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The development of a terrain-resolving scheme for the forward model and its adjoint in the four-dimensional Variational Doppler Radar Analysis System (VDRAS)

    • National Central University

    Research output: Contribution to journalArticlepeer-review

    20 Scopus citations

    Abstract

    The four-dimensional Variational Doppler Radar Analysis System (VDRAS) developed at the National Center for Atmospheric Research (NCAR) is significantly improved by implementing a terrain-resolving scheme to its forward model and adjoint based on the ghost cell immersed boundary method (GCIBM), which allows the topographic effects to be considered without the necessity to rebuild the model on a terrain-following coordinate system. The new system, called IBM_VDRAS, is able to perform forward forecast and backward adjoint model integration over nonflat lower boundaries, ranging from mountains with smooth slopes to buildings with sharp surfaces. To evaluate the performance of the forward model over complex terrain, idealized numerical experiments of a two-dimensional linear mountain wave and three-dimensional leeside vortices are first conducted, followed by a comparison with a simulation by the Weather Research and Forecasting (WRF) Model. An observing system simulation experiment is also conducted with the assimilation of simulated radar data to examine the ability of IBM_VDRAS in analyzing orographically forced moist convection. It is shown that the IBM_VDRAS can retrieve terrain-influenced three-dimensional meteorological fields including winds, thermodynamic, and microphysical parameters with reasonable accuracy. The new system, with the advanced radar data assimilation capability and the GCIBM terrain scheme, has the potential to be used for studying the evolution of convective weather systems under the influence of terrain.

    Original languageEnglish
    Pages (from-to)289-306
    Number of pages18
    JournalMonthly Weather Review
    Volume145
    Issue number1
    DOIs
    StatePublished - 2017

    Keywords

    • Data assimilation
    • Mesoscale forecasting
    • Numerical analysis/modeling
    • Radars/Radar observations
    • Topographic effects

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