Hydrometeor classification system using dual-polarization radar measurements: model improvements and in situ verification
A hydrometeor classification system based on a fuzzy logic technique using dual-polarization radar measurements of precipitation is presented. In this study, five dual-polarization radar measurements (namely horizontal reflectivity, differential reflectivity, specific differential phase, correlation...
Gespeichert in:
| Veröffentlicht in: | IEEE transactions on geoscience and remote sensing 2005-04, Vol.43 (4), p.792-801 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 801 |
|---|---|
| container_issue | 4 |
| container_start_page | 792 |
| container_title | IEEE transactions on geoscience and remote sensing |
| container_volume | 43 |
| creator | Lim, S. Chandrasekar, V. Bringi, V.N. |
| description | A hydrometeor classification system based on a fuzzy logic technique using dual-polarization radar measurements of precipitation is presented. In this study, five dual-polarization radar measurements (namely horizontal reflectivity, differential reflectivity, specific differential phase, correlation coefficient, and linear depolarization ratio) and altitude relating to environmental melting layer are used as input variables of the system. The hydrometeor classification system chooses one of nine different hydrometeor categories as output. The system presented in this paper is a further development of an existing hydrometeor classification system model developed at Colorado State University (CSU). The hydrometeor classification system is evaluated by comparing inferred results from the CSU CHILL Facility dual-polarization radar measurements with the in situ sample data collected by the T-28 aircraft during the Severe Thunderstorm Electrification and Precipitation Study. |
| doi_str_mv | 10.1109/TGRS.2004.843077 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_proquest_miscellaneous_28904923</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>1411984</ieee_id><sourcerecordid>2352068301</sourcerecordid><originalsourceid>FETCH-LOGICAL-c450t-53078b8b4a96fb08ea08ae2a69b65c58f13df3410c949acbd7feee7f83a05c23</originalsourceid><addsrcrecordid>eNqNkUGL1TAUhYMo-BzdC26CC131eZMmbeJOBp0RBgR9-3Cb3kqGtnkm7cDz15tnxQEXg6sLud85yclh7KWAvRBg3x2uvn7bSwC1N6qGtn3EdkJrU0Gj1GO2A2GbShorn7JnOd8CCKVFu2On61Of4kQLxcT9iDmHIXhcQpx5PuWFJr7mMH_n_YpjdYwjpvBzWyfsMfGJMK-JJpqX_J5PsaeRh-mY4t12xnHueShmYVn5HaW_9s_ZkwHHTC_-zAt2-PTxcHld3Xy5-nz54abySsNS6RLGdKZTaJuhA0MIBkliY7tGe20GUfdDrQR4qyz6rm8HImoHUyNoL-sL9nazLU_6sVJe3BSyp3HEmeKanbGNFLUwdSHfPEiW3wNl5f-AIK2V57tf_wPexjXNJa0zTdso0L8h2CCfYs6JBndMYcJ0cgLcuVp3rtadq3VbtUXyapOEEvUeV0LYQvwCORSizQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>867640522</pqid></control><display><type>article</type><title>Hydrometeor classification system using dual-polarization radar measurements: model improvements and in situ verification</title><source>IEEE Electronic Library (IEL)</source><creator>Lim, S. ; Chandrasekar, V. ; Bringi, V.N.</creator><creatorcontrib>Lim, S. ; Chandrasekar, V. ; Bringi, V.N.</creatorcontrib><description>A hydrometeor classification system based on a fuzzy logic technique using dual-polarization radar measurements of precipitation is presented. In this study, five dual-polarization radar measurements (namely horizontal reflectivity, differential reflectivity, specific differential phase, correlation coefficient, and linear depolarization ratio) and altitude relating to environmental melting layer are used as input variables of the system. The hydrometeor classification system chooses one of nine different hydrometeor categories as output. The system presented in this paper is a further development of an existing hydrometeor classification system model developed at Colorado State University (CSU). The hydrometeor classification system is evaluated by comparing inferred results from the CSU CHILL Facility dual-polarization radar measurements with the in situ sample data collected by the T-28 aircraft during the Severe Thunderstorm Electrification and Precipitation Study.</description><identifier>ISSN: 0196-2892</identifier><identifier>EISSN: 1558-0644</identifier><identifier>DOI: 10.1109/TGRS.2004.843077</identifier><identifier>CODEN: IGRSD2</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Additives ; Atmospheric modeling ; Categories ; Classification ; Colorado State University CHILL (CSU-CHILL) radar ; Depolarization ; dual-polarization radar measurements ; Fuzzy logic ; hydrometeor classification ; Hydrometeors ; Input variables ; Mathematical models ; Precipitation ; Radar detection ; Radar measurement ; Radar measurements ; Rain ; Reflectivity ; Severe Thunderstorm Electrification and Precipitation Study (STEPS) ; Shape measurement ; Storms</subject><ispartof>IEEE transactions on geoscience and remote sensing, 2005-04, Vol.43 (4), p.792-801</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2005</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c450t-53078b8b4a96fb08ea08ae2a69b65c58f13df3410c949acbd7feee7f83a05c23</citedby><cites>FETCH-LOGICAL-c450t-53078b8b4a96fb08ea08ae2a69b65c58f13df3410c949acbd7feee7f83a05c23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1411984$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1411984$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Lim, S.</creatorcontrib><creatorcontrib>Chandrasekar, V.</creatorcontrib><creatorcontrib>Bringi, V.N.</creatorcontrib><title>Hydrometeor classification system using dual-polarization radar measurements: model improvements and in situ verification</title><title>IEEE transactions on geoscience and remote sensing</title><addtitle>TGRS</addtitle><description>A hydrometeor classification system based on a fuzzy logic technique using dual-polarization radar measurements of precipitation is presented. In this study, five dual-polarization radar measurements (namely horizontal reflectivity, differential reflectivity, specific differential phase, correlation coefficient, and linear depolarization ratio) and altitude relating to environmental melting layer are used as input variables of the system. The hydrometeor classification system chooses one of nine different hydrometeor categories as output. The system presented in this paper is a further development of an existing hydrometeor classification system model developed at Colorado State University (CSU). The hydrometeor classification system is evaluated by comparing inferred results from the CSU CHILL Facility dual-polarization radar measurements with the in situ sample data collected by the T-28 aircraft during the Severe Thunderstorm Electrification and Precipitation Study.</description><subject>Additives</subject><subject>Atmospheric modeling</subject><subject>Categories</subject><subject>Classification</subject><subject>Colorado State University CHILL (CSU-CHILL) radar</subject><subject>Depolarization</subject><subject>dual-polarization radar measurements</subject><subject>Fuzzy logic</subject><subject>hydrometeor classification</subject><subject>Hydrometeors</subject><subject>Input variables</subject><subject>Mathematical models</subject><subject>Precipitation</subject><subject>Radar detection</subject><subject>Radar measurement</subject><subject>Radar measurements</subject><subject>Rain</subject><subject>Reflectivity</subject><subject>Severe Thunderstorm Electrification and Precipitation Study (STEPS)</subject><subject>Shape measurement</subject><subject>Storms</subject><issn>0196-2892</issn><issn>1558-0644</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqNkUGL1TAUhYMo-BzdC26CC131eZMmbeJOBp0RBgR9-3Cb3kqGtnkm7cDz15tnxQEXg6sLud85yclh7KWAvRBg3x2uvn7bSwC1N6qGtn3EdkJrU0Gj1GO2A2GbShorn7JnOd8CCKVFu2On61Of4kQLxcT9iDmHIXhcQpx5PuWFJr7mMH_n_YpjdYwjpvBzWyfsMfGJMK-JJpqX_J5PsaeRh-mY4t12xnHueShmYVn5HaW_9s_ZkwHHTC_-zAt2-PTxcHld3Xy5-nz54abySsNS6RLGdKZTaJuhA0MIBkliY7tGe20GUfdDrQR4qyz6rm8HImoHUyNoL-sL9nazLU_6sVJe3BSyp3HEmeKanbGNFLUwdSHfPEiW3wNl5f-AIK2V57tf_wPexjXNJa0zTdso0L8h2CCfYs6JBndMYcJ0cgLcuVp3rtadq3VbtUXyapOEEvUeV0LYQvwCORSizQ</recordid><startdate>20050401</startdate><enddate>20050401</enddate><creator>Lim, S.</creator><creator>Chandrasekar, V.</creator><creator>Bringi, V.N.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><scope>7U5</scope><scope>7SP</scope><scope>F28</scope></search><sort><creationdate>20050401</creationdate><title>Hydrometeor classification system using dual-polarization radar measurements: model improvements and in situ verification</title><author>Lim, S. ; Chandrasekar, V. ; Bringi, V.N.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c450t-53078b8b4a96fb08ea08ae2a69b65c58f13df3410c949acbd7feee7f83a05c23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Additives</topic><topic>Atmospheric modeling</topic><topic>Categories</topic><topic>Classification</topic><topic>Colorado State University CHILL (CSU-CHILL) radar</topic><topic>Depolarization</topic><topic>dual-polarization radar measurements</topic><topic>Fuzzy logic</topic><topic>hydrometeor classification</topic><topic>Hydrometeors</topic><topic>Input variables</topic><topic>Mathematical models</topic><topic>Precipitation</topic><topic>Radar detection</topic><topic>Radar measurement</topic><topic>Radar measurements</topic><topic>Rain</topic><topic>Reflectivity</topic><topic>Severe Thunderstorm Electrification and Precipitation Study (STEPS)</topic><topic>Shape measurement</topic><topic>Storms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lim, S.</creatorcontrib><creatorcontrib>Chandrasekar, V.</creatorcontrib><creatorcontrib>Bringi, V.N.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><jtitle>IEEE transactions on geoscience and remote sensing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Lim, S.</au><au>Chandrasekar, V.</au><au>Bringi, V.N.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Hydrometeor classification system using dual-polarization radar measurements: model improvements and in situ verification</atitle><jtitle>IEEE transactions on geoscience and remote sensing</jtitle><stitle>TGRS</stitle><date>2005-04-01</date><risdate>2005</risdate><volume>43</volume><issue>4</issue><spage>792</spage><epage>801</epage><pages>792-801</pages><issn>0196-2892</issn><eissn>1558-0644</eissn><coden>IGRSD2</coden><abstract>A hydrometeor classification system based on a fuzzy logic technique using dual-polarization radar measurements of precipitation is presented. In this study, five dual-polarization radar measurements (namely horizontal reflectivity, differential reflectivity, specific differential phase, correlation coefficient, and linear depolarization ratio) and altitude relating to environmental melting layer are used as input variables of the system. The hydrometeor classification system chooses one of nine different hydrometeor categories as output. The system presented in this paper is a further development of an existing hydrometeor classification system model developed at Colorado State University (CSU). The hydrometeor classification system is evaluated by comparing inferred results from the CSU CHILL Facility dual-polarization radar measurements with the in situ sample data collected by the T-28 aircraft during the Severe Thunderstorm Electrification and Precipitation Study.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TGRS.2004.843077</doi><tpages>10</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 0196-2892 |
| ispartof | IEEE transactions on geoscience and remote sensing, 2005-04, Vol.43 (4), p.792-801 |
| issn | 0196-2892 1558-0644 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_28904923 |
| source | IEEE Electronic Library (IEL) |
| subjects | Additives Atmospheric modeling Categories Classification Colorado State University CHILL (CSU-CHILL) radar Depolarization dual-polarization radar measurements Fuzzy logic hydrometeor classification Hydrometeors Input variables Mathematical models Precipitation Radar detection Radar measurement Radar measurements Rain Reflectivity Severe Thunderstorm Electrification and Precipitation Study (STEPS) Shape measurement Storms |
| title | Hydrometeor classification system using dual-polarization radar measurements: model improvements and in situ verification |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T18%3A58%3A10IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Hydrometeor%20classification%20system%20using%20dual-polarization%20radar%20measurements:%20model%20improvements%20and%20in%20situ%20verification&rft.jtitle=IEEE%20transactions%20on%20geoscience%20and%20remote%20sensing&rft.au=Lim,%20S.&rft.date=2005-04-01&rft.volume=43&rft.issue=4&rft.spage=792&rft.epage=801&rft.pages=792-801&rft.issn=0196-2892&rft.eissn=1558-0644&rft.coden=IGRSD2&rft_id=info:doi/10.1109/TGRS.2004.843077&rft_dat=%3Cproquest_RIE%3E2352068301%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=867640522&rft_id=info:pmid/&rft_ieee_id=1411984&rfr_iscdi=true |