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气象:2022,48(2):129-148
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CMA高分辨区域集合预报系统支撑北京冬奥会气象服务保障的评估分析
邓国,戴玲玲,周玉淑,陈静,李红祺,陈法敬,王继志
(中国气象局地球系统数值预报中心,北京 100081; 灾害天气国家重点实验室,北京 100081; 国家气象中心,北京 100081; 安徽省滁州市气象局,滁州 239004; 中国科学院大气物理研究所云降水物理与强风暴重点实验室,北京 100029; 中国科学院大学,北京 100049)
Evaluation and Analysis of Meteorological Service for Beijing Winter Olympic Games Supported by CMA High-Resolution Regional Ensemble Prediction System
DENG Guo,DAI Lingling,ZHOU Yushu,CHEN Jing,LI Hongqi,CHEN Fajing,WANG Jizhi
(CMA Earth System Modeling and Prediction Centre, Beijing 100081; State Key Laboratory of Severe Weather, Beijing 100081; National Meteorological Centre, Beijing 100081; Chuzhou Meteorological Office of Anhui Province, Chuzhou 239004; Key Laboratory of Cloud-Precipitation Physics and Severe Storms, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029; University of Chinese Academy of Sciences, Beijing 100049)
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投稿时间:2021-07-07    修订日期:2021-09-29
中文摘要: 冰雪运动项目与气象条件关系密切,气象条件是冬奥会赛事顺利进行的关键因素之一。中国气象局地球系统数值预报中心根据2022年北京冬奥会比赛气象保障需求,基于多尺度混合初值扰动方法和侧边界扰动方法,初步建立了高分辨率区域集合预报试验系统,针对北京冬奥会比赛同期时段开展了连续试验。初步试验统计结果表明:主要预报变量高、中、低层等压面要素集合平均值的均方根误差基本小于等于控制预报误差,体现了集合平均相对于单一确定性预报的优势;地面要素风和降水预报效果较好,但温度24 h预报偏差高于2 ℃,距离精准冬奥气象保障还有一定差距。针对试验期间两次寒潮大风过程开展了高分辨率区域集合预报,天气学分析的检验结果表明,集合预报产品可以比较准确地描述地面温度主要分布特征、寒潮移动过程和降水预报,为预报员提供寒潮标准24 h变温预报、大风预报等有价值的概率预测信息。基于诊断方法开发了能见度、大风、降水相态等对冬奥赛事运行和运动员表现有重要影响的天气要素集合预报产品,初步试验结果表明不同集合成员的取舍对能见度预报反应敏感,具有一定预报能力,但预报范围偏大,数值偏低,需进一步改进;阵风预报与实况大值区分布比较一致,降水相态预报与观测分布吻合,雨雪分界线,降雨、雨夹雪、雪、冰粒落区范围合理,进一步提升了北京冬奥会气象的保障能力。
Abstract:Winter sports are closely related to meteorological conditions, which is one of the most important factors for the success of Winter Olympic Games. According to the meteorological support requirements of Beijing Winter Olympic Games, CMA Earth System Modeling and Prediction Centre has preliminarily established a high-resolution regional ensemble prediction test system based on the multi-scale blending (MSB) initial condition perturbation method and lateral boundary condition (LBC) perturbation method, and carried out continuous tests for the same period corresponding to the 2022 Beijing Winter Olympic Games. The statistical results of the preliminary test show that the root mean square error of the ensemble mean values of isobaric surface elements at high, medium and low layers of the main forecast variables is basically less than or equal to the control forecast error, which reflects the advantages of the ensemble mean over the single deterministic forecast. The forecast effect of surface element wind and precipitation is good, but the deviation of 24 h temperature forecast is 2 ℃ higher, which is far from the accurate Winter Olympic Games meteorological support. The high-resolution regional ensemble forecast synoptic analysis of two cold waves and strong wind processes during the test period shows that the ensemble forecast products can accurately describe the main distribution characteristics of ground temperature, cold wave movement process and precipitation forecast, and provide valuable probabilistic forecast information for forecasters, such as cold wave standard 24 h varying temperature forecast and gale forecast. Based on the diagnostic method, the weather element ensemble forecast products that have an important impact on the operation of Winter Olympic events and athletes’ performance such as visibility, strong wind and precipitation phase are developed. The preliminary test results show that the choice of different ensemble members is sensitive to the visibility forecast, and has a certain forecast ability, but the forecast range is too large, and the value is low, which needs to be further improved. The distribution of gust forecast is consistent with the actual large-value area. The precipitation phase forecast is consistent with the observed distribution, especially the boundary of rain and snow, and the location ranges of rainfall, sleet, snow and ice particles are reasonable, which further improves the meteorological support ability to the Beijing Winter Olympic Games.
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基金项目:国家重点研发计划(2018YFF0300103)、国家自然科学基金项目(41975137和42175012)、中国气象局数值预报(GRAPES)发展专项共同资助
引用文本:
邓国,戴玲玲,周玉淑,陈静,李红祺,陈法敬,王继志,2022.CMA高分辨区域集合预报系统支撑北京冬奥会气象服务保障的评估分析[J].气象,48(2):129-148.
DENG Guo,DAI Lingling,ZHOU Yushu,CHEN Jing,LI Hongqi,CHEN Fajing,WANG Jizhi,2022.Evaluation and Analysis of Meteorological Service for Beijing Winter Olympic Games Supported by CMA High-Resolution Regional Ensemble Prediction System[J].Meteor Mon,48(2):129-148.