High resolution regional climate model simulations available through the ACECRC Climate Futures team: what we have and how they can be used

The Climate Futures for Tasmania Project began in 2007 and has developed into the Climate Futures team within the Antarctic Climate and Ecosystems Cooperative Research Centre. The original project produced a data archive of dynamically downscaled simulations from 6 CMIP3 global climate models, for both the A2 and B1 emissions scenarios using CSIRO’s Conformal Cubic Atmospheric Model (CCAM) over Tasmania. The highest resolution outputs were of 14 km spatial resolution with 6 hrly temporal resolution. This has recently grown to include a further 6 CMIP5 global climate models dynamically downscaled simulations over South-East Australia and Tasmania at 1-hourly temporal resolution. This new set of simulations has a range of spatial resolutions (depending on the domain): 50 km spatial resolution over the Australasian region; 10 km spatial resolution over South East Australia (133.95E to 154.05E and -44.05N to -27.95N, which is approximately Baird Bay in the west to the East Coast, and from the Gold Coast in the North to the southern tip of Tasmania); and 5 km targeting the Australian Alpine Region, but including almost all of Victoria.

This data archive has been used by numerous projects in the fields of ecological research, natural disaster management, local government land-use planning, water management, power generation and to provide agriculture with estimates of the future. We will provide a description of the gridded data products available for use now through the ACECRC Climate Futures team and a general description of how to access them. We will provide examples of how these data have been used in the past and describe the archiving paradigm we have found to be the most effective when planning to revisit or query an archive numerous times for various different purposes.

This presentation aims to introduce the research community to this data archive; describe the archiving method selected and demonstrate the advantages of this approach; and provide example use cases.