| 双流机场雷暴天气预报方法研究 |
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| 作者姓名： | 李典南 徐海 许东蓓 |
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| 作者单位： | 贵州省气象台,中国民用航空西南地区空中交通管理局气象中心,成都信息工程大学大气科学学院 |
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| 摘 要： | 利用双流国际机场2013—2018年的逐小时气象观测资料、欧洲中心ERA-interim逐6小时再分析资料、成都市气象局多普勒天气雷达产品资料，运用统计学方法分析双流机场雷暴月变化和日变化特征，并利用相关性分析筛选出双流机场雷暴天气预报因子，在此基础上基于二级逻辑回归法建立潜势预报模型（预报方程和消空方程），最后进行数据的回代检验。结果表明：对流有效位能、K指数、850 hPa比湿、850与500 hPa假相当位温差、回波顶高、1.5º仰角基本反射率、3.4º仰角基本反射率、垂直累积液态水含量为雷暴天气的主要预报因子，据此建立的潜势预报模型对双流机场雷暴天气的预报具有一定指示性，且综合来看在夏季的预报效果更好。
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| 关 键 词： | 双流机场 雷暴 预报因子 预报方程 |
| 收稿时间： | 2020/11/29 0:00:00 |
| 修稿时间： | 2021/2/1 0:00:00 |
Study on Thunderstorm Forecasting Methods at Shuangliu Airport |
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| Authors: | LI Diannan XU Hai and XU Dongbei |
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| Institution: | Guizhou Meteorological Observatory,Meteorological Center of Southwest Air Traffic Management Bureau, CAAC,College of Atmospheric Sciences, Chengdu University of Information Technology |
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| Abstract: | Based on the hourly meteorological observation data of Shuangliu International Airport from 2013 to 2018, the 6 hourly reanalysis data of European Center ECMWF ERA-interim, and the products data of Doppler Weather Radar of Chengdu Meteorological Bureau, statistical methods were used to analyze the monthly and daily characteristics of the changes of thunderstorms at Shuangliu Airport, and correlation analysis were used to screen out some thunderstorm forecast factors of Shuangliu Airport. On this basis, the potential forecast models (prediction equation and voiding equation) were established based on the two-level logistic regression method, and finally the existing data were tested for retrogression. The results show: The main predictors of thunderstorms are convective available potential energy, K index, 850 hPa specific humidity, potential pseudo-equivalent temperature difference between 850 hPa and 500 hPa, echo top, 1.5º elevation angle basic reflectance, 3.4º elevation angle basic reflectance, and vertically integrated liquid. The potential forecast models established based on these has certain indications for the forecast of thunderstorm at Shuangliu Airport, and the overall forecasting effect in summer is better. |
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| Keywords: | Shuangliu Airport thunderstorm forecast factors prediction equation |
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