Journal of Arid Meteorology ›› 2021, Vol. 39 ›› Issue (3): 507-513.

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Extreme Short-time Heavy Precipitation Forecast Based on GRAPES-MESO Model

ZHANG Wulong1,2, KANG Lan1,2, ZHOU Wei1,2, YIN Hang1,2   

  1. 1.Sichuan Provincial Meteorology Observatory, Chengdu 610072, China;
    2.Heavy Rain and Drought-Flood Disaster in Plateau and Basin Key
     Laboratory of Sichuan Province, Chengdu 610072, China
  • Online:2021-06-30 Published:2021-07-16

基于GRAPES-MESO模式的极端短时强降水预报

张武龙1,2,康岚1,2,周威1,2,银航1,2   

  1. 1.四川省气象台,四川成都610072;
    2.高原与盆地暴雨旱涝灾害四川省重点实验室,四川成都610072

Abstract: Based on hourly precipitation data from 109 meteorological stations in Sichuan basin and 3-hourly forecast data with 0.1°×0.1° spatial resolution from GRAPESMESO model from May to September during 2017-2018, this study investigated the characteristic of key physical parameters of the occurrence and development of extreme shorttime heavy precipitation (hourly precipitation amount ≥50 mm), such as thermal instability, water vapor and dynamic conditions. A prediction model was established using random probability thought and principal component analysis method to develop the extreme shorttime heavy precipitation probability forecast product. The forecast effect evaluation showed that the TS was 24.0% when the probability was greater than or equal to 0.7. The value could be used as the reference threshold for the extreme shorttime heavy precipitation forecast. During the rainstorm process in Sichuan basin on 22 July 2019, the practical application indicated that the product had good reference meaning for the forecast of extreme shorttime heavy precipitation location.

Key words: extreme shorttime heavy precipitation, GRAPESMESO, Sichuan basin, forecast product

摘要: 利用2017—2018年5—9月四川盆地109个自动站逐小时降水资料,以及GRAPESMESO模式0.1°×0.1°的逐3 h预报场资料,从热力不稳定、水汽、动力条件等方面分析极端短时强降水(1 h降水量大于等于50 mm)发生发展所需的关键物理量指标,结合随机事件概率思想和主成分分析方法构建预报模型,研发极端短时强降水概率预报产品。经预报效果评估,当概率值达0.7以上时,TS评分为24.0%,可将其作为极端短时强降水预报的参考阈值。2019年7月22日四川盆地暴雨过程应用表明,该产品对极端短时强降水落区有较好的参考意义。

关键词: 极端短时强降水, GRAPESMESO, 四川盆地, 预报产品