| 不同数值模式对江淮地区梅汛期暴雨模拟的对比分析 |
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| 引用本文： | 张文月,闵锦忠.不同数值模式对江淮地区梅汛期暴雨模拟的对比分析[J].气象科学,2024,44(2):328-337. |
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| 作者姓名： | 张文月 闵锦忠 |
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| 作者单位： | 南京信息工程大学 气象灾害教育部重点实验室/气候与环境变化国际联合实验室/气象灾害 预报预警与评估协同创新中心/大气科学学院, 南京 210044 |
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| 基金项目： | 国家自然科学基金重大资助项目 (42192553) |
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| 摘 要： | 从降水偏差特征、预报技巧和对象诊断分析3个角度评估了欧洲中期天气预报中心模式(EC)、华东区域中心区域数值模式(WARMS)和江苏区域模式(PWAFS)对2020年江淮地区梅汛期11次典型暴雨过程的预报性能,并分析了各模式的优点及不足。结果表明:(1)24 h观测日平均累计降水主要分布在大别山—江苏淮北以及大别山—皖南山区,相应的模式降水偏差大值区与主要雨带位置有较好的对应关系,其中,EC在大别山和皖南山区存在明显干偏差,在江苏淮北地区则出现系统性北偏。WARMS和PWAFS两种区域模式均在大别山和皖南山区上游地区和下游浙江地区出现大范围湿偏差,而在江苏淮北地区出现干偏差;(2)24 h预报技巧评分结果表明,EC对暴雨及以下量级的TS评分最高,但大暴雨量级PWAFS最优,原因是EC对大暴雨量级出现较高漏报。对比WARMS和PWAFS两家区域模式可见,PWAFS在几乎各量级的空报和漏报率都低于WARMS,因此TS评分也高于WARMS;(3)通过MODE对象诊断分析发现,EC对降水位置预报最稳定,PWAFS对降水强度和范围的预报效果最优,但对雨带位置的预报不够稳定。总得来说,PWAFS的预报性能略优于WARMS,与EC相比在对降水强度和雨带范围的刻画上也具有优势,但预报稳定性尚有待提高。
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| 关 键 词： | 数值模式 江淮梅雨 暴雨 对象诊断分析 |
| 收稿时间： | 2023/2/26 0:00:00 |
| 修稿时间： | 2023/5/21 0:00:00 |
Comparison and analysis of different numerical models for rainstorm simulation during Jianghuai Meiyu period |
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| ZHANG Wenyue,MIN Jinzhong.Comparison and analysis of different numerical models for rainstorm simulation during Jianghuai Meiyu period[J].Scientia Meteorologica Sinica,2024,44(2):328-337. |
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| Authors: | ZHANG Wenyue MIN Jinzhong |
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| Institution: | Key Laboratory of Meteorological Disaster, Ministry of Education/International Joint Laboratory on Climate and Environment Change/Disasters Collaborative Innovation Centeron Forecast and Evaluation of Meteorological Disaster/School of Atmospheric Science, Nanjing University of Information Science & Technology, Nanjing 210044, China |
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| Abstract: | This paper evaluates the prediction performance of the European Central Numerical Model (EC), the East China Regional Central Regional Numerical Model (WARMS) and the Jiangsu Regional Model (PWAFS) for 11 typical rainstorm processes in the Meiyu season in the Yangtze Huaihe River region in 2020 from three perspectives of precipitation deviation characteristics, prediction skills and object diagnosis analysis, and the advantages and disadvantages of each model were analyzed. Results show that: (1) the daily average accumulated precipitation observed in 24 hours is mainly distributed in the Dabie Mountains-Huaibei, Jiangsu Province and the Dabie Mountains-southern Anhui Province. The corresponding area with the maximum value of the model precipitation deviation has a good correspondence with the location of the main rain belt. Among them, EC has a significant dry deviation in the Dabie Mountains and southern Anhui Province, while in Huaibei and Jiangsu Province, there is a systematic north deviation. Both WARMS and PWAFS regional models have a large range of wet deviations in the upper reaches of the Dabie Mountains and southern Anhui mountains and in the lower reaches of Zhejiang Province, while they have a dry deviation in the Huaibei region of Jiangsu Province; (2) the scoring results of 24-hour prediction skills show that the TS score of EC for rainstorm level and below is the highest, while PWAFS is the best for heavy rainstorm level because of the high frequency of missing report of EC for heavy rainstorm. Comparing the two regional models of WARMS and PWAFS, it can be seen that PWAFS has lower missing report and false report rates at almost all levels than WARMS, so its TS score is also higher than that of WARMS; (3) through the diagnosis and analysis of MODE objects, it is found that EC has the most stable precipitation location prediction, PWAFS has the best prediction effect of precipitation intensity and range, but the forecast of rain band location is not stable enough. In general, the prediction performance of PWAFS is slightly better than that of WARMS. Compared with EC, PWAFS also has advantages in describing precipitation intensity and rain band range, but the prediction stability needs to be improved. |
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| Keywords: | numerical mode Jianghuai meiyu rainstorm object diagnosis analysis |
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