|Working Group I: The Scientific Basis|
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The Purpose of Climate Scenarios
This new chapter for the IPCC assesses the methods used to develop climate scenarios. Impact assessments have a very wide range of scenario requirements, ranging from global mean estimates of temperature and sea level, through continental-scale descriptions of changes in mean monthly climate, to point or catchment-level detail about future changes in daily or even sub-daily climate.
The science of climate scenario development acts as an important bridge from the climate science of Working Group I to the science of impact, adaptation and vulnerability assessment, considered by Working Group II. It also has a close dependence on emissions scenarios, which are discussed by Working Group III.
Methods for Constructing Scenarios
All these methods can continue to serve a useful role in the provision of scenarios for impact assessment, but it is likely that the major advances in climate scenario construction will be made through the refinement and extension of climate model based approaches.
Each new advance in climate model simulations of future climate has stimulated new techniques for climate scenario construction. There are now numerous techniques available for scenario construction, the majority of which ultimately depend upon results obtained from general circulation model (GCM) experiments.
Representing the Cascade of Uncertainty
There is a cascade of uncertainties in future climate predictions which includes unknown future emissions of greenhouse gases and aerosols, the conversion of emissions to atmospheric concentrations and to radiative forcing of the climate, modelling the response of the climate system to forcing, and methods for regionalising GCM results.
Scenario construction techniques can be usefully contrasted according to the sources of uncertainty that they address and those that they ignore. These techniques, however, do not always provide consistent results. For example, simple methods based on direct GCM changes often represent model-to-model differences in simulated climate change, but do not address the uncertainty associated with how these changes are expressed at fine spatial scales. With regionalisation approaches, the reverse is often true.
A number of methods have emerged to assist with the quantification and communication of uncertainty in climate scenarios. These include pattern-scaling techniques to inter-polate/extrapolate between results of model experiments, climate scenario generators, risk assessment frameworks and the use of expert judgement. The development of new or refined scenario construction techniques that can account for multiple uncertainties merits further investigation.
Representing High Spatial and Temporal Resolution Information
Preliminary evidence suggests that coarse spatial resolution AOGCM (Atmosphere-Ocean General Circulation Model) information for impact studies needs to be used cautiously in regions characterised by pronounced sub-GCM grid scale variability in forcings. The use of suitable regionalisation techniques may be important to enhance the AOGCM results over such regions.
Incorporating higher resolution information in climate scenarios can substantially alter the assessment of impacts. The incorporation of such information in scenarios is likely to become increasingly common and further evaluation of the relevant methods and their added value in impact assessment is warranted.
Representing Extreme Events
Applying Climate Scenarios in Impact Assessments
The choice of method constrains the sources of uncertainty that can be addressed. Relatively simple techniques, such as those that rely on scaled or unscaled GCM changes, may well be the most appropriate for applications in integrated assessment modelling or for informing policy; more sophisticated techniques, such as regional climate modelling or conditioned stochastic weather generation, are often necessary for applications involving detailed regional modelling of climate change impacts.
Improving Information Required for Scenario Development
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