| 摘要: |
| 利用华南精细数值天气预报模式,设计了无同化资料(CTRL)、同化雷达反演水汽(EXP1)以及同化雷达反演水汽、地面和探空资料(EXP2)三个试验,对2017年登陆广东沿海的四个台风降水预报与路径预报进行模拟,以评估资料同化对登陆台风短期降水预报、路径预报的影响。分析结果如下:雷达反演水汽同化后对未来24小时降水预报技巧均有正的改善,对台风路径预报影响不大;在此基础上同化地面、探空资料后对台风路径预报有改进,对降水预报改进不明显(与EXP1比)。通过诊断分析台风“玛娃”,发现模式初值场水汽的增量配合对流上升区有利于短时间内成云致雨,从而提高短时降水预报;地面及探空资料同化有利于登陆台风的短时路径预报。 |
| 关键词: 资料同化 台风 降水路径及预报 |
| DOI:10.16032/j.issn.1004-4965.2019.052 |
| 分类号: |
| 基金项目: |
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| IMPACT OF DATA ASSIMILATION ON SHORT-TERM PRECIPITATION FORECAST AND TRACK FORECAST OF TYPHOON LANDING IN THE COASTAL AREA OF GUANGDONG IN 2017 |
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ZHANG Cheng-zhong1, XUE Ji-shan1,2, HUANG Yan-yan1, DAI Guang-feng1
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1. Guangzhou Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional
Numerical Weather Prediction, CMA, Guangzhou 510641, China;2. Chinese Academy of Meteorological Sciences, Beijing 100081, China
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| Abstract: |
| Based on the south China fine numerical weather prediction model, three different experiments are designed-one with assimilation of radar-retrieved water vapor(EXP1), the second with assimilation of radar-retrieved water vapor plus surface and sounding data(EXP2), and the third without assimilation (CTRL)-to assess the impact of data assimilation on the prediction of short-term precipitation and the track of typhoon landing in the coastal area of Guangdong in 2017. Results are as follows. After the assimilation of radar-retrieved water vapor, the skill of the precipitation prediction is improved, and the impact of assimilation on the typhoon track forecast is not significant. The skill of track forecast is improved with assimilation of radar-retrieved water vapor plus surface and sounding data, while the improvement of precipitation forecasts is not significant compared with EXP1. Through the diagnosis and analysis of the typhoon“Mawar”, it is found that the couple of the increase of water vapor in the initial field and the updraft is conducive to the production of cloud and rain water in a short time, thus improving the short-term precipitation forecast; the assimilation of surface and sounding data is conducive to the improvement of the short-term track forecast of landing typhoon. |
| Key words: data assimilation typhoon track and precipitation forecast |