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

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Title
Evaluating reanalysis-driven CORDEX regional climate models over Australia: model performance and errors
Author(s)
Di Virgilio, Giovanni; Evans, Jason P.; Di Luca, Alejandro; Roman Olson; Argueeso, Daniel; Kala, Jatin; Andrys, Julia; Hoffmann, Peter; Katzfey, Jack J.; Rockell, Burkhardt
Publication Date
2019-09
Journal
CLIMATE DYNAMICS, v.53, no.5-6, pp.2985 - 3005
Publisher
SPRINGER
Abstract
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.
URI
https://pr.ibs.re.kr/handle/8788114/10578
DOI
10.1007/s00382-019-04672-w
ISSN
0930-7575
Appears in Collections:
Center for Climate Physics(기후물리 연구단) > 1. Journal Papers (저널논문)
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