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    Spatial–Temporal Analysis of Temperature Using Smoothing Spline ANOVA

    Source: Journal of Climate:;1998:;volume( 011 ):;issue: 001::page 18
    Author:
    Luo, Zhen
    ,
    Wahba, Grace
    ,
    Johnson, Donald R.
    DOI: 10.1175/1520-0442(1998)011<0018:STAOTU>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: A new method, smoothing spline ANOVA, for combining station records of surface air temperature to get the estimates of regional averages as well as gridpoint values is proposed. This method is closely related to the optimal interpolation (also optimal averaging) method. It may be viewed as a generalization of these methods from spatial interpolation methods to a method interpolating in both spatial and temporal directions. The connection of this method to the commonly used anomaly approach is discussed in the context of correcting biases resulting from incomplete sampling. A main strength of this new method is its ability to borrow information across both space and time just like optimal interpolation does across space. This increases not only the accuracy of estimates but also the ability to correct various biases resulting from incomplete sampling. Some of these biases are ignored by the anomaly approach.
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      Spatial–Temporal Analysis of Temperature Using Smoothing Spline ANOVA

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4188456
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    contributor authorLuo, Zhen
    contributor authorWahba, Grace
    contributor authorJohnson, Donald R.
    date accessioned2017-06-09T15:37:40Z
    date available2017-06-09T15:37:40Z
    date copyright1998/01/01
    date issued1998
    identifier issn0894-8755
    identifier otherams-4905.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4188456
    description abstractA new method, smoothing spline ANOVA, for combining station records of surface air temperature to get the estimates of regional averages as well as gridpoint values is proposed. This method is closely related to the optimal interpolation (also optimal averaging) method. It may be viewed as a generalization of these methods from spatial interpolation methods to a method interpolating in both spatial and temporal directions. The connection of this method to the commonly used anomaly approach is discussed in the context of correcting biases resulting from incomplete sampling. A main strength of this new method is its ability to borrow information across both space and time just like optimal interpolation does across space. This increases not only the accuracy of estimates but also the ability to correct various biases resulting from incomplete sampling. Some of these biases are ignored by the anomaly approach.
    publisherAmerican Meteorological Society
    titleSpatial–Temporal Analysis of Temperature Using Smoothing Spline ANOVA
    typeJournal Paper
    journal volume11
    journal issue1
    journal titleJournal of Climate
    identifier doi10.1175/1520-0442(1998)011<0018:STAOTU>2.0.CO;2
    journal fristpage18
    journal lastpage28
    treeJournal of Climate:;1998:;volume( 011 ):;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