Considerations for Oversampling in Azimuth on the Phased Array Weather Radar
When spectral moments in the azimuth are spaced by less than a beamwidth, it is called oversampling. Superresolution is a type of oversampling that refers to sampling at half a beamwidth on the national network of Doppler weather radars [Weather Surveillance Radar-1988 Doppler (WSR-88D)]. Such close...
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Veröffentlicht in: | Journal of atmospheric and oceanic technology 2015-09, Vol.32 (9), p.1614-1629 |
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description | When spectral moments in the azimuth are spaced by less than a beamwidth, it is called oversampling. Superresolution is a type of oversampling that refers to sampling at half a beamwidth on the national network of Doppler weather radars [Weather Surveillance Radar-1988 Doppler (WSR-88D)]. Such close spacing is desirable because it extends the range at which small severe weather features, such as tornadoes or microbursts, can be resolved. This study examines oversampling for phased array radars. The goal of the study is to preserve the same effective beamwidth as on the WSR-88D while obtaining smaller spectral moment estimate errors at the same or faster volume update times. To that effect, a weighted average of autocorrelations of radar signals from three consecutive radials is proposed. Errors in three spectral moments obtained from these autocorrelations are evaluated theoretically. Methodologies on how to choose weights that preserve the desirable effective beamwidth are presented. The results are demonstrated on the fields of spectral moments obtained with the National Weather Radar Testbed (NWRT), a phased array weather radar at NOAA's National Severe Storms Laboratory (NSSL). |
doi_str_mv | 10.1175/JTECH-D-15-0018.1 |
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Superresolution is a type of oversampling that refers to sampling at half a beamwidth on the national network of Doppler weather radars [Weather Surveillance Radar-1988 Doppler (WSR-88D)]. Such close spacing is desirable because it extends the range at which small severe weather features, such as tornadoes or microbursts, can be resolved. This study examines oversampling for phased array radars. The goal of the study is to preserve the same effective beamwidth as on the WSR-88D while obtaining smaller spectral moment estimate errors at the same or faster volume update times. To that effect, a weighted average of autocorrelations of radar signals from three consecutive radials is proposed. Errors in three spectral moments obtained from these autocorrelations are evaluated theoretically. Methodologies on how to choose weights that preserve the desirable effective beamwidth are presented. The results are demonstrated on the fields of spectral moments obtained with the National Weather Radar Testbed (NWRT), a phased array weather radar at NOAA's National Severe Storms Laboratory (NSSL).</description><identifier>ISSN: 0739-0572</identifier><identifier>EISSN: 1520-0426</identifier><identifier>DOI: 10.1175/JTECH-D-15-0018.1</identifier><language>eng</language><publisher>Boston: American Meteorological Society</publisher><subject>Autocorrelation ; Azimuth ; Climatology ; Doppler effect ; Doppler radar ; Doppler sonar ; Errors ; Estimates ; Marine ; Meteorological radar ; Microbursts ; Microbursts (meteorology) ; Oversampling ; Phased arrays ; Preserves ; Radar ; Radar arrays ; Severe storms ; Severe weather ; Spectra ; Storms ; Studies ; Surveillance radar ; Tornadoes ; Weather ; Weather radar</subject><ispartof>Journal of atmospheric and oceanic technology, 2015-09, Vol.32 (9), p.1614-1629</ispartof><rights>Copyright American Meteorological Society Sep 2015</rights><rights>Copyright American Meteorological Society 2015</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c476t-4c3f393265c1d124fb16f80c2465c8f04cd7571f654b25cb76eac3142cdfb5e33</citedby><cites>FETCH-LOGICAL-c476t-4c3f393265c1d124fb16f80c2465c8f04cd7571f654b25cb76eac3142cdfb5e33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,3668,27903,27904</link.rule.ids></links><search><creatorcontrib>Borowska, Lesya</creatorcontrib><creatorcontrib>Zhang, Guifu</creatorcontrib><creatorcontrib>Zrnic, Dusan S</creatorcontrib><title>Considerations for Oversampling in Azimuth on the Phased Array Weather Radar</title><title>Journal of atmospheric and oceanic technology</title><description>When spectral moments in the azimuth are spaced by less than a beamwidth, it is called oversampling. Superresolution is a type of oversampling that refers to sampling at half a beamwidth on the national network of Doppler weather radars [Weather Surveillance Radar-1988 Doppler (WSR-88D)]. Such close spacing is desirable because it extends the range at which small severe weather features, such as tornadoes or microbursts, can be resolved. This study examines oversampling for phased array radars. The goal of the study is to preserve the same effective beamwidth as on the WSR-88D while obtaining smaller spectral moment estimate errors at the same or faster volume update times. To that effect, a weighted average of autocorrelations of radar signals from three consecutive radials is proposed. Errors in three spectral moments obtained from these autocorrelations are evaluated theoretically. Methodologies on how to choose weights that preserve the desirable effective beamwidth are presented. The results are demonstrated on the fields of spectral moments obtained with the National Weather Radar Testbed (NWRT), a phased array weather radar at NOAA's National Severe Storms Laboratory (NSSL).</description><subject>Autocorrelation</subject><subject>Azimuth</subject><subject>Climatology</subject><subject>Doppler effect</subject><subject>Doppler radar</subject><subject>Doppler sonar</subject><subject>Errors</subject><subject>Estimates</subject><subject>Marine</subject><subject>Meteorological radar</subject><subject>Microbursts</subject><subject>Microbursts (meteorology)</subject><subject>Oversampling</subject><subject>Phased arrays</subject><subject>Preserves</subject><subject>Radar</subject><subject>Radar arrays</subject><subject>Severe storms</subject><subject>Severe weather</subject><subject>Spectra</subject><subject>Storms</subject><subject>Studies</subject><subject>Surveillance radar</subject><subject>Tornadoes</subject><subject>Weather</subject><subject>Weather radar</subject><issn>0739-0572</issn><issn>1520-0426</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqNkUtLAzEUhYMoWKs_wF3AjZupuXnOLEtbXxQqUnEZ0kxip7QzNZkR6q83ta5ciKt7OXwc7j0HoUsgAwAlbh7nk9F9Ns5AZIRAPoAj1ANBSUY4lceoRxQrMiIUPUVnMa5IghjIHpqOmjpWpQumrdKGfRPw7MOFaDbbdVW_4arGw89q07VL3NS4XTr8tDTRlXgYgtnhV2eSFvCzKU04RyferKO7-Jl99HI7mae7prO7h9FwmlmuZJtxyzwrGJXCQgmU-wVInxNLeVJyT7gtlVDgpeALKuxCSWcsA05t6RfCMdZH1wffbWjeOxdbvamideu1qV3TRZ0CYbxQLBf_QCkFleeySOjVL3TVdKFOj2iaU0lTkCz_iwIFoiBFoWSi4EDZ0MQYnNfbUG1M2Gkgel-Y_i5MjzUIvS9MA_sCt6qGnQ</recordid><startdate>20150901</startdate><enddate>20150901</enddate><creator>Borowska, Lesya</creator><creator>Zhang, Guifu</creator><creator>Zrnic, Dusan S</creator><general>American Meteorological Society</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TG</scope><scope>7TN</scope><scope>7UA</scope><scope>7XB</scope><scope>88F</scope><scope>88I</scope><scope>8AF</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H8D</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>L7M</scope><scope>M1Q</scope><scope>M2O</scope><scope>M2P</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>S0X</scope><scope>7SP</scope></search><sort><creationdate>20150901</creationdate><title>Considerations for Oversampling in Azimuth on the Phased Array Weather Radar</title><author>Borowska, Lesya ; Zhang, Guifu ; Zrnic, Dusan S</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c476t-4c3f393265c1d124fb16f80c2465c8f04cd7571f654b25cb76eac3142cdfb5e33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Autocorrelation</topic><topic>Azimuth</topic><topic>Climatology</topic><topic>Doppler effect</topic><topic>Doppler radar</topic><topic>Doppler sonar</topic><topic>Errors</topic><topic>Estimates</topic><topic>Marine</topic><topic>Meteorological radar</topic><topic>Microbursts</topic><topic>Microbursts (meteorology)</topic><topic>Oversampling</topic><topic>Phased arrays</topic><topic>Preserves</topic><topic>Radar</topic><topic>Radar arrays</topic><topic>Severe storms</topic><topic>Severe weather</topic><topic>Spectra</topic><topic>Storms</topic><topic>Studies</topic><topic>Surveillance radar</topic><topic>Tornadoes</topic><topic>Weather</topic><topic>Weather radar</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Borowska, Lesya</creatorcontrib><creatorcontrib>Zhang, Guifu</creatorcontrib><creatorcontrib>Zrnic, Dusan S</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Military Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Military Database</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>SIRS Editorial</collection><collection>Electronics & Communications Abstracts</collection><jtitle>Journal of atmospheric and oceanic technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Borowska, Lesya</au><au>Zhang, Guifu</au><au>Zrnic, Dusan S</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Considerations for Oversampling in Azimuth on the Phased Array Weather Radar</atitle><jtitle>Journal of atmospheric and oceanic technology</jtitle><date>2015-09-01</date><risdate>2015</risdate><volume>32</volume><issue>9</issue><spage>1614</spage><epage>1629</epage><pages>1614-1629</pages><issn>0739-0572</issn><eissn>1520-0426</eissn><abstract>When spectral moments in the azimuth are spaced by less than a beamwidth, it is called oversampling. Superresolution is a type of oversampling that refers to sampling at half a beamwidth on the national network of Doppler weather radars [Weather Surveillance Radar-1988 Doppler (WSR-88D)]. Such close spacing is desirable because it extends the range at which small severe weather features, such as tornadoes or microbursts, can be resolved. This study examines oversampling for phased array radars. The goal of the study is to preserve the same effective beamwidth as on the WSR-88D while obtaining smaller spectral moment estimate errors at the same or faster volume update times. To that effect, a weighted average of autocorrelations of radar signals from three consecutive radials is proposed. Errors in three spectral moments obtained from these autocorrelations are evaluated theoretically. Methodologies on how to choose weights that preserve the desirable effective beamwidth are presented. The results are demonstrated on the fields of spectral moments obtained with the National Weather Radar Testbed (NWRT), a phased array weather radar at NOAA's National Severe Storms Laboratory (NSSL).</abstract><cop>Boston</cop><pub>American Meteorological Society</pub><doi>10.1175/JTECH-D-15-0018.1</doi><tpages>16</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Autocorrelation Azimuth Climatology Doppler effect Doppler radar Doppler sonar Errors Estimates Marine Meteorological radar Microbursts Microbursts (meteorology) Oversampling Phased arrays Preserves Radar Radar arrays Severe storms Severe weather Spectra Storms Studies Surveillance radar Tornadoes Weather Weather radar |
title | Considerations for Oversampling in Azimuth on the Phased Array Weather Radar |
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