Monitoring the Absolute Calibration of a Polarimetric Weather Radar
The absolute calibration of a dual-polarization radar of the German Weather Service is continuously monitored using the operational birdbath scan and collocated disdrometer measurements at the Hohenpeissenberg observatory. The goal is to measure the radar reflectivity constant Z better than ±1 dB. T...
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Veröffentlicht in: | Journal of atmospheric and oceanic technology 2017-03, Vol.34 (3), p.599-615 |
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description | The absolute calibration of a dual-polarization radar of the German Weather Service is continuously monitored using the operational birdbath scan and collocated disdrometer measurements at the Hohenpeissenberg observatory. The goal is to measure the radar reflectivity constant
Z
better than ±1 dB. The assumption is that a disdrometer measurement close to the surface can be related to the radar measurement at the first far-field range bin. This is verified using a Micro Rain Radar (MRR). The MRR data fill the gap between the measurement near the surface and the far-field range bin at 650 m. Using data from the first half of the warm season in 2014, a bias in radar calibration of 1.8 dB is found. Data from only stratiform precipitation events are considered. After adjusting the radar calibration and using an independent data sample, very good agreement is found between the radar, the MRR, and the disdrometer with a bias in
smaller than 1 dB. The bias in
is not captured with the classic one-point calibration, which is performed twice a day using a built-in test signal generator. This is attributed to the fact that the characterization of the transmit and receive path is not accurate enough. Solar interferences during the operational scanning are used to characterize the receiver. There, the bias found is small, about 0.2 dB, so that bias based on the comparison of the radar with external sensors is attributed to the transmit path. The representativeness of the disdrometer measurements are assessed using two additional disdrometers located within 200-m distance. |
doi_str_mv | 10.1175/JTECH-D-16-0076.1 |
format | Article |
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Z
better than ±1 dB. The assumption is that a disdrometer measurement close to the surface can be related to the radar measurement at the first far-field range bin. This is verified using a Micro Rain Radar (MRR). The MRR data fill the gap between the measurement near the surface and the far-field range bin at 650 m. Using data from the first half of the warm season in 2014, a bias in radar calibration of 1.8 dB is found. Data from only stratiform precipitation events are considered. After adjusting the radar calibration and using an independent data sample, very good agreement is found between the radar, the MRR, and the disdrometer with a bias in
smaller than 1 dB. The bias in
is not captured with the classic one-point calibration, which is performed twice a day using a built-in test signal generator. This is attributed to the fact that the characterization of the transmit and receive path is not accurate enough. Solar interferences during the operational scanning are used to characterize the receiver. There, the bias found is small, about 0.2 dB, so that bias based on the comparison of the radar with external sensors is attributed to the transmit path. The representativeness of the disdrometer measurements are assessed using two additional disdrometers located within 200-m distance.</description><identifier>ISSN: 0739-0572</identifier><identifier>EISSN: 1520-0426</identifier><identifier>DOI: 10.1175/JTECH-D-16-0076.1</identifier><language>eng</language><publisher>Boston: American Meteorological Society</publisher><subject>Accuracy ; Algorithms ; Atmospheric precipitations ; Bias ; Calibration ; Climatology ; Disdrometers ; Dual polarization radar ; Measurement ; Polarization ; Precipitation ; Radar ; Radar calibration ; Radar measurement ; Radar polarimetry ; Radar reflectivity ; Radar systems ; Rain ; Rainfall measurement ; Reflectance ; Remote sensing ; Scanning ; Sensors ; Warm seasons ; Weather ; Weather radar</subject><ispartof>Journal of atmospheric and oceanic technology, 2017-03, Vol.34 (3), p.599-615</ispartof><rights>Copyright American Meteorological Society Mar 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-626a5d02b6183dc8ac0c0b30baa25d19979d74e5be1e23a9345eb5f10dbe7f563</citedby><cites>FETCH-LOGICAL-c316t-626a5d02b6183dc8ac0c0b30baa25d19979d74e5be1e23a9345eb5f10dbe7f563</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,3679,27922,27923</link.rule.ids></links><search><creatorcontrib>Frech, Michael</creatorcontrib><creatorcontrib>Hagen, Martin</creatorcontrib><creatorcontrib>Mammen, Theo</creatorcontrib><title>Monitoring the Absolute Calibration of a Polarimetric Weather Radar</title><title>Journal of atmospheric and oceanic technology</title><description>The absolute calibration of a dual-polarization radar of the German Weather Service is continuously monitored using the operational birdbath scan and collocated disdrometer measurements at the Hohenpeissenberg observatory. The goal is to measure the radar reflectivity constant
Z
better than ±1 dB. The assumption is that a disdrometer measurement close to the surface can be related to the radar measurement at the first far-field range bin. This is verified using a Micro Rain Radar (MRR). The MRR data fill the gap between the measurement near the surface and the far-field range bin at 650 m. Using data from the first half of the warm season in 2014, a bias in radar calibration of 1.8 dB is found. Data from only stratiform precipitation events are considered. After adjusting the radar calibration and using an independent data sample, very good agreement is found between the radar, the MRR, and the disdrometer with a bias in
smaller than 1 dB. The bias in
is not captured with the classic one-point calibration, which is performed twice a day using a built-in test signal generator. This is attributed to the fact that the characterization of the transmit and receive path is not accurate enough. Solar interferences during the operational scanning are used to characterize the receiver. There, the bias found is small, about 0.2 dB, so that bias based on the comparison of the radar with external sensors is attributed to the transmit path. The representativeness of the disdrometer measurements are assessed using two additional disdrometers located within 200-m distance.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Atmospheric precipitations</subject><subject>Bias</subject><subject>Calibration</subject><subject>Climatology</subject><subject>Disdrometers</subject><subject>Dual polarization radar</subject><subject>Measurement</subject><subject>Polarization</subject><subject>Precipitation</subject><subject>Radar</subject><subject>Radar calibration</subject><subject>Radar measurement</subject><subject>Radar polarimetry</subject><subject>Radar reflectivity</subject><subject>Radar systems</subject><subject>Rain</subject><subject>Rainfall measurement</subject><subject>Reflectance</subject><subject>Remote sensing</subject><subject>Scanning</subject><subject>Sensors</subject><subject>Warm seasons</subject><subject>Weather</subject><subject>Weather radar</subject><issn>0739-0572</issn><issn>1520-0426</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNotkMtOwzAQRS0EEqXwAewssXaZsWO7WVZpeakIhIpYWnbiQKoQFztd8Pe4wGo2R3PvPYRcIswQtbx-2KyqO7ZkqBiAVjM8IhOUHBgUXB2TCWhRMpCan5KzlLYAgALVhFSPYejGELvhnY4fni5cCv1-9LSyfeeiHbsw0NBSS59Db2P36cfY1fTN20xH-mIbG8_JSWv75C_-75S83qw2uc766fa-WqxZnaNGpriysgHuFM5FU89tDTU4Ac5aLhssS102uvDSefRc2FIU0jvZIjTO61YqMSVXf393MXztfRrNNuzjkCMNlrzQgHllpvCPqmNIKfrW7HJtG78Ngjm4Mr-uzNKgMgdXBsUPkkJcXg</recordid><startdate>20170301</startdate><enddate>20170301</enddate><creator>Frech, Michael</creator><creator>Hagen, Martin</creator><creator>Mammen, Theo</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></search><sort><creationdate>20170301</creationdate><title>Monitoring the Absolute Calibration of a Polarimetric Weather Radar</title><author>Frech, Michael ; Hagen, Martin ; Mammen, Theo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-626a5d02b6183dc8ac0c0b30baa25d19979d74e5be1e23a9345eb5f10dbe7f563</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Atmospheric precipitations</topic><topic>Bias</topic><topic>Calibration</topic><topic>Climatology</topic><topic>Disdrometers</topic><topic>Dual polarization radar</topic><topic>Measurement</topic><topic>Polarization</topic><topic>Precipitation</topic><topic>Radar</topic><topic>Radar calibration</topic><topic>Radar measurement</topic><topic>Radar polarimetry</topic><topic>Radar reflectivity</topic><topic>Radar systems</topic><topic>Rain</topic><topic>Rainfall measurement</topic><topic>Reflectance</topic><topic>Remote sensing</topic><topic>Scanning</topic><topic>Sensors</topic><topic>Warm seasons</topic><topic>Weather</topic><topic>Weather radar</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Frech, Michael</creatorcontrib><creatorcontrib>Hagen, Martin</creatorcontrib><creatorcontrib>Mammen, Theo</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><jtitle>Journal of atmospheric and oceanic technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Frech, Michael</au><au>Hagen, Martin</au><au>Mammen, Theo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Monitoring the Absolute Calibration of a Polarimetric Weather Radar</atitle><jtitle>Journal of atmospheric and oceanic technology</jtitle><date>2017-03-01</date><risdate>2017</risdate><volume>34</volume><issue>3</issue><spage>599</spage><epage>615</epage><pages>599-615</pages><issn>0739-0572</issn><eissn>1520-0426</eissn><abstract>The absolute calibration of a dual-polarization radar of the German Weather Service is continuously monitored using the operational birdbath scan and collocated disdrometer measurements at the Hohenpeissenberg observatory. The goal is to measure the radar reflectivity constant
Z
better than ±1 dB. The assumption is that a disdrometer measurement close to the surface can be related to the radar measurement at the first far-field range bin. This is verified using a Micro Rain Radar (MRR). The MRR data fill the gap between the measurement near the surface and the far-field range bin at 650 m. Using data from the first half of the warm season in 2014, a bias in radar calibration of 1.8 dB is found. Data from only stratiform precipitation events are considered. After adjusting the radar calibration and using an independent data sample, very good agreement is found between the radar, the MRR, and the disdrometer with a bias in
smaller than 1 dB. The bias in
is not captured with the classic one-point calibration, which is performed twice a day using a built-in test signal generator. This is attributed to the fact that the characterization of the transmit and receive path is not accurate enough. Solar interferences during the operational scanning are used to characterize the receiver. There, the bias found is small, about 0.2 dB, so that bias based on the comparison of the radar with external sensors is attributed to the transmit path. The representativeness of the disdrometer measurements are assessed using two additional disdrometers located within 200-m distance.</abstract><cop>Boston</cop><pub>American Meteorological Society</pub><doi>10.1175/JTECH-D-16-0076.1</doi><tpages>17</tpages><oa>free_for_read</oa></addata></record> |
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source | American Meteorological Society; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection |
subjects | Accuracy Algorithms Atmospheric precipitations Bias Calibration Climatology Disdrometers Dual polarization radar Measurement Polarization Precipitation Radar Radar calibration Radar measurement Radar polarimetry Radar reflectivity Radar systems Rain Rainfall measurement Reflectance Remote sensing Scanning Sensors Warm seasons Weather Weather radar |
title | Monitoring the Absolute Calibration of a Polarimetric Weather Radar |
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