story lines laid out in a report. These story lines were then turned into various quantifications of the underlying driving socioeconomic forces. The story lines were then used to estimate emissions, atmospheric concentrations, radiative forcing, and finally, from climate models, ranges of temperature and precipitation. IAV models could then use these estimations at an aggregate level to look at impacts such as risks to species, risks from extreme climate events, distribution of impacts across societies, and aggregate economic impacts. However, this kind of activity took several years to play out so that by the time the models of impacts were producing estimates, there might have been a new generation of climate models in use. Further, Moss pointed out that there has been quite a bit of research on how people interpret these story lines and scenarios and this research indicates that there can be overconfidence in interpreting results that are simply illustrative story lines. People often begin to believe that such story lines are the most likely story lines, which is not the case. This belief can limit their thinking about alternative futures, whereas taking a broad approach is extremely important for bracketing the widest possible future conditions. Finally, Moss noted that there is not necessarily a one-to-one correspondence between the story lines generated by models and the socioeconomic quantification of those story lines.
As described by Moss, a newly developed scenario process that can help to address these issues starts with radiative forcing instead of with socioeconomic story lines. The new process begins by assuming some different levels of radiative forcing (or representative concentration pathways; RCPs) and then models in parallel both the climate scenarios that result from using the RCPs and the socioeconomic scenarios that could produce those RCPs. Some of the new socioeconomic scenarios will be consistent with the levels of emissions required to produce the RCPs, and some will be independent. Moss concluded that this new scenario process, although not perfect, presents opportunities, including greater openness and flexibility, especially for socioeconomic scenario development, that could lead to increased collaboration across the distinct research communities and improved synthesis and coordination across assessments at different scales. He noted that the challenges for mitigation and impacts analysis include the need to carefully consider what projections are needed on what time scale and how that information is going to be used. He also noted the need for approaches to performing probabilistic analysis and to communicating uncertainties.
Dale Jorgensen of Harvard University then discussed a modeling approach (the IGEM model) and scenarios for climate modeling based on the requirements specified in the Waxman-Markey bill. Jorgensen first discussed the major determinants of economic growth, including productivity changes, capital accumulation (investment), population, labor supply, and human capital. He went on to discuss the historical record of technical change for various industries in the United States and the modeling of technical change and substitution in the IGEM model. The use of econometrics in the IGEM model makes it possible to sort out what portion of the technology change occurring over the very extensive historical record is attributable to price changes like those experienced during the energy crisis periods and how much is due to changes separate from price. Jorgensen also described the modeling of household savings/investment and consumption and leisure. Finally, he described the demographic assumptions used in the IGEM model, given that projections of consumption and welfare depend on projections of population.
This model was then benchmarked to the base case in the 2009 Energy Outlook (EIA, 2009) and was used by Jorgensen to look at nine scenarios related to the Waxman-Markey bill. The modeling results demonstrate the importance of demographic and technology assumptions. Jorgensen argued that the model of technology and technological change should include substitution (“elasticities”) and technical change (“trends”) and that the IGEM econometric model provides a unified representation. Jorgensen also concluded that standard statistical techniques, based on confidence intervals generated by the econometrics, can capture uncertainties in estimated impacts, and that this econometric approach avoids the limits on dimensionality of a Monte Carlo approach.
The remainder of the session included a panel discussion and comments from the audience. Nebojsa Nakicenovic of the International Institute for Applied Systems Analysis served as the discussant, with comments that focused on story lines. His hypothesis was that the importance of story lines will increase as the RCP scenarios require additional logic and justification. He stated his belief that, because of the large numbers of parameters and complicated assumptions in coupling socioeconomic modeling to modeling of climate process, it is important to have the complementary analysis of story lines to explain the logic of how these scenarios are constructed. Finally, Nakicenovic described the story lines in the case of multiple scenarios as very helpful in explaining the logic for