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    Investigation of Non-Gaussian Doppler Spectra Observed by Weather Radar in a Tornadic Supercell

    Source: Journal of Atmospheric and Oceanic Technology:;2009:;volume( 026 ):;issue: 003::page 444
    Author:
    Yu, Tian-You
    ,
    Rondinel, Ricardo Reinoso
    ,
    Palmer, Robert D.
    DOI: 10.1175/2008JTECHA1124.1
    Publisher: American Meteorological Society
    Abstract: Radar Doppler spectra that deviate from a Gaussian shape were observed from a tornadic supercell on 10 May 2003, exhibiting features such as a dual peak, flat top, and wide skirt in the nontornadic region. Motivated by these observations, a spectral model of a mixture of two Gaussian components, each defined by its three spectral moments, is introduced to characterize different degrees of deviation from Gaussian shape. In the standard autocovariance method, a Gaussian spectrum is assumed and biases in velocity and spectrum width estimates may result if this assumption is violated. The impact of non-Gaussian weather spectra on these biases is formulated and quantified in theory and, consequently, verified using four experiments of numerical simulations. Those non-Gaussian spectra from the south region of the supercell are further examined and a nonlinear fitting algorithm is proposed to estimate the six spectral moments and compare to those obtained from the autocovariance method. It is shown that the dual-Gaussian model can better represent observed spectra for those cases. The authors? analysis suggests that vertical shear may be responsible for the flat-top or the dual-peak spectra in the lower elevation of 0.5° and their transition to the single-peak and wide-skirt spectra in the next elevation scan of 1.5°.
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      Investigation of Non-Gaussian Doppler Spectra Observed by Weather Radar in a Tornadic Supercell

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4209142
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    contributor authorYu, Tian-You
    contributor authorRondinel, Ricardo Reinoso
    contributor authorPalmer, Robert D.
    date accessioned2017-06-09T16:25:39Z
    date available2017-06-09T16:25:39Z
    date copyright2009/03/01
    date issued2009
    identifier issn0739-0572
    identifier otherams-67670.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4209142
    description abstractRadar Doppler spectra that deviate from a Gaussian shape were observed from a tornadic supercell on 10 May 2003, exhibiting features such as a dual peak, flat top, and wide skirt in the nontornadic region. Motivated by these observations, a spectral model of a mixture of two Gaussian components, each defined by its three spectral moments, is introduced to characterize different degrees of deviation from Gaussian shape. In the standard autocovariance method, a Gaussian spectrum is assumed and biases in velocity and spectrum width estimates may result if this assumption is violated. The impact of non-Gaussian weather spectra on these biases is formulated and quantified in theory and, consequently, verified using four experiments of numerical simulations. Those non-Gaussian spectra from the south region of the supercell are further examined and a nonlinear fitting algorithm is proposed to estimate the six spectral moments and compare to those obtained from the autocovariance method. It is shown that the dual-Gaussian model can better represent observed spectra for those cases. The authors? analysis suggests that vertical shear may be responsible for the flat-top or the dual-peak spectra in the lower elevation of 0.5° and their transition to the single-peak and wide-skirt spectra in the next elevation scan of 1.5°.
    publisherAmerican Meteorological Society
    titleInvestigation of Non-Gaussian Doppler Spectra Observed by Weather Radar in a Tornadic Supercell
    typeJournal Paper
    journal volume26
    journal issue3
    journal titleJournal of Atmospheric and Oceanic Technology
    identifier doi10.1175/2008JTECHA1124.1
    journal fristpage444
    journal lastpage461
    treeJournal of Atmospheric and Oceanic Technology:;2009:;volume( 026 ):;issue: 003
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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