气候变化领域集成服务门户(CCPortal): Evaluating reanalysis-driven CORDEX regional climate models over Australia: model performance and errors

CCPortal

DOI	10.1007/s00382-019-04672-w
	Evaluating reanalysis-driven CORDEX regional climate models over Australia: model performance and errors
	Di Virgilio G.; Evans J.P.; Di Luca A.; Olson R.; Argüeso D.; Kala J.; Andrys J.; Hoffmann P.; Katzfey J.J.; Rockel B.
发表日期	2019
ISSN	0930-7575
起始页码	2985
结束页码	3005
卷号	53 期号:2020-05-06
英文摘要	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. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
英文关键词	Australian climate; CORDEX-Australasia; Dynamical downscaling; Model bias; Precipitation; Temperature
语种	英语
scopus关键词	air temperature; climate modeling; downscaling; error analysis; numerical model; performance assessment; precipitation (climatology); regional climate; Australia
来源期刊	Climate Dynamics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/146046
作者单位	Climate Change Research Centre, University of New South Wales, Sydney, Australia; Australian Research Council Centre of Excellence for Climate Extremes, University of New South Wales, Sydney, Australia; Department of Atmospheric Sciences, Yonsei University, Seoul, South Korea; Center for Climate Physics, Institute for Basic Science, Busan, South Korea; Pusan National University, Busan, South Korea; Department of Physics, University of the Balearic Islands, Palma de Mallorca, Spain; Environmental and Conservation Sciences, Murdoch University, Murdoch, WA 6150, Australia; Climate Science Centre-CSIRO Oceans and Atmosphere, Aspendale, VIC, Australia; Climate Service Center Germany (GERICS), Helmholtz-Zentrum Geesthacht, Hamburg, Germany; Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Geesthacht, Germany
推荐引用方式 GB/T 7714	Di Virgilio G.,Evans J.P.,Di Luca A.,et al. Evaluating reanalysis-driven CORDEX regional climate models over Australia: model performance and errors[J],2019,53(2020-05-06).
APA	Di Virgilio G..,Evans J.P..,Di Luca A..,Olson R..,Argüeso D..,...&Rockel B..(2019).Evaluating reanalysis-driven CORDEX regional climate models over Australia: model performance and errors.Climate Dynamics,53(2020-05-06).
MLA	Di Virgilio G.,et al."Evaluating reanalysis-driven CORDEX regional climate models over Australia: model performance and errors".Climate Dynamics 53.2020-05-06(2019).