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    Detection of gust fronts using the doppler velocity derived divergence product

    Clemins, Russel J.
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    [PDF] research.pdf (9.232Mb)
    Date
    2018
    Format
    Thesis
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    Abstract
    Identifying gust fronts can be essential for situational awareness when developing nowcasts during convective events. In addition to bearing potentially damaging winds, gust fronts also act as forcing mechanisms; influencing storm initiation, development, and propagation. Using doppler radar, gust fronts are usually observed by the presence of a reflectivity thin line ahead of the parent storm. In the situation where a thin line is not visible on radar, there is a loss of situational awareness. This study aimed to determine if gust fronts can be observed through the doppler velocity derived divergence product by isolating contiguous areas of divergence (convergence) that form couplets or line features, relative to the leading edge or ahead of a storm. Radar data for the study was collected using the University of Missouri-Columbia's MZZU X-Band radar, as well as the WSR-88D from the NWS Saint Louis CFO. Data processing was performed through the Warning Decision Support System-Integrated Information (WDSS-II), and the data was analyzed using the MatLab software. Thresholds for minimum pixel area, as well as minimum and maximum divergence (convergence) were used to establish a range of interest. Data was then filtered through a process of dilation and erosion, to prune out noise and highlight larger features. Through multiple cases using MZZU and KLSX, suitable criteria were developed that allowed the identification of Div-Conv couplets and linear regions of convergence that suggest the presence of gust fronts. Eddy covariance towers near Columbia, MO were used for surface observations of vertical velocity (w) and Turbulence Kinetic Energy (TKE). Good agreement was found between increases in w and TKE when gust fronts were detected and propagating through the region.
    URI
    https://hdl.handle.net/10355/66314
    Degree
    M.S.
    Thesis Department
    Soil, environmental and atmospheric sciences (MU)
    Rights
    OpenAccess.
    This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.
    Collections
    • 2018 MU theses - Freely available online
    • Soil, Environmental and Atmospheric Sciences electronic theses and dissertations (MU)

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