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Sensitivity of a mesoscale model to different convective parameterization schemes in a heavy rain event

机译:暴雨事件中尺度模型对不同对流参数化方案的敏感性

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摘要

The Valencia region, on the Mediterranean coast of the Iberian Peninsula, is propitious to heavy precipitation, especially the area encompassing the South of Valencia province and the North of the Alicante province. In October 2007 a torrential rain affected the aforementioned area, producing accumulated rainfall values greater than 400 mm in less than 24 h and flash-floods that caused extensive economic losses and human casualties. This rain event has been studied in numerical experiments using the Regional Atmospheric Modeling System. The present paper deals with the effect of using the different convective parameterizations (CP) currently implemented in the Regional Atmospheric Modeling System (Kuo and Kain-Fritsch) in the forecast results, in particular on precipitation forecast. Sensitivity tests have been run with and without these parameterizations activated in a series of combinations of the different grids. Results are very different depending on the model convective parameterization setting. A statistical verification has also been undertaken by calculating different skill scores for each simulation in the experiment.
机译:伊比利亚半岛地中海沿岸的瓦伦西亚地区有利于大量降雨,特别是包括瓦伦西亚省南部和阿利坎特省北部的地区。 2007年10月,一场暴雨影响了上述地区,在不到24小时的时间内产生了超过400毫米的累积降雨,山洪暴发,造成了广泛的经济损失和人员伤亡。已经使用区域大气模拟系统在数值实验中研究了这种降雨事件。本文讨论了在预报结果中使用目前在区域大气模拟系统(Kuo和Kain-Fritsch)中实施的不同对流参数化(CP)的影响,特别是对降水预报的影响。在有或没有以不同网格的一系列组合激活这些参数设置的情况下,已经进行了灵敏度测试。结果取决于模型对流参数设置的不同。通过为实验中的每个模拟计算不同的技能得分,还可以进行统计验证。

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