Reanalysis-driven regional climate simulations using the Weather Research and Forecasting (WRF) model in New South Wales (NSW) and Australian Regional Climate Modelling (NARCliM) Version 2.0 are assessed for capturing precipitation extreme indices. Seven configurations of the WRF model driven by ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis v5 (ERA5) for Australia from 1979 to 2020 at 20 km resolution are evaluated. We assess the spatiotemporal patterns of six selected Expert Team on Sector-Specific Climate Indices (ET-SCI) precipitation extremes by comparing regional climate model (RCM) simulations against gridded observations. The RCMs evaluated have varying levels of accuracy in simulating precipitation extremes. While they capture climatology and coefficient of variation of precipitation extremes relatively well, temporal correlation and trend reproduction present challenges. Some RCMs perform more effectively for specific extreme indices, while others encounter challenges in accurately replicating them. No single RCM excels in all aspects, highlighting the need to consider specific strengths when selecting RCMs for global climate model (GCM) driven simulations.

中文翻译：

---

在 ERA5 再分析驱动的 CORDEX-澳大利亚域区域气候模拟中评估极端降水量


使用新南威尔士州 (NSW) 天气研究和预报 (WRF) 模型和澳大利亚区域气候模型 (NARCliM) 2.0 版对再分析驱动的区域气候模拟进行评估，以获取极端降水指数。对 1979 年至 2020 年澳大利亚 ECMWF（欧洲中期天气预报中心）再分析 v5 (ERA5) 驱动的 WRF 模型的七种配置进行了评估，分辨率为 20 公里。我们通过将区域气候模型（RCM）模拟与网格观测进行比较，评估了六个选定的部门特定气候指数（ET-SCI）极端降水专家组的时空模式。评估的 RCM 在模拟极端降水方面具有不同程度的准确度。虽然它们相对较好地捕获了极端降水的气候学和变异系数，但时间相关性和趋势再现提出了挑战。一些 RCM 对于特定的极端指数表现更有效，而另一些则在准确复制它们方面遇到挑战。没有任何一个 RCM 在所有方面都表现出色，这凸显了在为全球气候模型 (GCM) 驱动的模拟选择 RCM 时需要考虑特定优势。