TS3 Methods and scenarios

TS.3.1 Developments in methods available to researchers on climate change impacts, adaptation and vulnerability

Since the Third Assessment (TAR), the need for improved decision analysis has motivated an expansion in the number of climate-change impacts, adaptation and vulnerability (CCIAV) approaches and methods in use. While scientific research aims to reduce uncertainty, decision-making aims to manage uncertainty by making the best possible use of the available knowledge [2.2.7, 2.3.4]. This usually involves close collaboration between researchers and stakeholders [2.3.2].

Therefore, although the standard climate scenario-driven approach is used in a large proportion of assessments described in this Report, the use of other approaches is increasing [2.2.1]. They include assessments of current and future adaptations to climate variability and change [2.2.3], adaptive capacity, social vulnerability [2.2.4], multiple stresses and adaptation in the context of sustainable development [2.2.5,2.2.6].

Risk management can be applied in all of these contexts. It is designed for decision-making under uncertainty; several detailed frameworks have been developed for CCIAV assessments and its use is expanding rapidly. The advantages of risk management include the use of formalised methods to manage uncertainty, stakeholder involvement, use of methods for evaluating policy options without being policy-prescriptive, integration of different disciplinary approaches, and mainstreaming of climate-change concerns into the broader decision-making context [2.2.6].

Stakeholders bring vital input into CCIAV assessments about a range of risks and their management. In particular, how a group or system can cope with current climate risks provides a solid basis for assessments of future risks. An increasing number of

Footnote 9, continued from below Box TS.4. At each location, all of which are in the Northern Hemisphere, the changing trait is compared with modelled temperatures driven by: (a) Natural forcings (pink bars), (b) anthropogenic (i.e., human) forcings (orange bars), and (c) combined natural and anthropogenic forcings (yellow bars). In addition, on each panel the frequencies of the correlation coefficients between the actual temperatures recorded during each study and changes in the traits of 83 species, the only ones of the 145 with reported local-temperature trends, are shown (dark blue bars). On average the number of years species were examined is about 28 with average starting and ending years of 1960 to 1998. Note that the agreement: a) between the natural and actual plots is weaker (K=60.16, p>0.05) than b) between the anthropogenic and actual (K=35.15, p>0.05), which in turn is weaker than c) the agreement between combined and actual (K=3.65, p<0.01). Taken together, these plots show that a measurable portion of the warming regional temperatures to which species are reacting can be attributed to humans, therefore showing joint attribution (see Chapter 1).

assessments involve, or are conducted by, stakeholders. This establishes credibility and helps to confer 'ownership' of the results, which is a prerequisite for effective risk management [2.3.2].

TS.3.2 Characterising the future in the Working Group IIIPCC Fourth Assessment

CCIAV assessments usually require information on how conditions such as climate, social and economic development, and other environmental factors are expected to change in the future. This commonly entails the development of scenarios, storylines or other characterisations of the future, often disaggregated to the regional or local scale [2.4.1, 2.4.6].

Scenarios are plausible descriptions, without ascribed likelihoods, of possible future states of the world. Storylines are qualitative, internally consistent narratives of how the future may evolve, which often underpin quantitative projections of future change that, together with the storyline, constitute a scenario [B2.1]. The IPCC Special Report on Emissions Scenarios (SRES), published in 2000, provided scenarios of future greenhouse gas emissions accompanied by storylines of social, economic and technological development that can be used in CCIAV studies (Figure TS.2). Although there can be methodological problems in applying these scenarios (for example, in downscaling projections of population and gross domestic product (GDP) from the four SRES large world regions to national or sub-national scales), they nevertheless provide a coherent global quantification of socio-economic development, greenhouse gas emissions and climate, and represent some of the most comprehensive scenarios presently available to CCIAV researchers. A substantial number of the impact studies assessed in this volume that employed future characterisations made use of the SRES scenarios. For some other

Economic emphasis -

A1 storyline

World: market-oriented Economy: fastest Der capita arowth Population: 2050 peak, then decline Governance: strong regional Interactions; Income convergence Technoloav: three scenario a roues:

• A1FI: fossil intensive

• A1T: non-fossil energy sources

• A1B: balanced across all sources

A2 storyline

World: differentiated Economy: reaionallv oriented: lowest per capita growth Population: continuously increasing Governance: self-reliance with preservation of local identities Technoloav: slowest and most fragmented development

B1 storyline

World: converaent Economy: service and information based; lower growth than A1 Population: same as A1 Governance: alobal solutions to economic, social and environmental sustalnabiiity

Technoloav: clean and resource-efficient

B2 storyline

World: local solutions Economy: Intermediate arowth Population: continuously increasina at lower rate than A2 Governance: local and reaional solutions to environmental protection and social equity Technoloav: more rapid than A2; less rapid, more diverse than A1/B1

■M- Environmental emphasis

Figure TS.2. Summary characteristics of the four SRES storylines [F2.5]

■M- Environmental emphasis

Figure TS.2. Summary characteristics of the four SRES storylines [F2.5]

studies, especially empirical analyses of adaptation and vulnerability, the scenarios were of limited relevance and were not adopted [2.4.6].

In the future, better integration of climate-related scenarios with those widely adopted by other international bodies (mainstreaming) is desirable, and enhanced information exchange between research and policy communities will greatly improve scenario usage and acceptance. Improved scenarios are required for poorly specified indicators such as future technology and adaptive capacity, and interactions between key drivers of change need to be better specified [2.5].

Characterising future climate

Sensitivity studies

A substantial number of model-based CCIAV studies assessed in this Report employ sensitivity analysis to investigate the behaviour of a system by assuming arbitrary, often regularly spaced, adjustments in important driving variables. Using a range of perturbations allows construction of impact response surfaces, which are increasingly being used in combination with probabilistic representations of future climate to assess risks of impacts [2.4.3,2.3.1,2.4.8].


Historical extreme weather events, such as floods, heatwaves and droughts, are increasingly being analysed with respect to their impacts and adaptive responses. Such studies can be useful for planning adaptation responses, especially if these events become more frequent and/or severe in the future. Spatial analogues (regions having a present-day climate similar to that expected in a study region in the future) have been adopted as a heuristic device for analysing economic impacts, adaptation needs and risks to biodiversity [2.4.4].

Climate model data

The majority of quantitative CCIAV studies assessed in the AR4 use climate models to generate the underlying scenarios of climate change. Some scenarios are based on pre-SRES emissions scenarios, such as IS92a, or even on equilibrium climate model experiments. However, the greatest proportion is derived from SRES emissions scenarios, principally the A2 scenario (assuming high emissions), for which the majority of early SRES-based climate model experiments were conducted. A few scenario-driven studies explore singular events with widespread consequences, such as an abrupt cessation of the North Atlantic Meridional Overturning Circulation (MOC) [,2.4.7].

The CCIAV studies assessed in the Working Group II Fourth Assessment (WGII AR4) are generally based on climate model simulations assessed by Working Group I (WGI) in the TAR. Since the TAR, new simulations have been performed with coupled Atmosphere-Ocean General Circulation Models (AOGCMs) assuming SRES emissions. These are assessed in the WGIAR4, but most were not available for the CCIAV studies assessed for the WGII AR4. Figure TS.3 compares the range of regional temperature and precipitation projections from recent A2-forced AOGCM simulations (assessed by WGI AR4: red bars) with earlier A2-forced simulations assessed in WGI TAR and used for scenario construction in many CCIAV studies assessed for the WGII AR4 (blue bars). The figure supports the WGI AR4

conclusion that the basic pattern of projected warming is little changed from previous assessments (note the positions of the blue and red bars), but confidence in regional projections is now higher for most regions for temperature and in some regions for precipitation (i.e., where red bars are shorter than blue bars) [B2.3].

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