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    Using Spectral Moment Data from NOAA's 404-MHz Radar Wind Profilers to Observe Precipitation

    Source: Bulletin of the American Meteorological Society:;1995:;volume( 076 ):;issue: 010::page 1717
    Author:
    Ralph, F. M.
    ,
    Neiman, P. J.
    ,
    van de Kamp, D. W.
    ,
    Law, D. C.
    DOI: 10.1175/1520-0477(1995)076<1717:USMDFN>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: A brief description is given of NOAA's 404-MHz WindProfiler Demonstration Network (WPDN), including the radarconfiguration, sampling strategy, site locations andcharacteristics, and a discussion of the Doppler power spectrumand its first three spectral moments: signal power (S),radial velocity (Vr), and velocity variance(σ2). Evidence is presented showing that 6-mintime resolution spectral moment data from the verticallypointing beam of a WPDN wind profiler can be used to identifywhen precipitation is present above the profiler. Signatures ofsnow, light and moderate stratiform rain, heavy convective rain,freezing rain, and snow within jet stream cirrus are illustratedand summarized. Although radar reflectivity factor (Z)cannot be determined from WPON wind profilers, the precipitationrates and tall speeds shown to be observable in the casesdocumented here are roughly consistent with earlier studiessuggesting that precipitation with Z > 0?15dBZ should typically be observable at 404 MHz, and thatprecipitation or clouds with Z < 0 dBZ should not bereadily distinguishable from clear-air echoes. Generalsignatures common to most precipitation, and characteristics inthe data that allow different types of precipitation to bedistinguished from one another, are revealed from three casestudies. The most useful indicators of stratiform rain aredownward Vr > 3?5 ms?1 and σ2 > 1.0m2 s?1. Snow is indicated by 2 ms?1 > Vr0.5?0.9 ms?1 and σ2 < 1.0m2 s?2. Evidence of a melting levelin S, Vr, and σ2is a very good indicator of stratiform precipitation, and whenabsent helps identity precipitation as convective whenS and σ2 are large. Because thespectral moment data are regularly archived, this informationcan be examined in real time and compared with simultaneouslymeasured wind profiles. Such information should be useful inboth research and operational meteorology. The ability to inferrelationships between precipitation and kinematic featuresevident in the observed winds is also illustrated.
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      Using Spectral Moment Data from NOAA's 404-MHz Radar Wind Profilers to Observe Precipitation

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4161283
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    contributor authorRalph, F. M.
    contributor authorNeiman, P. J.
    contributor authorvan de Kamp, D. W.
    contributor authorLaw, D. C.
    date accessioned2017-06-09T14:41:35Z
    date available2017-06-09T14:41:35Z
    date copyright1995/10/01
    date issued1995
    identifier issn0003-0007
    identifier otherams-24594.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4161283
    description abstractA brief description is given of NOAA's 404-MHz WindProfiler Demonstration Network (WPDN), including the radarconfiguration, sampling strategy, site locations andcharacteristics, and a discussion of the Doppler power spectrumand its first three spectral moments: signal power (S),radial velocity (Vr), and velocity variance(σ2). Evidence is presented showing that 6-mintime resolution spectral moment data from the verticallypointing beam of a WPDN wind profiler can be used to identifywhen precipitation is present above the profiler. Signatures ofsnow, light and moderate stratiform rain, heavy convective rain,freezing rain, and snow within jet stream cirrus are illustratedand summarized. Although radar reflectivity factor (Z)cannot be determined from WPON wind profilers, the precipitationrates and tall speeds shown to be observable in the casesdocumented here are roughly consistent with earlier studiessuggesting that precipitation with Z > 0?15dBZ should typically be observable at 404 MHz, and thatprecipitation or clouds with Z < 0 dBZ should not bereadily distinguishable from clear-air echoes. Generalsignatures common to most precipitation, and characteristics inthe data that allow different types of precipitation to bedistinguished from one another, are revealed from three casestudies. The most useful indicators of stratiform rain aredownward Vr > 3?5 ms?1 and σ2 > 1.0m2 s?1. Snow is indicated by 2 ms?1 > Vr0.5?0.9 ms?1 and σ2 < 1.0m2 s?2. Evidence of a melting levelin S, Vr, and σ2is a very good indicator of stratiform precipitation, and whenabsent helps identity precipitation as convective whenS and σ2 are large. Because thespectral moment data are regularly archived, this informationcan be examined in real time and compared with simultaneouslymeasured wind profiles. Such information should be useful inboth research and operational meteorology. The ability to inferrelationships between precipitation and kinematic featuresevident in the observed winds is also illustrated.
    publisherAmerican Meteorological Society
    titleUsing Spectral Moment Data from NOAA's 404-MHz Radar Wind Profilers to Observe Precipitation
    typeJournal Paper
    journal volume76
    journal issue10
    journal titleBulletin of the American Meteorological Society
    identifier doi10.1175/1520-0477(1995)076<1717:USMDFN>2.0.CO;2
    journal fristpage1717
    journal lastpage1739
    treeBulletin of the American Meteorological Society:;1995:;volume( 076 ):;issue: 010
    contenttypeFulltext
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