Four types of climate scenario that have been applied in impact assessments are introduced in this section. The most common scenario type is based on outputs from climate models and receives most attention in this chapter. The other three types have usually been applied with reference to or in conjunction with model-based scenarios, namely: incremental scenarios for sensitivity studies, analogue scenarios, and a general category of “other scenarios”. The origins of these scenarios and their mutual linkages are depicted in Figure 13.3.
The suitability of each type of scenario for use in policy-relevant impact assessment can be assessed according to five criteria adapted from Smith and Hulme (1998):
A summary of the major advantages and disadvantages of different scenario development methods, based on these criteria, is presented in Table 13.1. The relative significance of the advantages and disadvantages is highly application dependent.
Table 13.1: The role of various types of climate scenarios and an evaluation of their advantages and disadvantages according to the five criteria described in the text. Note that in some applications a combination of methods may be used (e.g., regional modelling and a weather generator). | |||
Scenario type or tool | Description/Use | Advantagesa | Disadvantagesa |
Incremental |
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Analogue: | |||
Palaeoclimatic |
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Instrumental |
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Spatial |
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Climate model based: | |||
Direct AOGCM outputs |
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High resolution/stretched grid (AGCM) |
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Regional models |
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Statistical downscaling |
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Climate scenario generators |
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Weather generators |
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Expert judgment |
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a Numbers in parentheses under Advantages and Disadavantages indicate that they are relevant to the criteria described. The five criteria are: (1) Consistency at regional level with global projections; (2) Physical plausibility and realism, such that changes in different climatic variables are mutually consistent and credible, and spatial and temporal patterns of change are realistic; (3) Appropriateness of information for impact assessments (i.e., resolution, time horizon, variables); (4) Representativeness of the potential range of future regional climate change; and (5) Accessibility for use in impact assessments. |
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