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    The CALIPSO Lidar Cloud and Aerosol Discrimination: Version 2 Algorithm and Initial Assessment of Performance

    Source: Journal of Atmospheric and Oceanic Technology:;2009:;volume( 026 ):;issue: 007::page 1198
    Author:
    Liu, Zhaoyan
    ,
    Vaughan, Mark
    ,
    Winker, David
    ,
    Kittaka, Chieko
    ,
    Getzewich, Brian
    ,
    Kuehn, Ralph
    ,
    Omar, Ali
    ,
    Powell, Kathleen
    ,
    Trepte, Charles
    ,
    Hostetler, Chris
    DOI: 10.1175/2009JTECHA1229.1
    Publisher: American Meteorological Society
    Abstract: The Cloud?Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite was launched in April 2006 to provide global vertically resolved measurements of clouds and aerosols. Correct discrimination between clouds and aerosols observed by the lidar aboard the CALIPSO satellite is critical for accurate retrievals of cloud and aerosol optical properties and the correct interpretation of measurements. This paper reviews the theoretical basis of the CALIPSO lidar cloud and aerosol discrimination (CAD) algorithm, and describes the enhancements made to the version 2 algorithm that is used in the current data release (release 2). The paper also presents a preliminary assessment of the CAD performance based on one full day (12 August 2006) of expert manual classification and on one full month (July 2006) of the CALIOP 5-km cloud and aerosol layer products. Overall, the CAD algorithm works well in most cases. The 1-day manual verification suggests that the success rate is in the neighborhood of 90% or better. Nevertheless, several specific layer types are still misclassified with some frequency. Among these, the most prevalent are dense dust and smoke close to the source regions. The analysis of the July 2006 data showed that the misclassification of dust as cloud occurs for <1% of the total tropospheric cloud and aerosol features found. Smoke layers are misclassified less frequently than are dust layers. Optically thin clouds in the polar regions can be misclassified as aerosols. While the fraction of such misclassifications is small compared with the number of aerosol features found globally, caution should be taken when studies are performed on the aerosol in the polar regions. Modifications will be made to the CAD algorithm in future data releases, and the misclassifications encountered in the current data release are expected to be reduced greatly.
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      The CALIPSO Lidar Cloud and Aerosol Discrimination: Version 2 Algorithm and Initial Assessment of Performance

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    contributor authorLiu, Zhaoyan
    contributor authorVaughan, Mark
    contributor authorWinker, David
    contributor authorKittaka, Chieko
    contributor authorGetzewich, Brian
    contributor authorKuehn, Ralph
    contributor authorOmar, Ali
    contributor authorPowell, Kathleen
    contributor authorTrepte, Charles
    contributor authorHostetler, Chris
    date accessioned2017-06-09T16:31:10Z
    date available2017-06-09T16:31:10Z
    date copyright2009/07/01
    date issued2009
    identifier issn0739-0572
    identifier otherams-69300.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4210953
    description abstractThe Cloud?Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite was launched in April 2006 to provide global vertically resolved measurements of clouds and aerosols. Correct discrimination between clouds and aerosols observed by the lidar aboard the CALIPSO satellite is critical for accurate retrievals of cloud and aerosol optical properties and the correct interpretation of measurements. This paper reviews the theoretical basis of the CALIPSO lidar cloud and aerosol discrimination (CAD) algorithm, and describes the enhancements made to the version 2 algorithm that is used in the current data release (release 2). The paper also presents a preliminary assessment of the CAD performance based on one full day (12 August 2006) of expert manual classification and on one full month (July 2006) of the CALIOP 5-km cloud and aerosol layer products. Overall, the CAD algorithm works well in most cases. The 1-day manual verification suggests that the success rate is in the neighborhood of 90% or better. Nevertheless, several specific layer types are still misclassified with some frequency. Among these, the most prevalent are dense dust and smoke close to the source regions. The analysis of the July 2006 data showed that the misclassification of dust as cloud occurs for <1% of the total tropospheric cloud and aerosol features found. Smoke layers are misclassified less frequently than are dust layers. Optically thin clouds in the polar regions can be misclassified as aerosols. While the fraction of such misclassifications is small compared with the number of aerosol features found globally, caution should be taken when studies are performed on the aerosol in the polar regions. Modifications will be made to the CAD algorithm in future data releases, and the misclassifications encountered in the current data release are expected to be reduced greatly.
    publisherAmerican Meteorological Society
    titleThe CALIPSO Lidar Cloud and Aerosol Discrimination: Version 2 Algorithm and Initial Assessment of Performance
    typeJournal Paper
    journal volume26
    journal issue7
    journal titleJournal of Atmospheric and Oceanic Technology
    identifier doi10.1175/2009JTECHA1229.1
    journal fristpage1198
    journal lastpage1213
    treeJournal of Atmospheric and Oceanic Technology:;2009:;volume( 026 ):;issue: 007
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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