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    An Improved Method for Analyzing Sparse and Irregularly Distributed SST Data on a Regular Grid: The Tropical Pacific Ocean

    Source: Journal of Climate:;1998:;volume( 011 ):;issue: 007::page 1717
    Author:
    Smith, Thomas M.
    ,
    Livezey, Robert E.
    ,
    Shen, Samuel S.
    DOI: 10.1175/1520-0442(1998)011<1717:AIMFAS>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: An improved method for interpolating sparsely sampled climatological data onto a regular grid is shown. The method uses the spatial and temporal covariance of the field, along with the sparse data, to fill the full grid. This improves on similar methods that have recently been developed by eliminating the development of features that are not sufficiently supported by the data (i.e., overfitting). Statistical tests are used to tune the method to represent as much variability as the spatial?temporal information will support without overfitting. The method is further improved by a data-checking procedure that detects and removes suspect data. The method is developed and evaluated by interpolating tropical Pacific sea surface temperature (SST) monthly anomalies to a regular grid for the 1856?1995 period. Ship data averaged to 5° squares are used as input and are interpolated to a complete 1° grid. Comparing the results to interpolations using other methods shows this method?s quantitative improvements where satellite data are available for validation. Comparisons in the presatellite era show sharper and stronger anomaly patterns with this method, compared to another method developed for use with sparse data. Also shown are several periods when data are so sparse that only very weak SST anomalies may be reliably reconstructed in the tropical Pacific (i.e., before 1870 and 1915?25). In future research, the global SST and possibly other climatological fields will be gridded using improved methods.
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      An Improved Method for Analyzing Sparse and Irregularly Distributed SST Data on a Regular Grid: The Tropical Pacific Ocean

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4189624
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    contributor authorSmith, Thomas M.
    contributor authorLivezey, Robert E.
    contributor authorShen, Samuel S.
    date accessioned2017-06-09T15:39:53Z
    date available2017-06-09T15:39:53Z
    date copyright1998/07/01
    date issued1998
    identifier issn0894-8755
    identifier otherams-5010.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4189624
    description abstractAn improved method for interpolating sparsely sampled climatological data onto a regular grid is shown. The method uses the spatial and temporal covariance of the field, along with the sparse data, to fill the full grid. This improves on similar methods that have recently been developed by eliminating the development of features that are not sufficiently supported by the data (i.e., overfitting). Statistical tests are used to tune the method to represent as much variability as the spatial?temporal information will support without overfitting. The method is further improved by a data-checking procedure that detects and removes suspect data. The method is developed and evaluated by interpolating tropical Pacific sea surface temperature (SST) monthly anomalies to a regular grid for the 1856?1995 period. Ship data averaged to 5° squares are used as input and are interpolated to a complete 1° grid. Comparing the results to interpolations using other methods shows this method?s quantitative improvements where satellite data are available for validation. Comparisons in the presatellite era show sharper and stronger anomaly patterns with this method, compared to another method developed for use with sparse data. Also shown are several periods when data are so sparse that only very weak SST anomalies may be reliably reconstructed in the tropical Pacific (i.e., before 1870 and 1915?25). In future research, the global SST and possibly other climatological fields will be gridded using improved methods.
    publisherAmerican Meteorological Society
    titleAn Improved Method for Analyzing Sparse and Irregularly Distributed SST Data on a Regular Grid: The Tropical Pacific Ocean
    typeJournal Paper
    journal volume11
    journal issue7
    journal titleJournal of Climate
    identifier doi10.1175/1520-0442(1998)011<1717:AIMFAS>2.0.CO;2
    journal fristpage1717
    journal lastpage1729
    treeJournal of Climate:;1998:;volume( 011 ):;issue: 007
    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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