This study applies a benchmarking framework to assess a 39-member ensemble of regional climate models which have dynamically downscaled CMIP6 models over the CORDEX Australasian region. Four modelling centres contributed regional climate models to this ensemble using three regional climate models (CCAM, WRF, and BARPA-R), and a total of five model configurations. Assessment is conducted over the Australian continent using a separation into four major climate zones over a 30 year historical climatological period (1985-2014). Rainfall and near-surface temperatures are compared against six benchmarks measuring mean state patterns, spatial and temporal variance, seasonal cycles, long-term trends and selected extreme indices. Benchmark thresholds are derived either from previous studies or comparison with the driving model ensemble. Major model biases vary between ensemble members and include dry biases in northern and southern Australia, winter wet biases and a persistent low bias in the winter diurnal temperature range across all the modelling centres. Daily variability at large length-scales is comparable in the driving global climate model and downscaled regional climate model length-scales, and long-term trends are largely determined by the driving global climate model. Overall, the ensemble was deemed to be fit for purpose for impact studies. Strengths and weaknesses of the systematic benchmarking framework used here are discussed.

Quantifying warming of the Earth’s climate system since the late 19th century and the ratio of regional to global warming are required when examining implications of Paris Agreement global warming targets. To estimate these terms reliably, the limitations in quality and length of observed records, differences between climate models and observations, and different results dependent on temporal and forcing contexts must be taken into account. Here we use observational datasets currently available back to 1860 and the latest set of global climate model simulations from CMIP5/6 to examine the warming of Australia in the past and projected future. We find that Australia has warmed by 1.5 °C (1.3–1.8 °C) during 1850 - 2019, at a ratio of ~1.4 times the global warming of ~1.1 °C. Models generally produce a lower ratio of Australian to global warming than in observations, which may be related to model biases or internal climate variability.

Outputs from new state-of-the-art climate models under the Coupled Model Inter-comparison Project phase 6 (CMIP6) promise improvement and enhancement of climate change projections information for Australia. Here we focus on three key aspects of CMIP6: what is new in these models, how the available CMIP6 models evaluate compared to CMIP5, and their projections of the future Australian climate compared to CMIP5 focussing on the highest emissions scenario. The CMIP6 ensemble has several new features of relevance to policy-makers and others, for example the integrated matrix of socio-economic and concentration pathways. The CMIP6 models show incremental improvements in the simulation of the climate in the Australian region, including a reduced equatorial Pacific cold-tongue bias, slightly improved rainfall teleconnections with regional climate drivers, improved representation of atmosphere and ocean extreme heat events, as well as dynamic sea level. However, important regional biases remain, evident in the excessive precipitation over the Maritime Continent and precipitation pattern biases in the nearby tropical convergence zones. Projections of temperature and rainfall from the available CMIP6 ensemble broadly agree with those from CMIP5, except for a group of CMIP6 models with higher climate sensitivity and greater warming and increase in some extremes after 2050. CMIP6 rainfall projections are similar to CMIP5, but the ensemble examined has a narrower range of rainfall change in summer in the north and winter in the south. Overall, future national projections are likely to be similar to previous versions but perhaps with some areas of improved confidence and clarity.