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    Mapping GPS Radio Occultation Data by Bayesian Interpolation

    Source: Journal of Atmospheric and Oceanic Technology:;2012:;volume( 029 ):;issue: 008::page 1062
    Author:
    Leroy, Stephen S.
    ,
    Ao, Chi O.
    ,
    Verkhoglyadova, Olga
    DOI: 10.1175/JTECH-D-11-00179.1
    Publisher: American Meteorological Society
    Abstract: ayesian interpolation for mapping GPS radio occultation data on a sphere is explored and its performance evaluated. Bayesian interpolation is ideally suited to the task of fitting data randomly and nonuniformly distributed with unknown error without overfitting the data. The geopotential height at dry pressure 200 hPa is simulated as data with theoretical distributions of the Challenging Mini-Satellite Payload (CHAMP) and of the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC). The simulated CHAMP data are found to be best fit with a spherical harmonic basis of 14th degree; the COSMIC data with a spherical harmonic basis of 20th degree. The best regularizer mimics a spline fit, and relaxing the penalty for purely meridional structures or for the global mean yields little advantage. Climatologies are most accurately established by binning in ?2-day intervals to best resolve synoptic structures in space and time. Finally, Bayesian interpolation is shown to negate a source of systematic sampling error obtained in binning and averaging highly nonuniform data but to incur another systematic error due to incomplete resolution of the background atmosphere, notably in the Southern Hemisphere.
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      Mapping GPS Radio Occultation Data by Bayesian Interpolation

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4227998
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    contributor authorLeroy, Stephen S.
    contributor authorAo, Chi O.
    contributor authorVerkhoglyadova, Olga
    date accessioned2017-06-09T17:24:19Z
    date available2017-06-09T17:24:19Z
    date copyright2012/08/01
    date issued2012
    identifier issn0739-0572
    identifier otherams-84640.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4227998
    description abstractayesian interpolation for mapping GPS radio occultation data on a sphere is explored and its performance evaluated. Bayesian interpolation is ideally suited to the task of fitting data randomly and nonuniformly distributed with unknown error without overfitting the data. The geopotential height at dry pressure 200 hPa is simulated as data with theoretical distributions of the Challenging Mini-Satellite Payload (CHAMP) and of the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC). The simulated CHAMP data are found to be best fit with a spherical harmonic basis of 14th degree; the COSMIC data with a spherical harmonic basis of 20th degree. The best regularizer mimics a spline fit, and relaxing the penalty for purely meridional structures or for the global mean yields little advantage. Climatologies are most accurately established by binning in ?2-day intervals to best resolve synoptic structures in space and time. Finally, Bayesian interpolation is shown to negate a source of systematic sampling error obtained in binning and averaging highly nonuniform data but to incur another systematic error due to incomplete resolution of the background atmosphere, notably in the Southern Hemisphere.
    publisherAmerican Meteorological Society
    titleMapping GPS Radio Occultation Data by Bayesian Interpolation
    typeJournal Paper
    journal volume29
    journal issue8
    journal titleJournal of Atmospheric and Oceanic Technology
    identifier doi10.1175/JTECH-D-11-00179.1
    journal fristpage1062
    journal lastpage1074
    treeJournal of Atmospheric and Oceanic Technology:;2012:;volume( 029 ):;issue: 008
    contenttypeFulltext
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