18 th World IMACS / MODSIM Congress, Cairns, Australia 13-17 July 2009 http://mssanz.org.au/modsim09 Dynamical downscaling techniques: Impacts on regional climate change signals Katzfey, J.J. 1 , J. McGregor 1 , K. Nguyen 1 and M. Thatcher 1 1 Center for Australian Weather and Climate Research (CAWCR), CSIRO Marine and Atmospheric Research (CMAR), PMB #1, Aspendale, Victoria, Australia Email: jack.katzfey@csiro.au Abstract: There are many different techniques for dynamical downscaling of global climate change projections to study regional climate change, including high-resolution global atmospheric models, stretched- grid models, and the most popular technique, limited-area models. All these methods require some information from fully-coupled atmospheric-oceanic-ice global coupled models (GCMs), ranging from ocean temperatures through to full atmospheric data every six hours as forcing. A systematic study of these various techniques and their impact on the simulated regional climate is required in order to assess the validity and assumptions that influence the results of the simulations. In this preliminary study, the impact on the precipitation when downscaling with and without atmospheric forcing (in the form of a digital filter) and with and without bias-corrected sea surface temperatures (SSTs) is investigated using the CSIRO Conformal Cubic Atmospheric Model (CCAM). The CCAM is a variable-resolution global atmospheric model with enhanced resolution over a selected region and does not require lateral boundary conditions. Significant improvement in the distribution of precipitation in the current climate is obtained when bias- corrected sea surface temperatures from global coupled models are used as lower boundary conditions. Using uncorrected SSTs and atmospheric forcing from the GCMs to drive CCAM, the basic large-scale features of the GCMs are preserved in the downscaled run. The results demonstrate the flexibility of using the variable-resolution CCAM for dynamical downscaling. Keywords: dynamical downscaling, regional climate, climate change 3942