Examination of the Quality of GOSAT/CAI Cloud Flag Data over Beijing Using Ground-based Cloud Data
It has been several years since the Greenhouse Gases Observing Satellite （GOSAT） began to observe the distribution of CO2 and CH4 over the globe from space. Results from Thermal and Near-infrared Sensor for Carbon Observation-Cloud and Aerosol Imager （TANSO-CAI） cloud screening are necessary for the...
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| Veröffentlicht in: | Advances in atmospheric sciences 2013-11, Vol.30 (6), p.1526-1534 |
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| description | It has been several years since the Greenhouse Gases Observing Satellite （GOSAT） began to observe the distribution of CO2 and CH4 over the globe from space. Results from Thermal and Near-infrared Sensor for Carbon Observation-Cloud and Aerosol Imager （TANSO-CAI） cloud screening are necessary for the retrieval of CO2 and CH4 gas concentrations for GOSAT TANSO-Fourier Transform Spectrometer （FTS） observations. In this study, TANSO-CAI cloud flag data were compared with ground-based cloud data collected by an all-sky imager （ASI） over Beijing from June 2009 to May 2012 to examine the data quality. The results showed that the CAI has an obvious cloudy tendency bias over Beijing, especially in winter. The main reason might be that heavy aerosols in the sky are incorrectly determined as cloudy pixels by the CAI algorithm. Results also showed that the CAI algorithm sometimes neglects some high thin cirrus cloud over this area. |
| doi_str_mv | 10.1007/s00376-013-2267-0 |
| format | Article |
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Results from Thermal and Near-infrared Sensor for Carbon Observation-Cloud and Aerosol Imager （TANSO-CAI） cloud screening are necessary for the retrieval of CO2 and CH4 gas concentrations for GOSAT TANSO-Fourier Transform Spectrometer （FTS） observations. In this study, TANSO-CAI cloud flag data were compared with ground-based cloud data collected by an all-sky imager （ASI） over Beijing from June 2009 to May 2012 to examine the data quality. The results showed that the CAI has an obvious cloudy tendency bias over Beijing, especially in winter. The main reason might be that heavy aerosols in the sky are incorrectly determined as cloudy pixels by the CAI algorithm. Results also showed that the CAI algorithm sometimes neglects some high thin cirrus cloud over this area.</description><identifier>ISSN: 0256-1530</identifier><identifier>EISSN: 1861-9533</identifier><identifier>DOI: 10.1007/s00376-013-2267-0</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Aerosols ; Air pollution ; Algorithms ; Artificial satellites ; Atmospheric aerosols ; Atmospheric Sciences ; Atmospherics ; Carbon ; Carbon dioxide ; Clouds ; Earth and Environmental Science ; Earth Sciences ; Flags ; Fourier transforms ; Geophysics/Geodesy ; Greenhouse gases ; Meteorology ; Methane ; 傅立叶变换光谱仪 ; 北京 ; 数据质量 ; 标志数据 ; 红外传感器 ; 考试 ; 观测卫星 ; 陆基</subject><ispartof>Advances in atmospheric sciences, 2013-11, Vol.30 (6), p.1526-1534</ispartof><rights>Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag Berlin Heidelberg 2013</rights><rights>Copyright © Wanfang Data Co. Ltd. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c409t-a44723e2245f0196a7b4b2bc9920a77910b717df8fdda4664c4a932354ee80f23</citedby><cites>FETCH-LOGICAL-c409t-a44723e2245f0196a7b4b2bc9920a77910b717df8fdda4664c4a932354ee80f23</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/s00376-013-2267-0$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00376-013-2267-0$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51298</link.rule.ids></links><search><creatorcontrib>霍娟 章文星 曾晓夏 吕达仁 刘毅</creatorcontrib><title>Examination of the Quality of GOSAT/CAI Cloud Flag Data over Beijing Using Ground-based Cloud Data</title><title>Advances in atmospheric sciences</title><addtitle>Adv. Atmos. Sci</addtitle><addtitle>Advances in Atmospheric Sciences</addtitle><description>It has been several years since the Greenhouse Gases Observing Satellite （GOSAT） began to observe the distribution of CO2 and CH4 over the globe from space. Results from Thermal and Near-infrared Sensor for Carbon Observation-Cloud and Aerosol Imager （TANSO-CAI） cloud screening are necessary for the retrieval of CO2 and CH4 gas concentrations for GOSAT TANSO-Fourier Transform Spectrometer （FTS） observations. In this study, TANSO-CAI cloud flag data were compared with ground-based cloud data collected by an all-sky imager （ASI） over Beijing from June 2009 to May 2012 to examine the data quality. The results showed that the CAI has an obvious cloudy tendency bias over Beijing, especially in winter. The main reason might be that heavy aerosols in the sky are incorrectly determined as cloudy pixels by the CAI algorithm. Results also showed that the CAI algorithm sometimes neglects some high thin cirrus cloud over this area.</description><subject>Aerosols</subject><subject>Air pollution</subject><subject>Algorithms</subject><subject>Artificial satellites</subject><subject>Atmospheric aerosols</subject><subject>Atmospheric Sciences</subject><subject>Atmospherics</subject><subject>Carbon</subject><subject>Carbon dioxide</subject><subject>Clouds</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Flags</subject><subject>Fourier transforms</subject><subject>Geophysics/Geodesy</subject><subject>Greenhouse gases</subject><subject>Meteorology</subject><subject>Methane</subject><subject>傅立叶变换光谱仪</subject><subject>北京</subject><subject>数据质量</subject><subject>标志数据</subject><subject>红外传感器</subject><subject>考试</subject><subject>观测卫星</subject><subject>陆基</subject><issn>0256-1530</issn><issn>1861-9533</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kc1u1DAUhS0EEkPhAdgFsYGF2-v_eDkM7bRSpQrRri0ncdIMGbtjJ9Dy9DjKqEIs2FzrSt8558oHofcETgmAOksATEkMhGFKpcLwAq1IKQnWgrGXaAVUSEwEg9foTUq7TGtWkhWqzh_tvvd27IMvQluM9674NtmhH5_mdXvzfX17tllfFZshTE1xMdiu-GpHW4SfLhZfXL_rfVfcpXluY5h8gyubXHPkZ_QtetXaIbl3x_cE3V2c324u8fXN9mqzvsY1Bz1iy7mizFHKRQtES6sqXtGq1pqCVUoTqBRRTVu2TWO5lLzmVjPKBHeuhJayE_R58f1lfWt9Z3Zhij4nmubw43H32ziavwckwMx-WtiHGA6TS6PZ96l2w2C9C1MyhItS5LOYyujHf9BnX8I5o0IrDpkiC1XHkFJ0rXmI_d7GJ0PAzA2ZpSGTTzBzQ2bW0EWTMus7F_9y_o_owzHoPvjukHXPSVwJSaTm7A9ZA5rH</recordid><startdate>20131101</startdate><enddate>20131101</enddate><creator>霍娟 章文星 曾晓夏 吕达仁 刘毅</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><general>Key Laboratory for Atmosphere and Global Environment Observation, Institute of Atmospheric Physics,Chinese Academy of Sciences, Beijing 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Atmos. Sci</stitle><addtitle>Advances in Atmospheric Sciences</addtitle><date>2013-11-01</date><risdate>2013</risdate><volume>30</volume><issue>6</issue><spage>1526</spage><epage>1534</epage><pages>1526-1534</pages><issn>0256-1530</issn><eissn>1861-9533</eissn><abstract>It has been several years since the Greenhouse Gases Observing Satellite （GOSAT） began to observe the distribution of CO2 and CH4 over the globe from space. Results from Thermal and Near-infrared Sensor for Carbon Observation-Cloud and Aerosol Imager （TANSO-CAI） cloud screening are necessary for the retrieval of CO2 and CH4 gas concentrations for GOSAT TANSO-Fourier Transform Spectrometer （FTS） observations. In this study, TANSO-CAI cloud flag data were compared with ground-based cloud data collected by an all-sky imager （ASI） over Beijing from June 2009 to May 2012 to examine the data quality. The results showed that the CAI has an obvious cloudy tendency bias over Beijing, especially in winter. 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| ispartof | Advances in atmospheric sciences, 2013-11, Vol.30 (6), p.1526-1534 |
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| language | eng |
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| source | Springer journals; Alma/SFX Local Collection |
| subjects | Aerosols Air pollution Algorithms Artificial satellites Atmospheric aerosols Atmospheric Sciences Atmospherics Carbon Carbon dioxide Clouds Earth and Environmental Science Earth Sciences Flags Fourier transforms Geophysics/Geodesy Greenhouse gases Meteorology Methane 傅立叶变换光谱仪 北京 数据质量 标志数据 红外传感器 考试 观测卫星 陆基 |
| title | Examination of the Quality of GOSAT/CAI Cloud Flag Data over Beijing Using Ground-based Cloud Data |
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