万齐林,薛纪善, 庄世宇. 2005. 多普勒雷达风场信息变分同化的试验研究[J]. 气象学报, 63(2):129-145, doi:10.11676/qxxb2005.014
多普勒雷达风场信息变分同化的试验研究
STUDY ON THE VARIATIONAL ASSIMILATION TECHNIQUE FOR THE RETRIEVAL OF WIND FIELDS FROM DOPPLER RADAR DATA
投稿时间:2004-07-15  修订日期:2004-09-27
DOI:10.11676/qxxb2005.014
中文关键词:  多普勒天气雷达,风场,变分同化
英文关键词:Variational assimilation technique, Wind fields, Doppler radar data.
基金项目:“十五”国家重点科技攻关计划项目“中国气象数值预报技术创新研究”(2001BA607B)和科技部重点公益性研究项目“我国登陆台风灾害的监测与预报技术研究”(2001DIA20026)
作者单位
万齐林 中国气象局广州热带海洋气象研究所广州510080 
薛纪善 中国气象科学研究院北京100081 
庄世宇 中国气象科学研究院北京100081 
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中文摘要:
      文中试验研究了一个在三维变分框架中直接同化多普勒天气雷达信息,获取雷达覆盖范围内大气风场的技术方案。径向风速是多普勒天气雷达数据中可直接被三维变分同化系统用来反演大气风场的唯一信息。由于风矢量有二或三个分量,径向风速作为风矢量的一个分量,不能为反演风矢量提供足够的信息。如果三维变分同化系统仅仅同化径向风速,所存在的不确定性将可能会给所反演的风场带来错误。文中提出的方案,不仅同化雷达径向风速,还同化雷达回波的移动信息,其关键是将雷达回波强度时空变化转换成一个新的雷达观测变量——雷达“视风速”。由于“视风速”是包含风场信息的变量,这在三维变分同化系统中增加了风场探测信息。通过联合利用“视风速”和径向风速,由单一径向风速确定风矢量所带来的不确定性可以被克服。使用中国气象科学研究院数值预报研究中心开发的三维变分同化系统(GRAPES-3Dvar)和广东省新一代天气雷达的监测资料进行了实例试验,结果表明本技术方案能够对获取大气系统结构是有用和有效的,也可用于形成模式初始场,这对中尺度天气预报是有作用的。
英文摘要:
      A variational assimilation technique for the retrieval of wind fields from Doppler weather radar data is introduced. The radial velocity (RV) is the unique signal to be used directly in three dimension variation assimilation system to retrieve wind-field from Doppler radar data. Since wind vector has two or three components, the radial velocity, as one component of wind vector, can not provide enough information for retrieving wind vector. Thus, if three-dimension variation assimilation system only used to assimilate the radial velocity, the indeterminacy would bring some mistakes into the retrieved wind-field. The assimilation technique suggested in this paper, not only assimilates the radial velocity, but also assimilates the information about the movement of radar echo. The key point is to transform the movement of radar echo to a new radar measuring variable -- “seeable velocity”(SV). Because the SV is possessed of the information of wind, more information is added to three-dimension variation assimilation system, and the indeterminacy that would come forth in retrieving wind vector by using RV only was overcome effectively by combining RV and SV. Using CMA GRAPES-3Dvar and CINRAD data, some tests were performed. The results showed that the method of retrieving wind-field was useful and effective for obtaining the construction of the weather system, and the scheme was also useful to obtain initial fields of model. It is an effective technique for meso-scale numerical weather prediction.
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