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Development of regional climate change scenarios for impact assessments
Assessing how countries or regions should respond to the impacts of a changing climate requires the application of climate change scenarios—plausible and self-consistent realizations of how the climate may evolve. Studying the sensitivity of socio-economic activities to change in one aspect of the climate can be done simply by seeing, for example, how agriculture is affected by an increase in temperature of 2°C. This approach ignores the full diversity of likely changes and their implications (which could be different even in the sector studied). To obtain this information, we need to apply global climate models (GCMs). These are physical representations of the climate system, which simulate weather variables, their interactions and the main factors driving their variability and change.
Applying a suite of GCMs with different assumptions about how atmospheric concentrations of greenhouse gases and aerosols will evolve provides a range of climate change scenarios. Where there is consensus amongst these and the physical mechanisms responsible are clear, then useful information is available for assessing regional impacts of climate change. In many cases, these scenarios lack the regional detail that impact studies generally need due to the coarse resolution of GCMs. Dynamical and statistical models are available to derive fine-scale information from the GCM output (Giorgi et al., 2001).1 Both types of models are driven by data from GCMs.
1 Note that interpolating between GCM grid points adds no high resolution information and so the interpolated fields can be misleading especially where local forcings (e.g. complex physiography) or higher resolution physical processes (e.g. the formation of tropical cyclones) are important.
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