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    Validation of Automatic Cb Observations for METAR Messages without Ground Truth

    Source: Journal of Applied Meteorology and Climatology:;2015:;volume( 054 ):;issue: 010::page 2063
    Author:
    Hyvärinen, Otto
    ,
    Saltikoff, Elena
    ,
    Hohti, Harri
    DOI: 10.1175/JAMC-D-14-0222.1
    Publisher: American Meteorological Society
    Abstract: n aviation meteorology, METAR messages are used to disseminate the existence of cumulonimbus (Cb) clouds. METAR messages are traditionally constructed manually from human observations, but there is a growing trend toward automation of this process. At the Finnish Meteorological Institute (FMI), METAR messages incorporate an operational automatic detection of Cb based solely on weather radar data, when manual observations are not available. However, the verification of this automatic Cb detection is challenging, as good ground truth data are not often available; even human observations are not perfect as Cb clouds can be obscured by other clouds, for example. Therefore, statistical estimation of the relevant verification measures from imperfect observations using latent class analysis (LCA) was explored. In addition to radar-based products and human observations, the convective rainfall rate from EUMETSAT?s Nowcasting Satellite Application Facility and lightning products from the Finnish lightning network were used for determining the existence of Cb clouds. Results suggest that LCA gives reasonable estimates of verification measures and, based on these estimates, the Cb detection system at FMI gives results comparable to human observations.
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      Validation of Automatic Cb Observations for METAR Messages without Ground Truth

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4217428
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    contributor authorHyvärinen, Otto
    contributor authorSaltikoff, Elena
    contributor authorHohti, Harri
    date accessioned2017-06-09T16:50:35Z
    date available2017-06-09T16:50:35Z
    date copyright2015/10/01
    date issued2015
    identifier issn1558-8424
    identifier otherams-75126.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4217428
    description abstractn aviation meteorology, METAR messages are used to disseminate the existence of cumulonimbus (Cb) clouds. METAR messages are traditionally constructed manually from human observations, but there is a growing trend toward automation of this process. At the Finnish Meteorological Institute (FMI), METAR messages incorporate an operational automatic detection of Cb based solely on weather radar data, when manual observations are not available. However, the verification of this automatic Cb detection is challenging, as good ground truth data are not often available; even human observations are not perfect as Cb clouds can be obscured by other clouds, for example. Therefore, statistical estimation of the relevant verification measures from imperfect observations using latent class analysis (LCA) was explored. In addition to radar-based products and human observations, the convective rainfall rate from EUMETSAT?s Nowcasting Satellite Application Facility and lightning products from the Finnish lightning network were used for determining the existence of Cb clouds. Results suggest that LCA gives reasonable estimates of verification measures and, based on these estimates, the Cb detection system at FMI gives results comparable to human observations.
    publisherAmerican Meteorological Society
    titleValidation of Automatic Cb Observations for METAR Messages without Ground Truth
    typeJournal Paper
    journal volume54
    journal issue10
    journal titleJournal of Applied Meteorology and Climatology
    identifier doi10.1175/JAMC-D-14-0222.1
    journal fristpage2063
    journal lastpage2075
    treeJournal of Applied Meteorology and Climatology:;2015:;volume( 054 ):;issue: 010
    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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