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The appropriate time horizon for socioeconomic scenarios depends on the use to which they are put. Climate modelers often use scenarios that look forward 100 years or more. Socioeconomic scenarios with similar time horizons may be needed to drive models of climate change, climate impacts, and land-use change. However, policymakers also may wish to use socioeconomic scenarios as decision tools in framing current policies for climate change adaptation. In this context, time horizons on the order of 20 years may be more appropriate, reflecting the immediate needs of decisionmakers.
Short-term socioeconomic scenarios can still be very uncertain. "Surprises" such as economic slumps or booms, wars, or famines frequently occur in social and economic systems. Over the course of 50-100 years, even the most basic scenario drivers, such as population and aggregate economic activity, are highly uncertain, and their future development can be projected with any credibility only by using alternative scenarios. Moreover, technologies will have been replaced at least once, and those in use 100 years hence could have unimagined effects on climate sensitivity and vulnerability. Politically led developments in local, regional, and international systems of governance also will unfold along unpredictable paths.
Global emissions scenarios form the framework for predicting climate change and variability impacts at the national level. To assess vulnerability and adaptation potential, national scenarios must account for biophysical and socioeconomic impacts. The potential for autonomous adaptations must be understood, reflecting the ability of nature and society to cope with climate change and climate variability. Many of the impacts of climate change on the coping ability of human systems are likely to be location-specific. Impact assessors therefore should make use of local/regional scenarios, where appropriate, and be wary of generalizing experiences from one location to another. Matching of regional scenarios may be difficult, however—for example, if data on population and land use are available at different levels of resolution.
As illustrated in Table 3-1, scenario exercises often make specific assumptions about individual sectors. These sectors usually are chosen because they are considered particularly sensitive to climate change (e.g., water, agriculture/food) or because they are important sources or sinks for GHGs (e.g., energy, forestry). Detailed quantitative assumptions often are made about levels of future economic activity or the price of key commodities, which will influence adaptation strategies.
Formal modeling work generally is used to improve the detail, coherence, and internal consistency of socioeconomic variables that are susceptible to quantification. Expert judgment or stakeholder consultations may be used to build consensus around the characterization of more subjective and less quantifiable variables that relate to values and institutions. Stakeholder engagement also can provide a wealth of local expertise about specific impacts and vulnerabilities.
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