多普勒雷达资料同化在台风“桑美”预报中的应用研究

沈菲菲; 闵锦忠; 陈鹏; 李超

doi:10.3969/j.issn.0253-4193.2015.03.003

多普勒雷达资料同化在台风“桑美”预报中的应用研究

doi: 10.3969/j.issn.0253-4193.2015.03.003

1.
南京信息工程大学气象灾害省部共建教育部重点实验室, 江苏南京 210044;南京信息工程大学大气科学学院, 江苏南京 210044;
2.
江苏省气象信息中心, 江苏南京 210008;
3.
江苏省南通市气象局, 江苏南通 226018

基金项目: 国家973计划项目(OPPAC-2013CB430102);国家自然科学基金项目(41375025);江苏省普通高校研究生科研创新计划(CXZZ11_0606,CXZZD_0490,CXZZB_0501)。

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出版历程
- 收稿日期: 2014-01-01

Experiments of assimilating Doppler radar data in forecast of typhoon Saomai

1.
Jiangsu Key Laboratory of Meteorological Disaster, Nanjing University of Information Science & Technology, Nanjing 210044, China;College of Atmospheric Science, Nanjing University of Information Science &Technology, Nanjing 210044, China;
2.
Jiangsu Meteorological Information Center, Jiangsu Province, Nanjing 210008, China;
3.
Nantong Meteorological Bureau, Jiangsu Province, Nantong 226018, China

摘要

摘要: 本文以2006年超强台风"桑美"为个例,考察了同化雷达径向风观测资料对台风初始场和预报场的改进作用。首先对沿海新一代多普勒天气雷达的径向风观测资料进行了去噪音、退模糊等一系列的质量控制,进一步利用美国国家大气研究中心开发的中尺度数值模式WRFV3.5及其三维变分同化系统WRF-3DVAR,每30 min循环同化雷达径向风观测资料。结果表明:同化多普勒雷达径向风观测资料后,对台风在模式中的初始位置进行了很好的修正,同时对台风区的动力和热力结构均有较好的调整。两组同化试验对于台风的路径、强度、降水等预报要优于控制试验,并且对背景误差协方差尺度化因子优化调整可以更有效地吸收雷达观测资料并提供更多的中小尺度信息。
- 雷达径向风资料 /
- 资料同化 /
- WRF-3DVAR系统 /
- 数值模拟
Abstract: The impact of assimilating radar radial velocity data on the analysis and forecasting of the super typhoon "Saomai" (2006) is investigated in this study. The pre-processing and quality control are performed on radar radial velocity observations,which are further assimilated every 30 minutes into the framework of Weather Research and Forecasting (WRF) V3.5 and its three-dimensional variational data assimilation system WRF-3DVAR developed by the U.S. National Center for Atmospheric Research (NCAR). The results show that assimilating Doppler radar radial velocity can improve the typhoon initialization for wind and temperature fields,producing more meticulous mesoscale structure information. Furthermore,radial velocity data assimilation have improved the forecasting of typhoon track,minimum sea level pressure,maximum wind speed,and precipitation. The analysis and forecasting performances can be further improved by reducing the background length-scale.
- radar radial velocity /
- data assimilation /
- WRF-3DVAR /
- numerical simulation

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