Large-Scale Predictors for Extreme Hourly Precipitation Events in Convection-Permitting Climate Simulations
Large-Scale Predictors for Extreme Hourly Precipitation Events in Convection-Permitting Climate Simulations
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DOI：
10.1175/jcli-d-17-0404.1
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发表时间：
2017-12
影响因子：
4.9
通讯作者：
S. Chan;E. Kendon;N. Roberts;S. Blenkinsop;H. Fowler
中科院分区：
文献类型：
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作者：
S. Chan;E. Kendon;N. Roberts;S. Blenkinsop;H. Fowler
摘要中纬度极端降水事件是由众所周知的气象驱动因素引起的，如垂直不稳定和低气压系统。原则上，动态天气和气候模型的行为方式相同，尽管可能对不同模型的驱动因素的敏感度有所不同。与参数化对流模式(PCM)不同，允许对流模式(CPM)能够真实地捕捉次日极端降水。CPM在计算上是昂贵的；能够诊断来自大尺度驱动因素的次日极端降水的发生，并具有足够的技能，将允许有效地针对CPM缩小尺度模拟。这里量化了极端每小时降水事件的发生与垂直稳定度和环流预报因子之间的回归关系，在联合王国南部1.5公里的中央气象站和12公里的中央气象站现在和未来的气候模拟。总体而言，大型预报员在预测气候变化的发生方面表现出了技巧。
AbstractMidlatitude extreme precipitation events are caused by well-understood meteorological drivers, such as vertical instability and low pressure systems. In principle, dynamical weather and climate models behave in the same way, although perhaps with the sensitivities to the drivers varying between models. Unlike parameterized convection models (PCMs), convection-permitting models (CPMs) are able to realistically capture subdaily extreme precipitation. CPMs are computationally expensive; being able to diagnose the occurrence of subdaily extreme precipitation from large-scale drivers, with sufficient skill, would allow effective targeting of CPM downscaling simulations. Here the regression relationships are quantified between the occurrence of extreme hourly precipitation events and vertical stability and circulation predictors in southern United Kingdom 1.5-km CPM and 12-km PCM present- and future-climate simulations. Overall, the large-scale predictors demonstrate skill in predicting the occurrence o...