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    A Dynamically Consistent Reconstruction of Ocean Temperature

    Source: Journal of Atmospheric and Oceanic Technology:;2017:;volume( 034 ):;issue: 005::page 1061
    Author:
    Shen, Samuel S. P.
    ,
    Behm, Gregory P.
    ,
    Song, Y. Tony
    ,
    Qu, Tangdong
    DOI: 10.1175/JTECH-D-16-0133.1
    Publisher: American Meteorological Society
    Abstract: his paper provides a spectral optimal gridding (SOG) method to make a dynamically consistent reconstruction of water temperature for the global ocean at different depth levels. The dynamical consistency is achieved by using the basis of empirical orthogonal functions (EOFs) derived from NASA Jet Propulsion Laboratory (JPL) non-Boussinesq ocean general circulation model (OGCM) output at ¼° resolution from 1958 to 2013. A convenient singular value decomposition (SVD) method is used to calculate the EOFs, in order to enable efficient computing for a fine spatial grid globally. These EOFs are used as explainable variables and are regressed against the sparsely distributed in situ ocean temperature data at 33 standard depth levels. The observed data are aggregated onto a 1° latitude?longitude grid at each level from the surface to the 5500-m layer for the period 1950?2014. Three representative temperature reconstruction examples are presented and validated: two 10-m-layer (i.e., the second layer from the surface) reconstructions for January 2008 and January 1998, which are compared with independent sea surface temperature (SST) observations; and one 100-m-layer reconstruction for January 1998, which shows a strong cold anomaly El Niño signal in the western tropical Pacific up to ?5°C from 150°E to 140°W. The SOG reconstruction can accurately locate the El Niño signal region in different ocean layers. The SOG reconstruction method is shown reliable and yields satisfactory accuracy even with sparse data. Validation and error analysis indicate that no systematic biases exist in the observed and reconstructed data.
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      A Dynamically Consistent Reconstruction of Ocean Temperature

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4228752
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    contributor authorShen, Samuel S. P.
    contributor authorBehm, Gregory P.
    contributor authorSong, Y. Tony
    contributor authorQu, Tangdong
    date accessioned2017-06-09T17:26:27Z
    date available2017-06-09T17:26:27Z
    date copyright2017/05/01
    date issued2017
    identifier issn0739-0572
    identifier otherams-85318.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4228752
    description abstracthis paper provides a spectral optimal gridding (SOG) method to make a dynamically consistent reconstruction of water temperature for the global ocean at different depth levels. The dynamical consistency is achieved by using the basis of empirical orthogonal functions (EOFs) derived from NASA Jet Propulsion Laboratory (JPL) non-Boussinesq ocean general circulation model (OGCM) output at ¼° resolution from 1958 to 2013. A convenient singular value decomposition (SVD) method is used to calculate the EOFs, in order to enable efficient computing for a fine spatial grid globally. These EOFs are used as explainable variables and are regressed against the sparsely distributed in situ ocean temperature data at 33 standard depth levels. The observed data are aggregated onto a 1° latitude?longitude grid at each level from the surface to the 5500-m layer for the period 1950?2014. Three representative temperature reconstruction examples are presented and validated: two 10-m-layer (i.e., the second layer from the surface) reconstructions for January 2008 and January 1998, which are compared with independent sea surface temperature (SST) observations; and one 100-m-layer reconstruction for January 1998, which shows a strong cold anomaly El Niño signal in the western tropical Pacific up to ?5°C from 150°E to 140°W. The SOG reconstruction can accurately locate the El Niño signal region in different ocean layers. The SOG reconstruction method is shown reliable and yields satisfactory accuracy even with sparse data. Validation and error analysis indicate that no systematic biases exist in the observed and reconstructed data.
    publisherAmerican Meteorological Society
    titleA Dynamically Consistent Reconstruction of Ocean Temperature
    typeJournal Paper
    journal volume34
    journal issue5
    journal titleJournal of Atmospheric and Oceanic Technology
    identifier doi10.1175/JTECH-D-16-0133.1
    journal fristpage1061
    journal lastpage1082
    treeJournal of Atmospheric and Oceanic Technology:;2017:;volume( 034 ):;issue: 005
    contenttypeFulltext
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    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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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