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    A Direct Link between Feature Tracking and Height Assignment of Operational EUMETSAT Atmospheric Motion Vectors

    Source: Journal of Atmospheric and Oceanic Technology:;2013:;volume( 031 ):;issue: 001::page 33
    Author:
    Borde, Régis
    ,
    Doutriaux-Boucher, Marie
    ,
    Dew, Greg
    ,
    Carranza, Manuel
    DOI: 10.1175/JTECH-D-13-00126.1
    Publisher: American Meteorological Society
    Abstract: eight assignment (HA) is currently the most challenging task in the operational atmospheric motion vectors? (AMV) extraction scheme. Several sources of error are associated with the height assignment step, including the sensitivity of the HA methods to several atmospheric parameters. However, one of the main difficulties is to identify, for the HA calculation, the most significant image pixels used in the feature-tracking process. The most widely used method selects the coldest pixels in a representative target box (e.g., coldest 25%) to infer the height of the detected feature, irrespective of what was tracked. This paper presents a method based on a closer link between the pixels used for tracking and their HA. The individual contribution to the overall tracking cross-correlation coefficient is used to identify the most significant pixels contributing to the tracking. This approach has been implemented operationally at European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) to derive AMVs since September 2012. This paper details the method, gives specific examples, and provides a first glance at its performances and benefits for the operational AMV production.
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      A Direct Link between Feature Tracking and Height Assignment of Operational EUMETSAT Atmospheric Motion Vectors

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4228349
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    contributor authorBorde, Régis
    contributor authorDoutriaux-Boucher, Marie
    contributor authorDew, Greg
    contributor authorCarranza, Manuel
    date accessioned2017-06-09T17:25:22Z
    date available2017-06-09T17:25:22Z
    date copyright2014/01/01
    date issued2013
    identifier issn0739-0572
    identifier otherams-84956.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4228349
    description abstracteight assignment (HA) is currently the most challenging task in the operational atmospheric motion vectors? (AMV) extraction scheme. Several sources of error are associated with the height assignment step, including the sensitivity of the HA methods to several atmospheric parameters. However, one of the main difficulties is to identify, for the HA calculation, the most significant image pixels used in the feature-tracking process. The most widely used method selects the coldest pixels in a representative target box (e.g., coldest 25%) to infer the height of the detected feature, irrespective of what was tracked. This paper presents a method based on a closer link between the pixels used for tracking and their HA. The individual contribution to the overall tracking cross-correlation coefficient is used to identify the most significant pixels contributing to the tracking. This approach has been implemented operationally at European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) to derive AMVs since September 2012. This paper details the method, gives specific examples, and provides a first glance at its performances and benefits for the operational AMV production.
    publisherAmerican Meteorological Society
    titleA Direct Link between Feature Tracking and Height Assignment of Operational EUMETSAT Atmospheric Motion Vectors
    typeJournal Paper
    journal volume31
    journal issue1
    journal titleJournal of Atmospheric and Oceanic Technology
    identifier doi10.1175/JTECH-D-13-00126.1
    journal fristpage33
    journal lastpage46
    treeJournal of Atmospheric and Oceanic Technology:;2013:;volume( 031 ):;issue: 001
    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
    yabeshDSpacePersian