The main purposes of socioeconomic scenarios in the assessment of climate impacts, adaptation, and vulnerability are:

• To characterize demographic, socioeconomic, and technological driving forces underlying anthropogenic GHG emissions that cause climate change
  
• To characterize the sensitivity, adaptive capacity, and vulnerability of social and economic systems in relation to climate change.

This section focuses on the second use. However, in integrated global assessments, scenarios underpinning these two applications should be consistent with one another. Many key parameters, such as population and economic growth, are common to both types of exercise. More flexibility with regard to consistency may be appropriate at local and regional scales. Regional trends may be diverse, and developments in a specific region may diverge from those at the global level.

The use of socioeconomic scenarios in assessing vulnerability to climate change is less well developed than their use in exploring GHG emissions. The IPCC Technical Guidelines for Assessing Climate Change Impacts and Adaptations (IPCC, 199) recommend the use of socioeconomic scenarios, with and without climate change, to assess impacts and adaptive responses. At that time, few studies had reached that ideal. As new frameworks for characterizing vulnerability develop (Downing et al., 1999), impact studies can begin to use more consistent, global scenario approaches.

Socioeconomic scenarios in impact assessment have tended to focus on quantitative characterization of key parameters and to ignore the qualitative "storyline" elements of a fully developed scenario approach. If the implications of climate change impacts and adaptation on sustainable development are to be assessed (Munasinghe, 2000), much more sophisticated descriptions of vulnerable impact units will be required, along with better understanding of institutional and economic coping capacity. Section 3.2 provides examples of emerging work of this kind.

Socioeconomic scenarios in general have been developed to aid decisionmaking under conditions of great complexity and uncertainty in which it is not possible to assign levels of probability to any particular state of the world at a future point in time. Therefore, it usually is not appropriate to make a statement of confidence concerning a specific socioeconomic scenario (Moss and Schneider, 2000). However, this does not mean that all scenarios are equally likely. Some, used to test sensitivities, may be at the limits of the range of plausibility. More robust statements may be possible about the level of confidence in specific quantitative indicators, such as population or GDP, associated with given scenarios.

The socioeconomic baseline describes the present or future state of all nonenvironmental factors that influence an exposure unit. The factors may be geographical (land use or communications), technological (pollution control, water regulation), managerial (forest rotation, fertilizer use), legislative (water-use quotas, air quality standards), economic (income levels, commodity prices), social (population, diet), or political (levels and styles of decisionmaking). The IPCC has published a set of baseline statistics for 195 countries that are representative of the early to mid-1990s (IPCC, 1998). The data were collected from a variety of sources, such as the World Bank, the United Nations Environment Programme (UNEP), and the Food and Agriculture Organization (FAO) (see Table 3-1). These are only selected, summary data; individual impact studies are likely to require information on other factors or at a much higher spatial resolution.

Climate change impact assessment requires sound understanding of current socioeconomic vulnerabilities. These vulnerabilities have implications for deliberate adaptations that "involve conscious actions to mitigate or exploit the effects of climate change" (Adger, 1999). Many of those who are exposed will be vulnerable to a range of other stresses, irrespective of climate change (e.g., high population growth, rapid urbanization, environmental degradation, ambient air pollution, social inequality, infrastructure degradation, and health hazards). In time, stresses associated with the development process may reinforce those generated by climate change. For instance, sea-level rise causes saltwater intrusion, which can be aggravated by diverting freshwater outflows to satisfy the needs of agriculture, energy, and human consumption.

Table 3-1: Dimensions and attributes of socioeconomic scenarios reported in some recent climate change impact and adaptation assessments.
Scenarios	IPCC Basea	SRES	Pakistanc	UKCIPd	ACACIAe	USNACCf
Time frame/horizon	Early 1990s	1990-2100	2020/2050	2020s/2050	2020s/2050s/2080s	2050/2100
Focus	Impacts	Emissions	Impacts	Impacts	Impacts	Both
Scenario attributesg
- Economic growth	X	X	X	X	X	X
- Population	X	X	X	X		X
- Land use	X	X	X	X		X
- Energy	X	X	X	X		X
- Agriculture/food production	X		X	X
- Technological change		X		X	X	X
- Water	X			X
- Level of governance		X		X	X
- Social values		X		X	X
- Contextual data						X
- Institutional change						X
- Biodiversity	X			X
- Coastal zone management				X
- Settlement patterns				X
- Political organization					X
- Social policy		X			X
- Environmental policy		X			X
- Regional development		X			X
- Literacy			X
- Health care			X
a IPCC Baseline Statistics (IPCC, 1998). b IPCC Special Report on Emissions Scenarios (Nakicenovic et al., 2000). c UNEP Pakistan Country Study (Government of Pakistan, 1998). d United Kingdom Climate Impacts Programme (Berkhout et al., 1999). e A Concerted Action Towards A Comprehensive Climate Impacts and Adaptations Assessment for the European Union (Parry, 2000). f U.S. National Assessment of the Potential Consequences of Climate Variability and Change national-scenarios; additional scenarios were developed for individual regions and sectors (http://www.nacc.usgcrp.gov/). g Categories, some of which overlap, used by authors of the scenarios.

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