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    Automatic Clouds Observation Improved by an Artificial Neural Network

    Source: Journal of Atmospheric and Oceanic Technology:;1998:;volume( 015 ):;issue: 001::page 114
    Author:
    Aviolat, Frédéric
    ,
    Cornu, Thierry
    ,
    Cattani, Daniel
    DOI: 10.1175/1520-0426(1998)015<0114:ACOIBA>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: This paper refers to a project aimed at building a device able to generate fully automatic meteorological weather reports (METAR) during the night at Swiss airports. Such reports include the description of sky conditions, namely, the heights and the amount of clouds at different layers, which may not be directly measured by conventional instruments. The authors present a cloud module that is specifically designed to provide the information on the clouds present in the sky. The originality of the present work is the use of a longwave radiometer, a pyrgeometer, to estimate the cloud amounts, whose processing is performed by an artificial neural network instead of empirical rules. Laser ceilometers are used to extract the bases of cloud layers by means of a heuristic processing. Results of this module show that information automatically produced by the module can be used as a good estimate of the clouds in a completely automatic METAR generator.
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      Automatic Clouds Observation Improved by an Artificial Neural Network

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4149068
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    contributor authorAviolat, Frédéric
    contributor authorCornu, Thierry
    contributor authorCattani, Daniel
    date accessioned2017-06-09T14:09:50Z
    date available2017-06-09T14:09:50Z
    date copyright1998/02/01
    date issued1998
    identifier issn0739-0572
    identifier otherams-1360.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4149068
    description abstractThis paper refers to a project aimed at building a device able to generate fully automatic meteorological weather reports (METAR) during the night at Swiss airports. Such reports include the description of sky conditions, namely, the heights and the amount of clouds at different layers, which may not be directly measured by conventional instruments. The authors present a cloud module that is specifically designed to provide the information on the clouds present in the sky. The originality of the present work is the use of a longwave radiometer, a pyrgeometer, to estimate the cloud amounts, whose processing is performed by an artificial neural network instead of empirical rules. Laser ceilometers are used to extract the bases of cloud layers by means of a heuristic processing. Results of this module show that information automatically produced by the module can be used as a good estimate of the clouds in a completely automatic METAR generator.
    publisherAmerican Meteorological Society
    titleAutomatic Clouds Observation Improved by an Artificial Neural Network
    typeJournal Paper
    journal volume15
    journal issue1
    journal titleJournal of Atmospheric and Oceanic Technology
    identifier doi10.1175/1520-0426(1998)015<0114:ACOIBA>2.0.CO;2
    journal fristpage114
    journal lastpage126
    treeJournal of Atmospheric and Oceanic Technology:;1998:;volume( 015 ):;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