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气象:2019,45(9):1199-1212
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广州“5·7”局地突发特大暴雨过程的数值可预报性分析
陈涛,孙军,谌芸,郭云谦,徐珺
(国家气象中心,北京 100081; 南方海洋科学与工程广东省实验室(珠海),珠海 519082)
Study on the Numerical Predictivity of Localized Severe Mesoscale Rainstorm in Guangzhou on 7 May 2017
CHEN Tao,SUN Jun,CHEN Yun,GUO Yunqian,XU Jun
(National Meteorological Centre, Beijing 100081; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082)
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投稿时间:2018-11-09    修订日期:2019-07-10
中文摘要: 2017年5月6日夜间至7日上午广州地区发生局地特大暴雨,分析表明对流触发与珠江口地区边界层南风增强等因素有密切关系。数值模式预报检验表明,ECMWF集合预报的强降水预报成员在初始条件上具有更显著的辐合上升、水汽和不稳定性条件,而GRAPES区域模式对6日20时初始场分析以及对边界层南风增强过程的预报都更为准确。集合敏感性分析表明,降水预报高敏感区分布与江南地区高压、南海高压以及华南低槽等关键天气系统的相对强度和位置有密切关系;降水对温度的预报敏感区主要位于关键区边界层内,近地面层到边界层底部温度越高、边界层顶越冷,越有利于对流不稳定性增强,有利于关键区内对流发展。通过3组探空预报试验分析了对流尺度降水预报关于初值热扰动、低层风场扰动和降水物理方案的敏感性,结果表明在特定环境条件下,与低层风场扰动试验组对比,降水预报对于初始热力扰动更为敏感;降水微物理方案预报试验表明,在小成员数的集合预报中物理方案扰动能够有效增大预报离散度。以上结果表明,分析对流尺度集合预报中各类初值扰动、物理扰动导致的预报变化和预报敏感性,能够更为全面地估计暖季中小尺度强降水事件的可预报性。
Abstract:Severe mesoscale rainstorm struck Guangzhou heavily from deep night of 6 May to early morning of 7 May 2017, and convection initiation was closely related to southerly wind enhancing in boundary layer near Pearl River Delta at night. Comparison between two sub groups in ECWMF ensemble forecasts shows members with strong rainfall have significant low level convergence, updraft, moist air and convective instability in initial conditions. GRAPES mesoscale model performed well in forecasting the dynamic process of southerly wind strengthening in lower level, producing good forecasts for the rainfall process. Ensemble sensitivity analysis reveals that the high sensitivity depends on the relative position, strength of key synoptic systems for high pressure in Yangtze River Basin, high pressure on South China Sea and low pressure trough residing on South China. Precipitation forecast sensitivity to temperature is closely relative to convective instability in boundary layer, the boundary structure with warmer air in near surface and colder air near the top of boundary layer would increase convective instability obviously. Three sets of convective scale simulations are applied to analyze sensitivity of convective precipitation forecast to initial thermal distur bance, low level wind disturbance, and cloud microphysical scheme differences. Convective precipitation forecast shows more sensitivities to initial thermal disturbance compared with low level wind disturbance, and forecast uncertainty could be estimated comprehensively through different cloud microphysical schemes. By carefully analyzing forecast sensitivity due to perturbations in initial conditions and physical process in the convective scale ensemble forecasts, the predictability of mesoscale heavy rainfall events in warm seasons could be improved.
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基金项目:国家重点研发计划(2017YFC1502103)和中国气象局暴雨专家创新团队专项(CMACXTD002-3)共同资助
引用文本:
陈涛,孙军,谌芸,郭云谦,徐珺,2019.广州“5·7”局地突发特大暴雨过程的数值可预报性分析[J].气象,45(9):1199-1212.
CHEN Tao,SUN Jun,CHEN Yun,GUO Yunqian,XU Jun,2019.Study on the Numerical Predictivity of Localized Severe Mesoscale Rainstorm in Guangzhou on 7 May 2017[J].Meteor Mon,45(9):1199-1212.