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This section presents a set of case studies that illustrates a range of specific approaches to the construction of socioeconomic scenarios that are relevant to climate impact assessment.
The IPCC's Special Report on Emissions Scenarios (SRES) (Nakicenovic et al., 2000) was prepared to improve on the earlier set of six IS92 scenarios developed in 1992 (Leggett et al., 1992). The SRES describes 40 scenarios in all—based on an extensive literature assessment, six alternative modeling approaches, and an "open process" that solicited worldwide participation and feedback. The scenarios (which are described in more detail in Section 3.8) cover the main demographic, economic, technological, and land-use driving forces of future emissions. They include emissions of all relevant GHGs plus sulfur dioxide (SO2), carbon monoxide (CO), nitrogen oxides (NOx), and nonmethane volatile organic hydrocarbons (VOCs). The IPCC specified that the scenarios should not include future policies that explicitly address climate change. However, they necessarily encompass other policies that may indirectly influence GHG sources and sinks. The scenarios suggest that assumptions about technology, rather than population and economic development, may be the most important driving force of future emissions.
The SRES emissions scenarios serve several purposes. First, they provide baselines of socioeconomic, technological, and land-use change, in combination with emissions trajectories, for the assessment of mitigation policies and measures (see TAR WGIII Chapter 2). Second, they can be used to drive the assessment of climate change (see TAR WGIII and Section 3.8). Third, they provide a global socioeconomic framework for regional-scale assessment of impacts and adaptation [e.g., see the United Kingdom Climate Impacts Programme (UKCIP) and European ACACIA examples, below].
The Pakistan Environment Ministry has produced a suite of three socioeconomic scenarios to inform national climate impact and adaptation planning (Government of Pakistan, 1998). The scenarios focus on two reference years—2020 and 2050—and include a combination of quantitative and qualitative indicators. Quantitative scenarios are presented for population, economic growth, agricultural production, energy demand, and industrial output. Variations in future rates of literacy, health care, import tariffs, forest cover, and infrastructure are expressed in qualitative terms. The 2020 scenario is the more detailed of the two; it is a composite of existing national projections and scenarios produced for "nonclimate" policymaking. The 2020-2050 scenarios were developed for the sole purpose of informing climate impact assessments and are much less detailed (Tol, 1998).
A set of "nonclimate scenarios" has been developed to provide a common framework for assessing climate impacts and adaptation under the stakeholder-led UKCIP (Berkhout et al., 1999). The scenarios were based on a broader "Environmental Futures" exercise (UK National Foresight Programme, 1999)—which, in turn, had drawn on emerging SRES work.
Four scenarios for the 2020s and 2050s were defined by two factors affecting the capacity and willingness of society to adapt to climate change: the extent to which social values reflect environmental concern and the effectiveness of governance institutions. Development of the scenarios involved extensive consultations with stakeholders (Lorenzoni et al., 2000). As a result, detailed scenario characterization was confined to the 2020s. For each scenario, key national indicators were developed. These indicators included population and GDP, as well as more specific variables relating to land-use change, patterns of agricultural activity, water demand, and investment in coastal defense. In addition, climate vulnerability was assessed qualitatively in several "impact domains," including agriculture, water, biodiversity, coastal zone management, and infrastructure and the built environment.
The framework scenarios were found to be a useful starting point for subsequent studies. However, the scenarios needed to be articulated in more detail to be useful at the regional or sectoral level. More quantification generally was required. This exercise underlined the need for scenarios to be tailored for end users, while maintaining broad consistency about key indicators such as population and GDP.
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