Validation of MODIS C6 AOD Products Retrieved by the Dark Target Method in the Beijing–Tianjin–Hebei Urban Agglomeration, China
The quality of the MODIS C6 3-km and 10-km aerosol optical depth（AOD） products retrieved by the Dark Target（DT）method is discussed using ground-based observations in the Beijing–Tianjin–Hebei region from 1 August 2007 to 31 July2008. Good consistency exists between the 3-km and 10-km products and gr...
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| Veröffentlicht in: | Advances in atmospheric sciences 2017-08, Vol.34 (8), p.993-1002 |
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| creator | Zhang, Jie Xin, Jinyuan Zhang, Wenyu Wang, Shigong Wang, Lili Xie, Wei Xiao, Guojie Pan, Hela Kong, Lingbin |
| description | The quality of the MODIS C6 3-km and 10-km aerosol optical depth（AOD） products retrieved by the Dark Target（DT）method is discussed using ground-based observations in the Beijing–Tianjin–Hebei region from 1 August 2007 to 31 July2008. Good consistency exists between the 3-km and 10-km products and ground-based observations. The retrieval accuracy of the two products both show distinctive seasonality. The percentage falling within the expected error（EE） is largest in the winter, moderate in the spring and autumn, and smallest in the summer. A worse overestimation appears in the spring and summer（27%–66%）. However, the 3-km and 10-km products over different surfaces still exhibit obvious deviations. The 10-km product performs better in the large cities, while the 3-km product has advantages in the suburbs. In urban areas, the percentage falling within EE of the 3-km AOD product（18%–59%） is lower than that for the 10-km AOD product（31%–69%）. However, in suburban areas, the percentage falling within EE of the 3-km AOD product（61%–84%） is higher than for the 10 km AOD product（54%–83%）.The percentages falling within EE differ considerably when the AOD is greater than1.5（73% and 63% for the 3-km and 10-km products, respectively）. On the whole, the 3-km（10-km） AOD product performs better in suburban（urban） areas. |
| doi_str_mv | 10.1007/s00376-016-6217-5 |
| format | Article |
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Good consistency exists between the 3-km and 10-km products and ground-based observations. The retrieval accuracy of the two products both show distinctive seasonality. The percentage falling within the expected error（EE） is largest in the winter, moderate in the spring and autumn, and smallest in the summer. A worse overestimation appears in the spring and summer（27%–66%）. However, the 3-km and 10-km products over different surfaces still exhibit obvious deviations. The 10-km product performs better in the large cities, while the 3-km product has advantages in the suburbs. In urban areas, the percentage falling within EE of the 3-km AOD product（18%–59%） is lower than that for the 10-km AOD product（31%–69%）. However, in suburban areas, the percentage falling within EE of the 3-km AOD product（61%–84%） is higher than for the 10 km AOD product（54%–83%）.The percentages falling within EE differ considerably when the AOD is greater than1.5（73% and 63% for the 3-km and 10-km products, respectively）. On the whole, the 3-km（10-km） AOD product performs better in suburban（urban） areas.</description><identifier>ISSN: 0256-1530</identifier><identifier>EISSN: 1861-9533</identifier><identifier>DOI: 10.1007/s00376-016-6217-5</identifier><language>eng</language><publisher>Heidelberg: Science Press</publisher><subject>Aerosol optical depth ; Aerosols ; Agglomeration ; Airborne particulates ; AOD ; Atmospheric aerosols ; Atmospheric Sciences ; Autumn ; Depth ; Earth and Environmental Science ; Earth Sciences ; Falling ; Geophysics/Geodesy ; Ground-based observation ; Meteorology ; Methods ; MODIS ; Optical analysis ; Original Paper ; Products ; Seasonal variations ; Seasonality ; Spring ; Spring (season) ; Suburban areas ; Suburbs ; Summer ; Urban areas ; Winter ; 产品 ; 北京 ; 城市群 ; 天津 ; 检索 ; 河北</subject><ispartof>Advances in atmospheric sciences, 2017-08, Vol.34 (8), p.993-1002</ispartof><rights>Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag GmbH Germany 2017</rights><rights>Advances in Atmospheric Sciences is a copyright of Springer, 2017.</rights><rights>Copyright © Wanfang Data Co. Ltd. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c377t-3ef1e5deebfcb84c1beda568562c2825ee7511574fd6c51e13e5b9e0086db3f53</citedby><cites>FETCH-LOGICAL-c377t-3ef1e5deebfcb84c1beda568562c2825ee7511574fd6c51e13e5b9e0086db3f53</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/s00376-016-6217-5$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00376-016-6217-5$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>315,781,785,27929,27930,41493,42562,51324</link.rule.ids></links><search><creatorcontrib>Zhang, Jie</creatorcontrib><creatorcontrib>Xin, Jinyuan</creatorcontrib><creatorcontrib>Zhang, Wenyu</creatorcontrib><creatorcontrib>Wang, Shigong</creatorcontrib><creatorcontrib>Wang, Lili</creatorcontrib><creatorcontrib>Xie, Wei</creatorcontrib><creatorcontrib>Xiao, Guojie</creatorcontrib><creatorcontrib>Pan, Hela</creatorcontrib><creatorcontrib>Kong, Lingbin</creatorcontrib><title>Validation of MODIS C6 AOD Products Retrieved by the Dark Target Method in the Beijing–Tianjin–Hebei Urban Agglomeration, China</title><title>Advances in atmospheric sciences</title><addtitle>Adv. Atmos. Sci</addtitle><addtitle>Advances in Atmospheric Sciences</addtitle><description>The quality of the MODIS C6 3-km and 10-km aerosol optical depth（AOD） products retrieved by the Dark Target（DT）method is discussed using ground-based observations in the Beijing–Tianjin–Hebei region from 1 August 2007 to 31 July2008. Good consistency exists between the 3-km and 10-km products and ground-based observations. The retrieval accuracy of the two products both show distinctive seasonality. The percentage falling within the expected error（EE） is largest in the winter, moderate in the spring and autumn, and smallest in the summer. A worse overestimation appears in the spring and summer（27%–66%）. However, the 3-km and 10-km products over different surfaces still exhibit obvious deviations. The 10-km product performs better in the large cities, while the 3-km product has advantages in the suburbs. In urban areas, the percentage falling within EE of the 3-km AOD product（18%–59%） is lower than that for the 10-km AOD product（31%–69%）. However, in suburban areas, the percentage falling within EE of the 3-km AOD product（61%–84%） is higher than for the 10 km AOD product（54%–83%）.The percentages falling within EE differ considerably when the AOD is greater than1.5（73% and 63% for the 3-km and 10-km products, respectively）. On the whole, the 3-km（10-km） AOD product performs better in suburban（urban） areas.</description><subject>Aerosol optical depth</subject><subject>Aerosols</subject><subject>Agglomeration</subject><subject>Airborne particulates</subject><subject>AOD</subject><subject>Atmospheric aerosols</subject><subject>Atmospheric Sciences</subject><subject>Autumn</subject><subject>Depth</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Falling</subject><subject>Geophysics/Geodesy</subject><subject>Ground-based observation</subject><subject>Meteorology</subject><subject>Methods</subject><subject>MODIS</subject><subject>Optical analysis</subject><subject>Original Paper</subject><subject>Products</subject><subject>Seasonal variations</subject><subject>Seasonality</subject><subject>Spring</subject><subject>Spring (season)</subject><subject>Suburban areas</subject><subject>Suburbs</subject><subject>Summer</subject><subject>Urban areas</subject><subject>Winter</subject><subject>产品</subject><subject>北京</subject><subject>城市群</subject><subject>天津</subject><subject>检索</subject><subject>河北</subject><issn>0256-1530</issn><issn>1861-9533</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</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>eNp9kcFu1DAQhiNEJZaWB-BmwQmpKZ44tpPjsgu0UqtFsOVqOfEk6-3W7tpZoJyQ-gi8IU-Ct6mAE6cZab5__tH8WfYc6AlQKl9HSpkUOQWRiwJkzh9lE6gE5DVn7HE2oQUXOXBGn2RPY1wnumYVTLK7z3pjjR6sd8R35GIxP_tEZoJMF3PyIXiza4dIPuIQLH5BQ5pbMqyQzHW4IksdehzIBQ4rb4h195M3aNfW9b9-_Fxa7VKbulNs0JLL0GhHpn2_8dcY7h2PyWxlnT7KDjq9ifjsoR5ml-_eLmen-fni_dlsep63TMohZ9gBcoPYdG1TlS00aDQXFRdFW1QFR5QcgMuyM6LlgMCQNzVSWgnTsI6zw-zVuPerdp12vVr7XXDJUZnt1bf1d4UFBUmr9M_EvhzZm-C3O4zDXxhqKMuylrxMFIxUG3yMATt1E-y1DrcKqNrnosZcVMpF7XNR-yuKURMT63oM_2z-j-jFg9HKu36bdH-chCx4XTLG2W_2jZzE</recordid><startdate>20170801</startdate><enddate>20170801</enddate><creator>Zhang, Jie</creator><creator>Xin, Jinyuan</creator><creator>Zhang, Wenyu</creator><creator>Wang, Shigong</creator><creator>Wang, Lili</creator><creator>Xie, Wei</creator><creator>Xiao, Guojie</creator><creator>Pan, Hela</creator><creator>Kong, Lingbin</creator><general>Science Press</general><general>Springer Nature B.V</general><general>College of Atmospheric Sciences, Chengdu University of Information Technology, Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu 610225, China</general><general>College of Atmospheric Sciences, Chengdu University of Information Technology, Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu 610225, China%Key Laboratory of Arid Climatic Change and Reducing Disaster of Gansu Province, College of Atmospheric Sciences,Lanzhou University, Lanzhou 730000, China%College of Atmospheric Sciences, Chengdu University of Information Technology, Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu 610225, China%State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics,Chinese Academy of Sciences, Beijing 100029, China</general><general>Key Laboratory of Arid Climatic Change and Reducing Disaster of Gansu Province, College of Atmospheric Sciences,Lanzhou University, Lanzhou 730000, China%State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics,Chinese Academy of Sciences, Beijing 100029, 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>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>PRINS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope></search><sort><creationdate>20170801</creationdate><title>Validation of MODIS C6 AOD Products Retrieved by the Dark Target Method in the Beijing–Tianjin–Hebei Urban Agglomeration, China</title><author>Zhang, Jie ; Xin, Jinyuan ; Zhang, Wenyu ; Wang, Shigong ; Wang, Lili ; Xie, Wei ; Xiao, Guojie ; Pan, Hela ; Kong, Lingbin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c377t-3ef1e5deebfcb84c1beda568562c2825ee7511574fd6c51e13e5b9e0086db3f53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Aerosol optical depth</topic><topic>Aerosols</topic><topic>Agglomeration</topic><topic>Airborne particulates</topic><topic>AOD</topic><topic>Atmospheric aerosols</topic><topic>Atmospheric Sciences</topic><topic>Autumn</topic><topic>Depth</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Falling</topic><topic>Geophysics/Geodesy</topic><topic>Ground-based observation</topic><topic>Meteorology</topic><topic>Methods</topic><topic>MODIS</topic><topic>Optical analysis</topic><topic>Original Paper</topic><topic>Products</topic><topic>Seasonal variations</topic><topic>Seasonality</topic><topic>Spring</topic><topic>Spring (season)</topic><topic>Suburban areas</topic><topic>Suburbs</topic><topic>Summer</topic><topic>Urban areas</topic><topic>Winter</topic><topic>产品</topic><topic>北京</topic><topic>城市群</topic><topic>天津</topic><topic>检索</topic><topic>河北</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Jie</creatorcontrib><creatorcontrib>Xin, Jinyuan</creatorcontrib><creatorcontrib>Zhang, Wenyu</creatorcontrib><creatorcontrib>Wang, Shigong</creatorcontrib><creatorcontrib>Wang, Lili</creatorcontrib><creatorcontrib>Xie, Wei</creatorcontrib><creatorcontrib>Xiao, Guojie</creatorcontrib><creatorcontrib>Pan, Hela</creatorcontrib><creatorcontrib>Kong, Lingbin</creatorcontrib><collection>中文科技期刊数据库</collection><collection>中文科技期刊数据库-CALIS站点</collection><collection>中文科技期刊数据库-7.0平台</collection><collection>中文科技期刊数据库-自然科学</collection><collection>中文科技期刊数据库- 镜像站点</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Military Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</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>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>Military Database</collection><collection>Science Database</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>ProQuest Central China</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Wanfang Data Journals - Hong Kong</collection><collection>WANFANG Data Centre</collection><collection>Wanfang Data Journals</collection><collection>万方数据期刊 - 香港版</collection><collection>China Online Journals (COJ)</collection><collection>China Online Journals (COJ)</collection><jtitle>Advances in atmospheric sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Jie</au><au>Xin, Jinyuan</au><au>Zhang, Wenyu</au><au>Wang, Shigong</au><au>Wang, Lili</au><au>Xie, Wei</au><au>Xiao, Guojie</au><au>Pan, Hela</au><au>Kong, Lingbin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Validation of MODIS C6 AOD Products Retrieved by the Dark Target Method in the Beijing–Tianjin–Hebei Urban Agglomeration, China</atitle><jtitle>Advances in atmospheric sciences</jtitle><stitle>Adv. Atmos. Sci</stitle><addtitle>Advances in Atmospheric Sciences</addtitle><date>2017-08-01</date><risdate>2017</risdate><volume>34</volume><issue>8</issue><spage>993</spage><epage>1002</epage><pages>993-1002</pages><issn>0256-1530</issn><eissn>1861-9533</eissn><abstract>The quality of the MODIS C6 3-km and 10-km aerosol optical depth（AOD） products retrieved by the Dark Target（DT）method is discussed using ground-based observations in the Beijing–Tianjin–Hebei region from 1 August 2007 to 31 July2008. Good consistency exists between the 3-km and 10-km products and ground-based observations. The retrieval accuracy of the two products both show distinctive seasonality. The percentage falling within the expected error（EE） is largest in the winter, moderate in the spring and autumn, and smallest in the summer. A worse overestimation appears in the spring and summer（27%–66%）. However, the 3-km and 10-km products over different surfaces still exhibit obvious deviations. The 10-km product performs better in the large cities, while the 3-km product has advantages in the suburbs. In urban areas, the percentage falling within EE of the 3-km AOD product（18%–59%） is lower than that for the 10-km AOD product（31%–69%）. However, in suburban areas, the percentage falling within EE of the 3-km AOD product（61%–84%） is higher than for the 10 km AOD product（54%–83%）.The percentages falling within EE differ considerably when the AOD is greater than1.5（73% and 63% for the 3-km and 10-km products, respectively）. On the whole, the 3-km（10-km） AOD product performs better in suburban（urban） areas.</abstract><cop>Heidelberg</cop><pub>Science Press</pub><doi>10.1007/s00376-016-6217-5</doi><tpages>10</tpages></addata></record> |
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| subjects | Aerosol optical depth Aerosols Agglomeration Airborne particulates AOD Atmospheric aerosols Atmospheric Sciences Autumn Depth Earth and Environmental Science Earth Sciences Falling Geophysics/Geodesy Ground-based observation Meteorology Methods MODIS Optical analysis Original Paper Products Seasonal variations Seasonality Spring Spring (season) Suburban areas Suburbs Summer Urban areas Winter 产品 北京 城市群 天津 检索 河北 |
| title | Validation of MODIS C6 AOD Products Retrieved by the Dark Target Method in the Beijing–Tianjin–Hebei Urban Agglomeration, China |
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