Past and Future Temperature Extremes and Vegetation in Western Australia (2018)

The south-west of Western Australia (SWWA) is a region of significant agricultural production, with the commodity value of wheat, barley, and oats varying annually from approximately $3,000 million to more than $5,000 million. These crops are grown from winter to spring and are rain-fed. Consequently crop yields are heavily impacted by inter-annual variations in temperature and precipitation. SWWA is also home to some of Australia’s most iconic forests, which are sensitive to changes in temperature and precipitation. Thus, an understanding of the current regional climate of SWWA and how it might change in the future is crucial for the planning and management of the region’s agriculture and forestry sectors. The aim of this project is to produce state-of-the art regional climate projections of future climate change for the region.

Principal investigator

Magnifying glass

Area of science

Atmospheric Science

Systems used


Applications used

Weather Research and Forecasting (WRF) Model
Partner Institution: Murdoch University | Project Code: y98

The Challenge

Global Climate Models (GCMs) are sophisticated mathematical models which are used to simulated current future climate across the entire globe. Their spatial resolution is to the order of 100 to 250 km, which is very coarse and limits their usefulness in assessing future changes in climate at the regional scale (1 to 10 km). The challenge is to dynamically downscale these GCMs from their coarse resolutions of 100 to 250 km, down to 1 to 10 km, to provide regionally relevant information about climate change and assist in developing policy and decision making about future climate change regionally.

The Solution

The solution is to to use state-of-the art Regional Climate Models (RCMs) to dynamically downscale GCMs. This requires the use of high performance computing as well as data storage resources.

The Outcome

The PAWSEY center provides both high performance computing via Magnus, as well as data storage solutions to enable our group to carry out high resolution regional climate projections for the southwest of Western Australia using the Weather Research and Forecasting (WRF) model, a state-of-the-art RCM.

List of Publications

Di Virgilio, G., Evans, J. P., Di Luca, A., Olson, R., Argüeso, D., Kala, J., Andrys, J., Hoffmann, P., Katzfey, J., Rockel, B. (2019) Evaluating reanalysis-driven CORDEX regional climate models over Australia: model performance and errors, Climate Dynamics, in press

Liu, N., M. Shaikh, J. Kala, R. Harper, B. Dell, S. Liu., G. Sun (2018) Parallelization of a distributed ecohydrological model. Environmental Modelling and Software, 101, 51-63, doi:10.1016/j.envsoft.2017.11.033

Figure 1. Annual mean near-surface atmospheric maximum temperature bias (K) with respect to observations for the RCMs. Stippled areas indicate locations where an RCM shows statistically significant bias (P < 0.01).