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Application of the Multigrid Method to the Two-Dimensional Doppler Radar Radial Velocity Data Assimilation

机译:多重网格方法在二维多普勒雷达径向速度资料同化中的应用

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摘要

In recent years, the Earth System Research Laboratory (ESRL) of the National Oceanic and Atmospheric Administration (NOAA) has developed a space and time mesoscale analysis system (STMAS), which is currently a sequential three-dimensional variational data assimilation (3DVAR) system and is developing into a sequential 4DVAR in the near future. It is implemented by using a multigrid method based on a variational approach to generate grid analyses. This study is to test how STMAS deals with 2D Doppler radar radial velocity and to what degree the 2D Doppler radar radial velocity can improve the conventional (in situ) observation analysis. Two idealized experiments and one experiment with real Doppler radar radial velocity data, handled by STMAS, demonstrated significant improvement of the conventional observation analysis. Because the radar radial wind data can provide additional wind information (even it is incomplete: e.g., missing tangential wind vector), the analyses by assimilating both radial wind data and conventional data showed better results than those by assimilating only conventional data. Especially in the case of sparse conventional data, radar radial wind data can provide significant information and improve the analyses considerably.
机译:近年来,美国国家海洋与大气管理局(NOAA)的地球系统研究实验室(ESRL)开发了一种时空中尺度分析系统(STMAS),该系统目前是连续的三维变差数据同化(3DVAR)系统并在不久的将来发展成连续的4DVAR。它是通过使用基于变分方法的多网格方法生成网格分析来实现的。这项研究旨在测试STMAS如何处理2D多普勒雷达径向速度,以及2D多普勒雷达径向速度可在多大程度上改善常规(原位)观测分析。由STMAS处理的两个理想化实验和一个使用真实多普勒雷达径向速度数据的实验证明了常规观测分析的显着改进。由于雷达径向风数据可以提供更多的风信息(即使它是不完整的,例如缺少切向风矢量),因此同化径向风数据和常规数据的分析显示出比仅同化常规数据更好的分析结果。特别是在稀疏的常规数据的情况下,雷达径向风数据可以提供重要的信息并大大改善分析效果。

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  • 来源
    《Journal of atmospheric and oceanic technology》 |2010年第2期|319-332|共14页
  • 作者单位

    College of Physical and Environmental Oceanography, Ocean University of China, Qingdao, and National Marine Data and Information Service, State Oceanic Administration, Tianjin, China 93 Liuwei Road, Hedong District, Tianjin 300171, China;

    NOAA/Earth System Research Laboratory, Boulder, Colorado;

    Central Weather Bureau, Taipei, Taiwan;

    National Marine Data and Information Service, State Oceanic Administration, Tianjin, China;

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