By Ted Parson, Harvard University

The National Assessment will culminate in the preparation of a Synthesis Report which integrates the inputs from regional and sectoral assessment teams. The potential complexity of this task is enormous, given the number and variety of these inputs. Therefore, the National Assessment Synthesis Team (NAST) has spent significant time at their early meetings in 1998 generating guidelines for the regions and sectors to use while conducting their assessments. These guidelines are intended to help manage the complexity of the task, and to maintain a level of consistency among the products of regional and sectoral teams.

Because climate impacts happen to people, economies, and societies, the consequences of a specified climatic change or pattern of variability depend on the character of the society that lives with the climate. Consequently, assessing impacts requires making assumptions about the future character of American population, land use, economic activity, uses of natural resources, technology and institutions.

But finding a defensible and useful way to make these assumptions poses major challenges. The characteristics of societies and economies that shape climatic impacts can be intensely detailed, fine-grained, and coupled, and may be specific to particular locations. The particular socio-economic characteristics that most strongly shape climate impacts and vulnerability in a particular domain or region are not obvious a priori and cannot be calculated through analysis. Moreover, the impacts of changes in climate and adaptations to them will be jointly determined with response measures to mitigate human contribution to climate change, and with the other large-scale economic, social, and technological trends that will shape future society. In the face of such complexity, and with the limited time available, a useful and defensible assessment of impacts of climate change and variability requires massive simplification.

To make the complexity of their projections manageable, each regional and sectoral team has been asked to make two fundamental simplifications. First, rather than examining all dimensions of impacts and vulnerability in their region or sector simultaneously, they have been asked to choose a few specific domains that they judge likely to be most important, or most illustrative, of patterns of impact in their region or sector. (For example, the Pacific Northwest team is examining climate impacts on freshwater flows in the Columbia Basin, and consequently on the multiple sectors and activities that depend on these flows. The human health sectoral team is examining climate-induced heat stress risks in major midwestern cities such as Chicago.)

Second, for each domain they are examining, the teams are identifying a small number of key socio-economic factors that in their judgement are likely to have the strongest and most direct influence on impacts and vulnerabilities. They are then examining the impacts of specified climate scenarios under alternative assumptions for these key socio-economic factors. By focusing on a few key factors directly linked to climate impacts, the teams should be able to avoid the overwhelming complexity that would follow from having to tell the full story of how the factors came to have these values. For example, if a forestry study decides that commercial forest-product demand is a key factor determining impacts, they can proceed to assume high and low values for demand without having to specify what combination of demographic, market, and technological factors caused demand to be high or low.

Given these guidelines, the basic approach being taken to impact assessment is as follows. A few alternative socio-economic scenarios are created by jointly varying the chosen socio-economic factors between their high and low values, combining values of different variables expected to be associated with high, and with low, vulnerability to impacts. While particular studies vary in their structure, typical analyses consider from two to four distinct socio-economic cases. A specified climate scenario is being imposed on each of these cases, and its effects measured relative to the present climate. This difference will provide a first-order illustration of potential climatic impacts. How this difference varies among alternative climate scenarios will illustrate variation of impacts due to uncertainty in climate. How the difference varies among alternative socio-economic scenarios will illustrate the socio-economic determinants of vulnerability. How it varies with specific hypothesized responses -- changes in management, policy, institutions and infrastructure -- will illustrate key decisions that may help influence adaptive capacity.

To provide consistent socio-economic assumptions, the assessment is providing teams with projections from a commercial regional economic model. The model provides annual population and economic projections at fine spatial scales -- annual population by sex for 5-year age cohorts, and employment and income for 13 sectors, at the level of states, counties, and metropolitan areas. Separate high, middle, and low projections are being provided, of which the "low" and "high" projections combined low and high assumptions for population, labor force participation, and productivity growth.

For population, the three scenarios use the US Census Bureau's assumptions for fertility and mortality, but apply a wider range of assumptions for future net immigration. The scenarios also vary rates of labor-force participation by older workers (55 years and over), with the low scenario holding participation at present levels while the middle and high scenarios extended recent trends of increasing participation. Finally, the scenarios assume varying annual rates of growth in economic output per worker -- 0.6%, 1.2%, and 2.4% per year in the low, middle and high scenarios.

Look to future issues of Acclimations for reports from the regions and the sectors on the use of socioeconomic scenarios in their assessments.