Using Spectral Moment Data from NOAA's 404-MHz Radar Wind Profilers to Observe PrecipitationSource: Bulletin of the American Meteorological Society:;1995:;volume( 076 ):;issue: 010::page 1717DOI: 10.1175/1520-0477(1995)076<1717:USMDFN>2.0.CO;2Publisher: 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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contributor author | Ralph, F. M. | |
contributor author | Neiman, P. J. | |
contributor author | van de Kamp, D. W. | |
contributor author | Law, D. C. | |
date accessioned | 2017-06-09T14:41:35Z | |
date available | 2017-06-09T14:41:35Z | |
date copyright | 1995/10/01 | |
date issued | 1995 | |
identifier issn | 0003-0007 | |
identifier other | ams-24594.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4161283 | |
description 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. | |
publisher | American Meteorological Society | |
title | Using Spectral Moment Data from NOAA's 404-MHz Radar Wind Profilers to Observe Precipitation | |
type | Journal Paper | |
journal volume | 76 | |
journal issue | 10 | |
journal title | Bulletin of the American Meteorological Society | |
identifier doi | 10.1175/1520-0477(1995)076<1717:USMDFN>2.0.CO;2 | |
journal fristpage | 1717 | |
journal lastpage | 1739 | |
tree | Bulletin of the American Meteorological Society:;1995:;volume( 076 ):;issue: 010 | |
contenttype | Fulltext |