2. Projects
3. Understanding the key drivers of climate change in South Australia

Understanding the key drivers of climate change in South Australia

The objective of this task was to understand the key drivers of climate change in South Australia. In this task it was necessary to explore the causes of non-stationarity in our environmental time series. This needed to allow for seasonal variations and the influences of climate drivers such as the Indian Ocean Dipole (IOD) and the Southern Oscillation Index (SOI), including assessment of statistical significances. The environmental time series were decomposed into random variations about an underlying level, trend, and additive seasonal effects and then these levels, trends and seasonal effects were tracked over time. A key output from the Task was the statistical analysis of 53 stations across the eight SA Natural Resource Management (NRM) regions. The SA NRM regions: (0) SA Arid Lands, (1) Alinytjara Wilurara, (2) SA Murray Darling Basin, (3) Northern and Yorke, (4) Eyre Peninsula, (5) Kangaroo Island, (6) Adelaide and Mount Lofty Ranges and (7) South East. In broad terms, the task aimed to develop a clear agreement on the definition of climate drivers for South Australia. Overall, the research focused on the critical areas: Understanding SA climate, including the impacts of the El Niño-Southern Oscillation (ENSO) cycle, the Pacific Decadal Oscillation (PDO), the Indian Ocean Dipole (IOD), and the Southern Annular Mode (SAM) on rainfall and other hydro-climatic variables. In terms of significance for the project, this knowledge was essential for a quantification of the relative importance of climate change and variability in historical observations. It was also required for the selection of models for climate downscaling and for developing projections, including quantification of their associated uncertainty. Finally, it was important for understanding the projected changes and their implications. Throughout the project, there was ongoing communication with Tasks 2 and 3 to assist with climate downscaling projections.

Data and resources