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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.

nn Statistical models use relationships between large-scale and local variables calibrated from historical data and can be applied if sufficient observed data are available. These relationships are then applied to GCM variables and assumed to hold in a changed climate. Dynamical models are similar in structure to GCMs and run at high resolution so they can resolve the local processes characterizing the detailed aspects of the climate of a region. In addition to providing skilful fine-scale detail, these dynamical models can also simulate realistic extreme events. Such models are becoming widely available to scientists in all countries through such initiatives as RegCNET of the International Centre for Theoretical Physics and the PRECIS programme of the UK Met Office Hadley Centre for Climate Change.
Figure 1—Simulation of UK winter precipitation in the Hadley Centre GCM and from its regional climate modelling system PRECIS run at 50 km and 25 km with data from the GCM compared to 10-km observations from the Climatic Research Unit
   
   
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Figure 2—Example of the application of PRECIS to develop regional climate changes scenarios for China which were used in the assessment of how climate change may affect crop production over China. Shown are projected changes of precipitation (mm/day) over China in the 2080s under the SRES B2 scenario (annual, winter, summer)

Richard Jones
Regional climate change research manager
Met Office Hadley Centre (Reading Unit), Meteorology Building
University of Reading, Reading, RG6 6BB, United Kingdom
richard.jones [at] metoffice.gov.uk
Telephone: +44 (0)118 378 5611 Fax: +44 (0)118 378 5615

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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