海洋预报2024,Vol.41Issue(5) :99-106.DOI:10.11737/j.issn.1003-0239.2024.05.010

多源数据融合在台风登陆前后风速的识别应用

Application of multi-source data fusion in identification of wind speed before and after typhoon landfall

方奎明 谈志安 陈莲 李渊 陆桥
海洋预报2024,Vol.41Issue(5) :99-106.DOI:10.11737/j.issn.1003-0239.2024.05.010

多源数据融合在台风登陆前后风速的识别应用

Application of multi-source data fusion in identification of wind speed before and after typhoon landfall

方奎明 1谈志安 2陈莲 3李渊 1陆桥1
扫码查看

作者信息

  • 1. 台州市气象局,浙江台州 318000
  • 2. 台州市路桥区气象局,浙江台州 318050
  • 3. 玉环市气象局,浙江台州 317600
  • 折叠

摘要

基于Pydda反演算法、三次方程内插法及典型相关分析法,利用多普勒雷达径向速度反演风场、ERA5-Land再分析风场和气象自动站风场进行风场数据融合,并分析1909号超强台风"利奇马"登陆前后融合风场的特征.试验结果表明:融合风场结合了各类风场的独特优势,能够弥补高海拔地区观测资料缺乏的不足;融合风场既包含低层风场的大风速区特征,也包含反演风场中超强台风"利奇马"的北倾结构特征.融合风场通过低层风场的传导能够对下一时刻的地面大风区起到一定指示作用,结合地形可以进一步判断强降水发生的大致范围,有助于划定风雨灾害影响区域.

Abstract

Based on Pydda inversion algorithm,cubic interpolation method and typical correlation analysis method,the wind field data are fused from Doppler radial velocity inversion wind field,ERA5-Land reanalysis wind field and automatic station wind field,and the characteristics of the fused wind field before and after the landfall of the super Typhoon"Lekima"(1909)are analyzed.The results show that the fused wind field with unique advantage of each wind source overcomes the deficiency of the lack of observational data at high altitudes,which performs well both for the large wind speed areas in the low-level atmosphere and the north-dipping vertical structure of the super Typhoon"Lekima"(1909).The fusion wind field can provide some indications of the windy area on the ground at the next time step through analyzing the low-level wind field at current time step,and further predict approximate extent of heavy precipitation after combining the topography information which can be used to identify the impacting areas of wind and rain disasters.

关键词

多源数据/风场反演/风场融合/台风风场/风速识别

Key words

multi-source data/wind field inversion/wind field fusion/typhoon wind field/wind speed identification

引用本文复制引用

出版年

2024
海洋预报
国家海洋环境预报中心

海洋预报

CSTPCD北大核心
影响因子:0.37
ISSN:1003-0239
段落导航相关论文