent with the concluding paragraph of the IPCC Working Group I Summary for Policymakers quoted above and the studies of Rahmstorf (1997), Broecker (1997), and Stocker and Schmittner (1997).
IPCC Lead Authors, who wrote the Working Group I Second Assessment Report, were fully aware both of the wide range of possible outcomes and of the broad distributions of attendant subjective probabilities. After a number of sentences highlight ing such uncertainties, the report concluded, "Nevertheless, the balance of evidence suggests that there is a discernible human influence on global climate" (1PPC, 1996a, p. 5). The reasons for this now-famous subjective judgment were many, such as the kinds of factors listed above. These include a well-validated theoretical case for the
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natural greenhouse effect, validation tests of both model parametcrizations and performance against present and paleoclimatic data, and the growing "fingerprint" evidence that suggests that horizontal and vertical patterns of climate change predicted to occur in coupled atmosphere-ocean models have been increasingly evident in observations over the past several decades. Clearly, more research is needed, but enough is already known to warrant assessments of the possible impacts of such projected climatic changes and the relative merits of alternative actions to mitigate emissions and/or to make adaptations less costly. That is the ongoing task of integrated assessment analysts, a task that will become increasingly critical in the next century. To accomplish this task, it is important to recognize what is well established in climate data and modeling and to separate this from aspects that are more speculative. That is precisely what IPCC (1996a) attempted to accomplish.
6 J Assessing the Environmental and Societal Impacts of Climatic Change Projections
One of the principal tools used in the integrated assessment of climate change is integrated assessment models (IA.Ms), These models often comprise many submodels adopted from a wide range of disciplines. In IA Ms, modelers "combine scientific and economic aspects of climate change in order to assess policy options for climate change" control (Kelly and Kolstad, in press).
One of the most dramatic of the standard "impacts" of climatic warming projections is the increase in sea level typically associated with warmer climatic conditions. A U.S. Environmental Protection Agency (EPA) study used an unusual approach: combining climatic models with the subjective opinions of many scientists on the values of uncertain elements in the models to help bracket the uncertainties inherent in this issue. Titus and Narayanan (1996) -including teams of experts of all persuasions on the issue-calculated the final product of their impact assessment as a statistical distribution of future sea level rise, ranging from negligible change as a low probability outcome to a meter or more rise, also with a low probability (see Figure 6,2}. The midpoint of the probability distribution is something like a half-meter sea level rise by the end of the next century.
Because the EPA analysis stopped there, this is by no means a complete assessment. To take integrated assessment to its logical conclusion, we must ask what the economic costs of various control strategies might be and how the costs of abatement compare to l he economic or environmental losses (i.e., impacts, or damages, as they are called) from sea level rises. That means putting a value — a dollar value typically — on climate change, coastal wetlands, fisheries, environmental ref ugees, and so on . 1 iadi Dowlatabadi at Carnegie Mellon University leads a team of integrated assessors who, like Titus, combined a wide range of scenarios of climatic changes and impacts but, unlike the EPA studies, added a wide range of abatement cost estimates into the mix. The group's integrated assessment was presented in statistical form as a probability that investments in CO? emissions controls would either cost more than the losses from averted climate change or the reverse (Morgan and Dowlatabadi, 1996). Because its results do not include estimates for all conceivable costs (e.g., the human or political consequences
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