Evaluating reanalysis-driven CORDEX regional climate models over Australia: model performance and errors

Show simple item record

dc.contributor.author Evans, Jason P.
dc.contributor.author Di Virgilio, Giovanni
dc.contributor.author Di Luca, Alejandro
dc.contributor.author Olson, Roman
dc.contributor.author Argüeso, Daniel
dc.contributor.author Kala, Jatin
dc.contributor.author Andrys, Julia
dc.contributor.author Hoffmann, Peter
dc.contributor.author Katzfey, Jack J.
dc.contributor.author Rockel, Burkhardt
dc.date.accessioned 2020-02-04T12:03:51Z
dc.date.available 2020-02-04T12:03:51Z
dc.date.issued 2020-02-04
dc.identifier.uri http://hdl.handle.net/11201/150813
dc.description.abstract [eng] 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.
dc.subject 53 - Física ca
dc.title Evaluating reanalysis-driven CORDEX regional climate models over Australia: model performance and errors ca
dc.type info:eu-repo/semantics/article
dc.subject.keywords Australian climate, CORDEX-Australasia, Dynamical downscaling, Model bias, Precipitation, Temperature
dc.identifier.doi https://doi.org/10.1007/s00382-019-04672-w

Files in this item

This item appears in the following Collection(s)

Show simple item record

Search Repository

Advanced Search


My Account