| 辽宁省夏季多模式降水预报检验及晴雨预报技术研究 |
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| 引用本文： | 聂安祺,李得勤,滕方达,陆井龙,王当.辽宁省夏季多模式降水预报检验及晴雨预报技术研究[J].气象与环境学报,2020,36(5):10-17. |
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| 作者姓名： | 聂安祺 李得勤 滕方达 陆井龙 王当 |
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| 作者单位： | 1. 中国气象局沈阳大气环境研究所, 辽宁 沈阳 1101662. 东北冷涡研究重点开放实验室, 辽宁 沈阳 1101663. 辽宁省气象台, 辽宁 沈阳 1101664. 中国气象局气象干部培训学院辽宁分院, 辽宁 沈阳 110166 |
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| 基金项目： | 辽宁省气象局重点科研项目;中国气象局沈阳大气环境研究所东北冷涡研究重点开放实验室联合开放基金课题 |
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| 摘 要： | 利用辽宁省291个国家气象观测站的降水资料，对2019年夏季（6-9月）8种模式降水预报及中央气象台格点降水预报进行了检验评估和比较，并采用消空方法进行晴雨预报技术研究。结果表明：2019年，EC模式具有最优的暴雨预报性能，而日本模式暴雨TS评分最高；中尺度模式对于局地性暴雨和短时强降水具有较好的预报潜力，性能较好的是GRAPES_MESO模式和睿图东北3 km模式；全球模式对24 h暴雨的预报频率比实况偏低30%，3 h强降水则偏低60%，中尺度模式对24 h暴雨的预报频率比实况偏高30%，3 h强降水则偏低20%。由于对小量级降水存在较多空报，各模式原始预报的晴雨预报大多呈现空报偏多的情况；使用小量级降水剔除的消空策略能够明显提高晴雨准确率，消空之后EC模式具有最优的晴雨预报性能。分别使用24 h和3 h累计降水量优化消空策略，发现分别取1.0 mm和0.8 mm的阈值进行消空可以使24 h晴雨准确率提高15.58%，3 h晴雨准确率提高10%-30%。
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| 关 键 词： | 暴雨 降水预报 检验 降水消空 |
| 收稿时间： | 2020-05-08 |
Verification of multi-model precipitation forecast in Liaoning province in summer and research on clear or rain forecast method |
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| An-qi NIE,De-qin LI,Fang-da TENG,Jing-long LU,Dang WANG.Verification of multi-model precipitation forecast in Liaoning province in summer and research on clear or rain forecast method[J].Journal of Meteorology and Environment,2020,36(5):10-17. |
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| Authors: | An-qi NIE De-qin LI Fang-da TENG Jing-long LU Dang WANG |
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| Institution: | 1. Institute of Atmospheric Environment, China Meteorological Administration, Shenyang 110166, China2. Key Opening Laboratory for Northeast China Cold Vortex Research, Shenyang 1101663. Liaoning Meteorological Observatory, Shenyang 110166, China4. Liaoning Branch of China Meteorological Administration Training Centre, Shenyang 110166, China |
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| Abstract: | Based on precipitation data observed at 291 national meteorological stations from June to September in 2019, we verified the precipitation forecasts from eight numerical models as well as the precipitation grid forecast released from the National Meteorological Center.We also studied the clear or rain forecasts based on the eliminating false alarm ratio (FAR) method.The results showed that the European Center for Medium-range Weather Forecast (ECMWF) model has the best precipitation forecast performance, and the Japan Model has the highest threat score (TS) among all the models.Some mesoscale models show good potential forecast on the local and short-time heavy rainfall events, among which the GRAPES_MESO model and the RMAPS Dongbei-3km model have better performance.The 24- and 3-h occurrence frequency of the heavy rainfall events predicted by the global model is 30% and 60% lower than the real situations, respectively, and that predicted by the mesoscale models is 30% higher and 20% lower than the real conditions, respectively.The false alarm ratio (FAR) for small precipitation events is high, leading to a high false alarm ratio for clear or rain events among the all models.The clear or rain forecast accuracy can be improved significantly using the method of eliminating FAR of small precipitation events.Based on this method, the ECMWF model has the best clear or rain forecast performance among the all models.The optimized eliminating thresholds for 24- and 3-h precipitation forecast are 1.0 mm and 0.8 mm, respectively, and the clear or rain accuracy can be promoted by 15.58% for the 24-h forecast, and by 10%-30% for the 3-h forecast. |
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| Keywords: | Heavy rainfall Precipitation forecast Verification Eliminating false alarm ratio of precipitation |
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