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ERA5-Land降水再分析资料在中国西南地区的适用性评估

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为了探究欧洲中期天气预报中心第五代陆面再分析ERA5-Land(ERA5L)降水资料在中国西南的四川、重庆、贵州、云南及西藏5省(区、市)的适用性.以2018-2020年中国气象局441个国家级地面站雨量器自动观测数据为参考基准,使用Pearson相关系数、平均相对误差、均方根误差、命中率、空报率以及临界成功指数评分,对ERA5L降水资料在评估时段内各区域和站点的整体精度、不同海拔、不同时间尺度(月、季),以及不同量级降水的特征和偏差进行分析.结果表明:(1)ERA5L降水资料能较好反映西南区域的降水变化特征,但相对站点观测存在不同程度的偏高,以西藏地区最为明显.(2)在四川盆地,ERA5L降水与站点观测相关性高、误差较小,在西藏、云南、贵州及四川西部的地形复杂山区,误差相对较大.(3)ERA5L降水的误差存在明显的月变化特征,从7月开始到次年的2月,平均相对误差随降水总量的降低而增加,命中率减小、空报率增大,随后从2-7月,平均相对误差又随着降水量的增大而减小,命中率增加、空报率减少;各省(区、市)在不同季节质量表现不一,春季和秋季重庆相对表现最优,夏季贵州最优,冬季四川最优.(4)相对站点观测,ERA5L降水在小雨量级高估;在中雨及以上量级低估,且随着雨强的增大,低估现象更为严重.综合来看,ERA5L降水再分析资料在西南区域表现出一定的应用潜力,在不同海拔的质量排序为:低海拔>中海拔>高海拔;在西南5省(区、市)适用性排序为:重庆>贵州>四川>云南>西藏.
The Applicability Performance of the ERA5-Land Precipitation Datasets in Southwest China
ERA5L precipitation reanalysis datasets were provided by the European Centre for Medium-Range Weather Forecasts(ECMWF)Fifth Generation Land Surface Reanalysis(ERA5L).An investigation of the ap-plicability of ERA5L precipitation reanalysis datasets produced for Sichuan,Chongqing,Guizhou,Yunnan and Xizang in Southwest China has been conducted.Statistical metrics,including Pearson correlation coefficients(CCs),mean relative deviations(MREs),root mean square errors(RMSEs),probability of detections(PODs),false alarm rates(FARs),and critical success indices(CSIs),were employed to assess the features and accuracy of ERA5L precipitation data using 441 national ground stations of the China Meteorological Admin-istration between 2018 and 2020.The characteristics and deviations of ERA5L precipitation data were analysed in aspects of different regions,stations,altitudes,and timescales(monthly and seasonal)in our assessment phase.The following insights were revealed:(1)ERA5L better represents precipitation changes in the south-western region;however,it tends to show higher precipitation levels than the in-situ observations,especially in Xizang.(2)In the Sichuan Basin,high correlation has been found between ERA5L precipitation data and in-situ observations,with a small error.The areas of Xizang,Yunnan,Guizhou and Western Sichuan are characterized by complex terrains and mountainous regions.The ERA5L data here has a relatively higher error.(3)The ERA5L exhibits a clear monthly variation in error,with a decline in overall precipitation leading to higher MRE,lower POD,and increased FAR from July to February.The MRE decreases,the POD increases,and the FAR rate decreases as precipitation increases from February to July.The quality of ERA5L varies between provinces and seasons.There is excellent precipitation quality in Chongqing during spring and autumn,and in Guizhou and Sichuan during summer and winter.(4)ERA5L precipitation is overestimated compared to in-situ observations in light rain magnitude,but underestimated in moderate and above-moderate rain.The underestimate becomes more severe as the rain intensity increases.As a whole,ERA5L has the potential for various applications in Southwest China.The hierarchy of ERA5L precipitation quality from high to low occurs in the following order:low altitude,medium altitude,and high altitude.In the context of five provinces,the order of applicability from high to low is as follows:Chongqing,Guizhou,Sichuan,Yunnan,and Xizang.

precipitationERA5-Landreanalysis dataapplicability assessment

黄晓龙、吴薇、许剑辉、李施颖、蒋雨荷、杜冰、王丽伟

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四川省气象探测数据中心,四川成都 610072

高原与盆地暴雨旱涝灾害四川省重点实验室,四川成都 610072

广东省科学院广州地理研究所,广东广州 510070

吉林省气象信息网络中心,吉林长春 130062

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降水 ERA5-Land 再分析资料 适用性评估

四川省科技厅重点研发计划项目中国气象局创新发展专项中国气象局创新发展专项高原与盆地暴雨旱涝灾害四川省重点实验室科技发展基金重大专项

2022YFS0541CXFZ2021Z007CXFZ2023J067SCQXKJZD202102

2023

高原气象
中国科学院寒区旱区环境与工程研究所

高原气象

CSTPCDCSCD北大核心
影响因子:2.193
ISSN:1000-0534
年,卷(期):2023.42(6)
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