A first-of-its-kind multi-model convection permitting ensemble for investigating convective phenomena over Europe and the Mediterranean
A first-of-its-kind multi-model convection permitting ensemble for investigating convective phenomena over Europe and the Mediterranean
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DOI：
10.1007/s00382-018-4521-8
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发表时间：
2020-07-01
期刊：
影响因子：
4.6
通讯作者：
Warrach-Sagi, K.
中科院分区：
文献类型：
--
作者：
Coppola, Erika;Sobolowski, Stefan;Warrach-Sagi, K.
介绍了最近在世界气候研究计划 (WCRP) 协调区域降尺度实验旗舰试点研究计划 (CORDEX-FPS) 赞助下启动的项目。该倡议旨在建立首个对流允许模型的集合气候实验，以研究欧洲和地中海当前和未来的对流过程以及相关极端情况。在这份手稿中，介绍了基本原理、科学目标和方法，以及该项目测试阶段的一些初步结果。选择了三个测试用例，以便初步了解整体性能。测试案例涵盖了奥地利夏季极端降水事件、瑞士阿尔卑斯山秋季焚风事件以及地中海沿岸详细记录的秋季事件。测试用例在“类天气”（WL，在相关事件发生前初始化）和“气候”（CM，在事件发生前 1 个月初始化）模式下运行。为测试用例生成了由 18-21 名成员组成的集合，代表具有不同物理和建模链选项的六种不同的建模系统（27 个建模团队已承诺执行更长的气候模拟）。结果表明，在 WL 模式下运行时，集成很好地捕获了所有三个事件，集成相关技能得分为 0.67、0.82 和 0.91。他们认为，事件越是由大规模条件驱动，团体成员之间的协议就越接近。即使在气候模式下，瑞士阿尔卑斯山和地中海沿岸的大规模驱动事件仍然会被捕获（集合相关技能得分分别为 0.90 和 0.62），但模型间的分布如预期的那样增加。就地中海地区而言，局部尺度的水流、地形和陆地-海洋对比之间相互作用的影响是显而易见的。然而，奥地利事件的传播幅度要大得多，尽管这并不奇怪，而大规模流动的推动微弱。尽管集成相关技能得分仍然很高（0.80）。初步结果说明了对流允许建模所面临的前景和挑战，并为基于集合的方法来研究高影响对流过程提供了强有力的论据。
A recently launched project under the auspices of the World Climate Research Program's (WCRP) Coordinated Regional Downscaling Experiments Flagship Pilot Studies program (CORDEX-FPS) is presented. This initiative aims to build first-of-its-kind ensemble climate experiments of convection permitting models to investigate present and future convective processes and related extremes over Europe and the Mediterranean. In this manuscript the rationale, scientific aims and approaches are presented along with some preliminary results from the testing phase of the project. Three test cases were selected in order to obtain a first look at the ensemble performance. The test cases covered a summertime extreme precipitation event over Austria, a fall Foehn event over the Swiss Alps and an intensively documented fall event along the Mediterranean coast. The test cases were run in both "weather-like" (WL, initialized just before the event in question) and "climate" (CM, initialized 1 month before the event) modes. Ensembles of 18-21 members, representing six different modeling systems with different physics and modelling chain options, was generated for the test cases (27 modeling teams have committed to perform the longer climate simulations). Results indicate that, when run in WL mode, the ensemble captures all three events quite well with ensemble correlation skill scores of 0.67, 0.82 and 0.91. They suggest that the more the event is driven by large-scale conditions, the closer the agreement between the ensemble members. Even in climate mode the large-scale driven events over the Swiss Alps and the Mediterranean coasts are still captured (ensemble correlation skill scores of 0.90 and 0.62, respectively), but the inter-model spread increases as expected. In the case over Mediterranean the effects of local-scale interactions between flow and orography and land-ocean contrasts are readily apparent. However, there is a much larger, though not surprising, increase in the spread for the Austrian event, which was weakly forced by the large-scale flow. Though the ensemble correlation skill score is still quite high (0.80). The preliminary results illustrate both the promise and the challenges that convection permitting modeling faces and make a strong argument for an ensemble-based approach to investigating high impact convective processes.