摘要
基于2019—2021年浙江省自动站观测资料和多模式预报数据,分析了各模式对梅汛期暴雨预报的综合表现,并采用12组降水订正方案开展了2020年和2021年浙江省梅汛期降水预报的客观订正,对比了各订正方案对模式暴雨预报的改进效果。结果表明:ECMWF、CMA-SH9和CMA-MESO梅汛期暴雨预报表现优于NCEP-GFS和CMA-GFS,且频率偏差关系稳定,可联合用于开展多模式预报客观订正;由于逐年梅汛期暴雨特征差异大,频率匹配算法无法对预报进行有效订正;最优评分法(OTS)能显著提升ECMWF模式暴雨预报TS评分,但空报率有所增加;对ECMWF降水预报经OTS量级订正后再开展基于集合平均的概率匹配订正,能明显改善以大雨带稳定性降水为主的梅汛期暴雨预报质量,但对于对流性较强的梅汛期暴雨过程订正效果不佳;优选预报成员的各类多模式融合算法均能够有效改进对流性较强的梅汛期暴雨过程预报质量,包括多模式平均、自适应集成和时滞集合预报在2020年和2021年均有明显正技巧;对各模式降水预报经OTS订正后再开展集成预报能够进一步提高梅汛期暴雨预报质量,且对稳定性暴雨和对流性暴雨过程均有较好的订正能力,其中经多模式时滞集合分级订正算法集成OTS量级订正预报表现最优。
Based on the 2019-2021 rainfall observation and forecasts from multiple NWP models in Zhejiang Province,the performances of five operational models in forecasting torrential rains during the Meiyu period are analyzed.The 12 objective correction schemes are used to hindcast forecasts for the 2020 and 2021 Meiyu periods in Zhejiang,and are comparatively analyzed through the compressive evaluation.The results demonstrate that the skills of ECMWF,CMA-SH9 and CMA-MESO models are better than NCEP-GFS and CMA-GFS models in forecasting the torrential rains in the Meiyu period,and they have stable frequency bias relationships,therefore picked out for objective correction.Frequency matching fails to improve torrential rain quality because of the significant interannual variation in characteristics of torrential rains in the Meiyu period.The optimal score method(OTS)can improve the TS score of ECMWF rainfall forecast obviously,but its false alarm ratio is raised.The probability matching correction based on ECMWF ensemble average and corrected forecast by OTS performs good skills in improving the forecast quality of the torrential rains in Meiyu period when steady torrential rain events with large rain bands are the dominant,but its correction is not effective for the convective-dominated torrential rain events.Various multi-model fusion schemes of preferred models,including multi-model averaging,adaptive integration and time-lagged ensemble forecast,can effectively improve the forecast quality of convective-dominated torrential rain events in the 2020 and 2021 Meiyu periods.Those schemes of multi-model fusion integrating OTS corrected models further improve the forecast skill for both steady and convective-dominated torrential rain events.Among them,the time-lagged ensemble algorithm integrating OTS corrected models has the best skill.
作者
沈文强
钱浩
马昊
孙长
叶延君
SHEN Wenqiang;QIAN Hao;MA Hao;SUN Zhang;YE Yanjun(Zhejiang Meteorological Observatory,Hangzhou 310051;Lanxi Meteorological Office of Zhejiang Province,Jinhua 321100)
出处
《气象》
CSCD
北大核心
2023年第6期697-707,共11页
Meteorological Monthly
基金
浙江省自然科学基金联合基金项目(LZJMD23D050001)
国家自然科学基金青年项目(42105011)
浙江省气象科技计划重点项目(2022ZD01、2021ZD02)共同资助。
关键词
客观订正
梅雨
暴雨
频率匹配
概率匹配
最优评分法
多模式集成
时滞集合预报
quantitative precipitation forecast
Meiyu
torrential rain
frequency matching
probability matching
optimal score method(OTS)
multi-model fusion
time-lagged ensemble forecast
