Downscaling in CCIA 2015

Downscaling is the process of translating outputs of coarse-scale Global Climate Models into locally-relevant information.

The ‘change factor’ method of scaling observed data is a useful, simple technique to produce regional data. The more technical methods of statistical downscaling and dynamical downscaling may produce new, more regional information about the pattern of projected climate change (termed the climate change ‘signal’). Downscaling offers the greatest potential for new insights where factors like topography or coastlines are important, such as in Tasmania, the Eastern Seaboard and south-east Australia (See Technical Report Section 6.3.5).

Each downscaling method has its pros and cons and gives different results. Also, downscaling may not be performed for every model and every scenario. In the CCIA 2015 projections (found on this site) we use the CMIP5 ensemble of global climate models as the primary tool for making climate change projections. We complement this with insights from two new sets of downscaling (one statistical and one dynamical) and previous regional studies, especially where there is a compelling case for ‘added value’ at the regional scale.

See the Projections Landscape page for more information on State Government initiatives for producing regional studies of climate change and that have produced scaled or downscaled outputs.