Derivation of Cloud-Free-Region Atmospheric Motion Vectors from FY-2E Thermal Infrared Imagery
The operational cloud-motion tracking technique fails to retrieve atmospheric motion vectors （AMVs） in areas lacking cloud; and while water vapor shown in water vapor imagery can be used, the heights assigned to the retrieved AMVs are mostly in the upper troposphere. As the noise-equivalent temperat...
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| Veröffentlicht in: | Advances in atmospheric sciences 2017-02, Vol.34 (2), p.272-282 |
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| creator | Wang, Zhenhui Sui, Xinxiu Zhang, Qing Yang, Lu Zhao, Hang Tang, Min Zhan, Yizhe Zhang, Zhiguo |
| description | The operational cloud-motion tracking technique fails to retrieve atmospheric motion vectors （AMVs） in areas lacking cloud; and while water vapor shown in water vapor imagery can be used, the heights assigned to the retrieved AMVs are mostly in the upper troposphere. As the noise-equivalent temperature difference （NEdT） performance of FY-2E split win- dow （10.3-11.5 μm, 11.6-12.8 μm） channels has been improved, the weak signals representing the spatial texture of water vapor and aerosols in cloud-free areas can be strengthened with algorithms based on the difference principle, and applied in calculating AMVs in the lower troposphere. This paper is a preliminary summary for this purpose, in which the principles and algorithm schemes for the temporal difference, split window difference and second-order difference （SD） methods are introduced. Results from simulation and cases experiments are reported in order to verify and evaluate the methods, based on comparison among retrievals and the ＂truth＂. The results show that all three algorithms, though not perfect in some cases, generally work well. Moreover, the SD method appears to be the best in suppressing the surface temperature influence and clarifying the spatial texture of water vapor and aerosols. The accuracy with respect to NCEP 800 hPa reanalysis data was found to be acceptable, as compared with the accuracy of the cloud motion vectors. |
| doi_str_mv | 10.1007/s00376-016-6098-7 |
| format | Article |
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As the noise-equivalent temperature difference （NEdT） performance of FY-2E split win- dow （10.3-11.5 μm, 11.6-12.8 μm） channels has been improved, the weak signals representing the spatial texture of water vapor and aerosols in cloud-free areas can be strengthened with algorithms based on the difference principle, and applied in calculating AMVs in the lower troposphere. This paper is a preliminary summary for this purpose, in which the principles and algorithm schemes for the temporal difference, split window difference and second-order difference （SD） methods are introduced. Results from simulation and cases experiments are reported in order to verify and evaluate the methods, based on comparison among retrievals and the ＂truth＂. The results show that all three algorithms, though not perfect in some cases, generally work well. Moreover, the SD method appears to be the best in suppressing the surface temperature influence and clarifying the spatial texture of water vapor and aerosols. The accuracy with respect to NCEP 800 hPa reanalysis data was found to be acceptable, as compared with the accuracy of the cloud motion vectors.</description><identifier>ISSN: 0256-1530</identifier><identifier>EISSN: 1861-9533</identifier><identifier>DOI: 10.1007/s00376-016-6098-7</identifier><language>eng</language><publisher>Heidelberg: Science Press</publisher><subject>Aerosols ; Algorithms ; Atmospheric Sciences ; Clouds ; Earth and Environmental Science ; Earth Sciences ; Geophysics/Geodesy ; Infrared imaging systems ; Meteorology ; NCEP再分析资料 ; Original Paper ; Surface temperature ; Troposphere ; Water vapor ; 二阶差分 ; 噪声等效温差 ; 图像显示 ; 大气 ; 热红外图像 ; 跟踪技术 ; 运动矢量</subject><ispartof>Advances in atmospheric sciences, 2017-02, Vol.34 (2), p.272-282</ispartof><rights>Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag Berlin Heidelberg 2017</rights><rights>Advances in Atmospheric Sciences is a copyright of Springer, 2017.</rights><rights>Copyright © Wanfang Data Co. 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All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c443t-5ae13ff4d360a28c9d886b01c19ec10c6a7d6126b8b177fa71db48066c2fa6223</citedby><cites>FETCH-LOGICAL-c443t-5ae13ff4d360a28c9d886b01c19ec10c6a7d6126b8b177fa71db48066c2fa6223</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://image.cqvip.com/vip1000/qk/84334X/84334X.jpg</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00376-016-6098-7$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00376-016-6098-7$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51297</link.rule.ids></links><search><creatorcontrib>Wang, Zhenhui</creatorcontrib><creatorcontrib>Sui, Xinxiu</creatorcontrib><creatorcontrib>Zhang, Qing</creatorcontrib><creatorcontrib>Yang, Lu</creatorcontrib><creatorcontrib>Zhao, Hang</creatorcontrib><creatorcontrib>Tang, Min</creatorcontrib><creatorcontrib>Zhan, Yizhe</creatorcontrib><creatorcontrib>Zhang, Zhiguo</creatorcontrib><title>Derivation of Cloud-Free-Region Atmospheric Motion Vectors from FY-2E Thermal Infrared Imagery</title><title>Advances in atmospheric sciences</title><addtitle>Adv. Atmos. Sci</addtitle><addtitle>Advances in Atmospheric Sciences</addtitle><description>The operational cloud-motion tracking technique fails to retrieve atmospheric motion vectors （AMVs） in areas lacking cloud; and while water vapor shown in water vapor imagery can be used, the heights assigned to the retrieved AMVs are mostly in the upper troposphere. As the noise-equivalent temperature difference （NEdT） performance of FY-2E split win- dow （10.3-11.5 μm, 11.6-12.8 μm） channels has been improved, the weak signals representing the spatial texture of water vapor and aerosols in cloud-free areas can be strengthened with algorithms based on the difference principle, and applied in calculating AMVs in the lower troposphere. This paper is a preliminary summary for this purpose, in which the principles and algorithm schemes for the temporal difference, split window difference and second-order difference （SD） methods are introduced. Results from simulation and cases experiments are reported in order to verify and evaluate the methods, based on comparison among retrievals and the ＂truth＂. The results show that all three algorithms, though not perfect in some cases, generally work well. Moreover, the SD method appears to be the best in suppressing the surface temperature influence and clarifying the spatial texture of water vapor and aerosols. The accuracy with respect to NCEP 800 hPa reanalysis data was found to be acceptable, as compared with the accuracy of the cloud motion vectors.</description><subject>Aerosols</subject><subject>Algorithms</subject><subject>Atmospheric Sciences</subject><subject>Clouds</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Geophysics/Geodesy</subject><subject>Infrared imaging systems</subject><subject>Meteorology</subject><subject>NCEP再分析资料</subject><subject>Original Paper</subject><subject>Surface temperature</subject><subject>Troposphere</subject><subject>Water vapor</subject><subject>二阶差分</subject><subject>噪声等效温差</subject><subject>图像显示</subject><subject>大气</subject><subject>热红外图像</subject><subject>跟踪技术</subject><subject>运动矢量</subject><issn>0256-1530</issn><issn>1861-9533</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNqF0U1vEzEQBmCrAqmh8AN6W8EFDi4ee_11rNKmjVSEhAoSl1qO104TdteJvaEtv74OW1WIA1xsyXreGWsGoWMgJ0CI_JgJYVJgAgILohWWB2gCSgDWnLEXaEIoFxg4I4foVc7rojVTMEE3Zz6tftphFfsqhmraxl2DZ8l7_MUv94-nQxfz5rYoV32Kv90374aYchVS7KrZd0zPq-sCOttW8z4km3xTzTu79OnhNXoZbJv9m6f7CH2dnV9PL_HV54v59PQKu7pmA-bWAwuhbpggliqnG6XEgoAD7R0QJ6xsBFCxUAuQMlgJzaJWRAhHgxWUsiP0Yax7Z_tg-6VZx13qS0fTbH_cr38ZTwlIUg5W7PvRblLc7nweTLfKzret7X3cZQMatBaUa_J_qriuFVVaFfruL_r8haK4ULzmvCgYlUsx5-SD2aRVZ9ODAWL2izTjIk1ZpNkv0siSoWMmF9uXqf5R-R-ht0-NbmO_3JbccychoUyBMcUeAVhpqYE</recordid><startdate>20170201</startdate><enddate>20170201</enddate><creator>Wang, Zhenhui</creator><creator>Sui, Xinxiu</creator><creator>Zhang, Qing</creator><creator>Yang, Lu</creator><creator>Zhao, Hang</creator><creator>Tang, Min</creator><creator>Zhan, Yizhe</creator><creator>Zhang, Zhiguo</creator><general>Science Press</general><general>Springer Nature B.V</general><general>Beijing Meteorological Office(Da Xing), Beijing 102600, China</general><general>School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, China%School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, China</general><scope>2RA</scope><scope>92L</scope><scope>CQIGP</scope><scope>W94</scope><scope>~WA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TG</scope><scope>7XB</scope><scope>88F</scope><scope>88I</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>M1Q</scope><scope>M2P</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>7UA</scope><scope>C1K</scope><scope>7QH</scope><scope>7TN</scope><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope></search><sort><creationdate>20170201</creationdate><title>Derivation of Cloud-Free-Region Atmospheric Motion Vectors from FY-2E Thermal Infrared Imagery</title><author>Wang, Zhenhui ; 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Atmos. Sci</stitle><addtitle>Advances in Atmospheric Sciences</addtitle><date>2017-02-01</date><risdate>2017</risdate><volume>34</volume><issue>2</issue><spage>272</spage><epage>282</epage><pages>272-282</pages><issn>0256-1530</issn><eissn>1861-9533</eissn><abstract>The operational cloud-motion tracking technique fails to retrieve atmospheric motion vectors （AMVs） in areas lacking cloud; and while water vapor shown in water vapor imagery can be used, the heights assigned to the retrieved AMVs are mostly in the upper troposphere. As the noise-equivalent temperature difference （NEdT） performance of FY-2E split win- dow （10.3-11.5 μm, 11.6-12.8 μm） channels has been improved, the weak signals representing the spatial texture of water vapor and aerosols in cloud-free areas can be strengthened with algorithms based on the difference principle, and applied in calculating AMVs in the lower troposphere. This paper is a preliminary summary for this purpose, in which the principles and algorithm schemes for the temporal difference, split window difference and second-order difference （SD） methods are introduced. Results from simulation and cases experiments are reported in order to verify and evaluate the methods, based on comparison among retrievals and the ＂truth＂. The results show that all three algorithms, though not perfect in some cases, generally work well. Moreover, the SD method appears to be the best in suppressing the surface temperature influence and clarifying the spatial texture of water vapor and aerosols. The accuracy with respect to NCEP 800 hPa reanalysis data was found to be acceptable, as compared with the accuracy of the cloud motion vectors.</abstract><cop>Heidelberg</cop><pub>Science Press</pub><doi>10.1007/s00376-016-6098-7</doi><tpages>11</tpages></addata></record> |
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| subjects | Aerosols Algorithms Atmospheric Sciences Clouds Earth and Environmental Science Earth Sciences Geophysics/Geodesy Infrared imaging systems Meteorology NCEP再分析资料 Original Paper Surface temperature Troposphere Water vapor 二阶差分 噪声等效温差 图像显示 大气 热红外图像 跟踪技术 运动矢量 |
| title | Derivation of Cloud-Free-Region Atmospheric Motion Vectors from FY-2E Thermal Infrared Imagery |
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