Evaluating reanalysis-driven CORDEX regional climate models over Australia: model performance and errors
The ability of regional climate models (RCMs) to accurately simulate current and future climate is increasingly important for impact assessment. This is the first evaluation of all reanalysis-driven RCMs within the CORDEX Australasia framework [four configurations of the Weather Forecasting and Research (WRF) model, and single configurations of COSMO-CLM (CCLM) and the Conformal-Cubic Atmospheric Model (CCAM)] to simulate the historical climate of Australia (1981–2010) at 50 km resolution. Simulations of near-surface maximum and minimum temperature and precipitation were compared with gridded observations at annual, seasonal, and daily time scales. The spatial extent, sign, and statistical significance of biases varied markedly between the RCMs. However, all RCMs showed widespread, statistically significant cold biases in maximum temperature which were the largest during winter. This bias exceeded − 5 K for some WRF configurations, and was the lowest for CCLM at ± 2 K. Most WRF configurations and CCAM simulated minimum temperatures more accurately than maximum temperatures, with biases in the range of ± 1.5 K. RCMs overestimated precipitation, especially over Australia’s populous eastern seaboard. Strong negative correlations between mean monthly biases in precipitation and maximum temperature suggest that the maximum temperature cold bias is linked to precipitation overestimation. This analysis shows that the CORDEX Australasia ensemble is a valuable dataset for future impact studies, but improving the representation of land surface processes, and subsequently of surface temperatures, will improve RCM performance. The varying RCM capabilities identified here serve as a foundation for the development of future regional climate projections and impact assessments for Australia.
KeywordsAustralian climate CORDEX-Australasia Dynamical downscaling Model bias Precipitation Temperature
We thank the NCAR Mesoscale and Microscale Meteorology Division for developing and maintaining WRF. We thank Marcus Thatcher and John McGregor at CSIRO Oceans and Atmosphere for developing CCAM, for help with the post-processing software to produce the CORDEX output, and for helpful discussions regarding CCAM. Logistical support was provided by the Climate Change Research Centre at the University of New South Wales, by the National Computing Infrastructure National Facility at Australian National University and by the Pawsey Supercomputing Centre. This project is supported through funding from the Earth Systems and Climate Change Hub of the Australian Government’s National Environmental Science Programme and the NSW government Office of Environment and Heritage. JK is supported by an Australian Research Council (ARC) Discovery Early Career Researcher Grant (DE170100102). AD is also supported by ARC Grant (DE170101191). RO was supported by the Basic Science Research Program through National Research Foundation of Korea (NRF-2017K1A3A7A03087790), and through the Institute for Basic Science (project code IBS-R028-D1). DA received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant agreement no. 743547. We thank two anonymous reviewers for their constructive feedback on this manuscript.
JE, AD, RO and DA designed and ran the UNSW WRF experiments. JK and JA ran the MU WRF experiments. PH and JJK ran the CCAM experiment. GD and JE conceived the research aims. GD designed and performed the analyses. GD prepared the manuscript with contributions from all co-authors.
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Conflict of interest
The authors declare that they have no conflict of interest.
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