Under a warming climate, regional rainfall patterns are likely to change due to a range of different physical (warmer atmosphere) and dynamical (changes to the circulation) processes in the atmosphere, as well as in response to any land surface changes that may eventuate (surface roughness, moisture fluxes and albedo).

Simulations by Global Climate Models (GCMs) provide a range of different plausible rainfall responses that demonstrates the types of changes that are possible (e.g., changes to magnitudes, seasonal shifts and intensities). However, most GCMs operate on a spatial resolution of about 100-250km, which presents two issues for use in adaptation and impact work: 1) a scale discrepancy between the provided GCM information (i.e., the climate change signal contained in the GCM output) and the scale that is of interest to most practitioners, and 2) processes occurring on GCM sub-grid scale are not resolved, which can be important depending on the region’s surface characteristics.

Using the Victorian Alps as an example, this poster argues for the use of fine resolution dynamical downscaling to advance current knowledge of climate change impacts on regional rainfall patterns. Dynamical downscaling simulates the physical and dynamical processes in the atmosphere at a finer resolution, using input from GCMs. However, given the limited availability of these data sets in Australia (which limits our understanding of the uncertainty space about this data), the value of dynamical downscaling for impact and adaptation work must always be considered in terms of what information is added relative to the GCM projections.