| 北京“7.21”特大暴雨高分辨率模式分析场及预报分析 |
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| 引用本文： | 姜晓曼,袁慧玲,薛明,陈曦,谭晓光.北京“7.21”特大暴雨高分辨率模式分析场及预报分析[J].气象学报,2014,72(2):207-219. |
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| 作者姓名： | 姜晓曼 袁慧玲 薛明 陈曦 谭晓光 |
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| 作者单位： | 南京大学大气科学学院与中尺度灾害性天气教育部重点实验室, 南京, 210093;南京大学大气科学学院与中尺度灾害性天气教育部重点实验室, 南京, 210093;南京大学大气科学学院与中尺度灾害性天气教育部重点实验室, 南京, 210093;美国俄克拉荷马大学气象学院与风暴分析预报中心, OK73072;南京大学大气科学学院与中尺度灾害性天气教育部重点实验室, 南京, 210093;中国气象局北京城市气象研究所, 北京, 100089 |
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| 基金项目： | 国家重点研究发展计划973项目（2013CB430106）、公益性行业（气象）科研专项（GYHY201206005）、国家自然科学基金项目（41175087）、国家人才培养基金（J1103410）。 |
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| 摘 要： | 2012年7月21-22日,61年以来最强降水袭击北京,北京大部分地区出现大暴雨,局部特大暴雨,过程雨量大、雨势强、范围广,造成了严重影响。此次强降水配置较为典型,业务预报提前指示出了此次过程,但预报结果存在强度偏弱,峰值偏晚等偏差。在对此次大暴雨进行综合分析的基础上,利用中国自动气象站与NOAA气候预测中心卫星反演降水资料CMORPH(Climate Prediction Center Morphing Technique)产品融合的逐时降水量网格数据资料作为观测,着重对北京市气象局新的快速更新循环同化和预报系统(BJ-RUC v2.0)的3 km高分辨率模式分析场和预报场进行了检验与分析,以期通过对中尺度模式预报性能的了解,为暴雨可预报性问题提供进一步的参考。研究结果表明,此次特大暴雨过程水汽条件极佳,降水区域较为集中,呈现西南一东北走向的中尺度雨带特征。利用常规检验评分对预报降水的时间序列进行检验发现,预报降水在时间上滞后,降水强度偏弱,存在偏西南的位置误差,并且未能反映降水系统的线状特征。进一步利用检验连续降水区域定量降水预报的CRA(contiguous rain area)方法,对预报误差进行分解表明,整体降水(5 mm/h)的主要误差来自于位置和形状误差;而在暴雨(20 mm/h)的预报中,降水强度的偏差占误差的主要部分。最后结合对预报场大尺度环流和物理量的诊断(水汽条件和不稳定条件),分析探讨了此次极端暴雨预报不佳的原因。
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| 关 键 词： | 特大暴雨 降水检验 中尺度模式 暴雨预报 |
| 收稿时间： | 2013/7/10 0:00:00 |
| 修稿时间： | 2013/12/9 0:00:00 |
Analysis of a torrential rainfall event over Beijing on 21-22 July 2012 based on high resolution model analyses and forecasts |
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| JIANG Xiaoman,YUAN Huiling,XUE Ming,CHEN Xi and TAN Xiaoguang.Analysis of a torrential rainfall event over Beijing on 21-22 July 2012 based on high resolution model analyses and forecasts[J].Acta Meteorologica Sinica,2014,72(2):207-219. |
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| Authors: | JIANG Xiaoman YUAN Huiling XUE Ming CHEN Xi and TAN Xiaoguang |
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| Institution: | School of Atmospheric Sciences and Key Laboratory of Mesoscale Severe Weather/Ministry of Education, Nanjing University, Nanjing 210093, China;School of Atmospheric Sciences and Key Laboratory of Mesoscale Severe Weather/Ministry of Education, Nanjing University, Nanjing 210093, China;School of Atmospheric Sciences and Key Laboratory of Mesoscale Severe Weather/Ministry of Education, Nanjing University, Nanjing 210093, China;School of Meteorology and Center for Analysis and Prediction of Storms, University of Oklahoma, Norman OK73072, USA;School of Atmospheric Sciences and Key Laboratory of Mesoscale Severe Weather/Ministry of Education, Nanjing University, Nanjing 210093, China;Beijing Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China |
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| Abstract: | The heaviest rainfall over 61 years hit Beijing on 21-22 July 2012. Characterized by its great rainfall amount and intensity, wide range, and high impact, this record-breaking severe rainfall caused dozens of deaths and extensive damage. Despite seeming typical in terms of synoptic conditions, the operational forecasts underestimated the precipitation amount and were later as to predicting the rainfall start time. To gain a better understanding of the performance of mesoscale models, verification of high-resolution forecasts and analyses from the WRF-based BJ-RUC v2.0 model with a horizontal grid spacing of 3 km is carried out. The results show that in this case water vapor is very rich and a quasi-linear precipitation system produces a rather concentrated rain area. Moreover, the model forecasts are first verified by using statistically the Equitable Threat Score (ETS) and BIAS score.The BJ-RUC v2.0 forecasts under-predict the rainfall with a southwestward displacement error and time delay of the extreme precipitation. Further quantitative analysis of the contiguous rain area (CRA) method indicates that major forecast errors for total precipitation (>5 mm/h) are due to inaccurate precipitation location and pattern, while forecast errors for severe rain (>20 mm/h) mainly come from precipitation intensity forecasts. Finally, the possible causes for the poor performance are discussed through diagnosing large-scale circulation and physical parameters (water vapor condition and instability conditions) based on the BJ-RUC v2.0 model outputs. |
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| Keywords: | Excessive rainfall Precipitation verification Mesoscale model Torrential rain forecast |
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