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气象:2020,46(6):753-764
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多数值模式对台风暴雨过程预报的空间检验评估
王新敏,栗晗
(中国气象局·河南省农业气象保障与应用技术重点开放实验室,郑州 450003; 河南省气象台,郑州 450003)
Spatial Verification Evaluation of Typhoon Rainstorm by Multiple Numerical Models
WANG Xinmin,LI Han
(Henan Key Laboratory of Agrometeorological Support and Applied Technique, CMA, Zhengzhou 450003; Henan Meteorological Observatory, Zhengzhou 450003)
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投稿时间:2019-02-26    修订日期:2019-10-25
中文摘要: 采用FSS评分(fractional skill score)和CRA方法(contiguous rain area)结合国家气象信息中心地面、卫星、雷达三源降水融合产品(CMPA_Hourly V2.1),对SHANGHAI_HR(SH)、GRAPES_MESO(MESO)、ECMWF_HR(EC)、GRAPES_GFS(GFS)四个模式2018年8月三次登陆台风暴雨过程的的降水预报进行了检验评估,对比分析了各模式的预报性能,得到结论如下:FSS评分相较于传统TS评分能够更好地通过量化的方式反映出不同模式的预报能力差别,而CRA方法能更全面详细地评估模式的误差来源;区域模式对于局地性强降水或大尺度降水的强中心预报相对于全球模式有一定优势,但全球模式对于较小量级降水的范围预报可参考性更好;对于“摩羯“、“温比亚”台风影响的两次过程,EC模式的预报位移误差明显偏西,同样的特征也表现在MESO和GFS对于“温比亚”台风影响的降水的预报;GFS模式对于降水范围、降水强度预报偏小、偏弱,EC模式预报略好于GFS模式但对于降水极值估计仍存在不足。相对而言,区域模式对于极值估计优于全球模式,SH模式对于极值的估计要优于MESO模式,但其预报降水存在范围、强度偏大的特征;大部分模式预报降水个体的误差主要来源于位移误差,强度误差和形态误差大致相当。
Abstract:Precipitation forecast of three typhoon rainfall processes affecting Henan Area in August 2018 from four numerical models, SHANGHAI_HR(SH), GRAPES_MESO(MESO), ECMWF_HR(EC), GRAPES_GFS(GFS) were evaluated using FSS (fractional skill score) and CRA (contiguous rain area) methods based on CMA radar-satellite-gauge merged precipitation (CMPA_Hourly V2.1) in this paper. The difference of two methods and the performance of each numerical model were discussed. The results show that FSS method can better distinguish the performance of different models through quantitive scores compared with the traditional TS method, and CRA method can reflect error sources of models more comprehensively. For local heavy rainfall or intense center of large-scale precipitation, regional models are more superior to global models. However, global models still perform well in 〖JP2〗predicting small-scale precipi-〖JP〗tation. For the two precipitation processes of typhoons ‘Yagi’ and ‘Rumbia’, the displacement errors of EC are more westward than the observation, and the same characteristics are also found in the prediction of ‘Rumbia’ precipitation by MESO and GFS. Precipitation scope and intensity tend to be underestimated by GFS model. The EC model can perform better a little, but still has some shortcomings in estimating precipitation extremes. Although regional models, especially SH, can forecast more intense precipitation centers, the scope and intensity can be easily overestimated. The displacement error for most models is main source of precipitation error, and intensity error and pattern error are roughly equivalent.
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基金项目:河南省气象局重点项目(Z201601)、河南省科技攻关项目(172102310463)、河南省气象局面上项目(KM201904)共同资助
引用文本:
王新敏,栗晗,2020.多数值模式对台风暴雨过程预报的空间检验评估[J].气象,46(6):753-764.
WANG Xinmin,LI Han,2020.Spatial Verification Evaluation of Typhoon Rainstorm by Multiple Numerical Models[J].Meteor Mon,46(6):753-764.