| 2016-2020年广东省定量降水预报检验评估 |
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| 引用本文： | 汪瑛,胡胜,涂静,曾沁,张红艳,黄晓莹,龚月婷,张华龙.2016-2020年广东省定量降水预报检验评估[J].热带气象学报,2021,37(2):154-165. |
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| 作者姓名： | 汪瑛 胡胜 涂静 曾沁 张红艳 黄晓莹 龚月婷 张华龙 |
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| 作者单位： | 1.广东省气象台，广东 广州 510641 |
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| 基金项目： | 广东省科技计划项目2019B020208016广东省科技计划项目2018B020207012广东省气象局科技项目GRMC2018Z05广东省气象局智能网格预报技术创新团队GRMCTD202004 |
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| 摘 要： | 对2016-2020年全球模式ECMWF和区域模式GZ_GRAPES、基于模式的解释应用和广东省气象局发布的定量降水预报（QPF）进行检验和评估。结果表明:ECMWF和GZ_GRAPES模式对一般性降水预报技巧在逐年提升，对大雨或以上的降水预报技巧的提升缓慢。GZ_GRAPES对大雨以上降水的预报技巧和定量降水预报的精细时空分布均优于ECMWF，区域模式更易预报出中小尺度降水信息。分类暴雨评定表明，模式对台风暴雨预报最好、锋面暴雨次之、季风暴雨预报最差。模式的暴雨预报落区偏小、低估明显，预报员通过经验订正明显提升了暴雨预报评分，其中季风暴雨的订正量最大，但存在预报范围偏大、空报较高的问题。基于ECMWF集合预报的解释应用与预报员的定量降水预报能力相当，降水越强，解释应用技术的优势越明显，但对季风暴雨也存在严重低估或漏报。目前降水精细时空分布、季风暴雨、极端性暴雨等依然靠预报员的经验订正为主，随着集合预报模式和区域高分辨率模式能力的提升，将预报经验客观化并与数值预报解释应用技术结合是提升QPF的一个方向。
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| 关 键 词： | 定量降水预报 暴雨 模式解释应用 检验和评估 预报员作用 |
| 收稿时间： | 2020-12-11 |
VERIFICATION AND EVALUATION OF QUANTITATIVE PRECIPITATION FORECAST FOR GUANGDONG PROVINCE DURING 2016-2020 |
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| WANG Ying,HU Sheng,TU Jing,ZENG Qin,ZHANG Hong-yan,HUANG Xiao-ying,GONG Yue-ting,ZHANG Hua-long.VERIFICATION AND EVALUATION OF QUANTITATIVE PRECIPITATION FORECAST FOR GUANGDONG PROVINCE DURING 2016-2020[J].Journal of Tropical Meteorology,2021,37(2):154-165. |
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| Authors: | WANG Ying HU Sheng TU Jing ZENG Qin ZHANG Hong-yan HUANG Xiao-ying GONG Yue-ting ZHANG Hua-long |
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| Affiliation: | 1.Guangdong Meteorological Observatory, Guangzhou 510641, China2.Guangzhou Institute of Tropical and Marine Meteorology, Guangzhou 510641, China3.National Meteorological Information Centre, Beijing 100080, China |
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| Abstract: | The present study examines and evaluates the 2016-2020 global model ECMWF and regional model GZ_GRAPES, model-based interpretation and application, and quantitative precipitation forecasts (QPF) issued by forecasters from the Guangdong Meteorological Service. The results show that the forecast skill of QPF (< 25mm) by the ECMWF and GZ_GRAPES increases year by year and the skill of QPF (≥25mm) varies from year to year. The GZ_GRAPES forecast skill for precipitation stronger than heavy rain and the fine temporal and spatial distribution of QPF are better than those of the ECMWF, and it is easier for the regional model to forecast small and medium-scale precipitation. Classified rainstorm evaluation shows that the models have the best forecast for typhoon rain, followed by frontal rainstorm and monsoon rain. The models'rainstorm forecast underestimates the rainfall area, and the underestimation is obvious. Forecasters have significantly improved the rainstorm forecast score through empirical corrections. Among them, the amount of correction for monsoon rain is the largest, but there are problems of a large forecast range and high false alarms. The interpretation and application based on the ECMWF ensemble forecast is equivalent to the QPF ability of forecasters. The stronger the precipitation, the more obvious the advantages of model interpretation and application, but there is also serious underestimation or underreporting of the monsoon rain. At present, the precise temporal and spatial distribution of precipitation, monsoon rains and extreme rainstorms still rely mainly on the empirical correction of forecasters. With the improvement of the capabilities of ensemble forecasting models and regional high-resolution models, forecasts will become more objective, which, combined with numerical forecasting techniques, can help improve QPF. |
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| Keywords: | quantitative precipitation forecast heavy rain model-based interpretation and application verification and evaluation the role of forecasters |
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