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    Interpolation of daily rainfall using spatiotemporal models and clustering

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    Type
    Article
    Authors
    Militino, A. F.
    Ugarte, M. D.
    Goicoa, T.
    Genton, Marc G. cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Statistics Program
    Date
    2014-06-11
    Online Publication Date
    2014-06-11
    Print Publication Date
    2015-06-15
    Permanent link to this record
    http://hdl.handle.net/10754/594086
    
    Metadata
    Show full item record
    Abstract
    Accumulated daily rainfall in non-observed locations on a particular day is frequently required as input to decision-making tools in precision agriculture or for hydrological or meteorological studies. Various solutions and estimation procedures have been proposed in the literature depending on the auxiliary information and the availability of data, but most such solutions are oriented to interpolating spatial data without incorporating temporal dependence. When data are available in space and time, spatiotemporal models usually provide better solutions. Here, we analyse the performance of three spatiotemporal models fitted to the whole sampled set and to clusters within the sampled set. The data consists of daily observations collected from 87 manual rainfall gauges from 1990 to 2010 in Navarre, Spain. The accuracy and precision of the interpolated data are compared with real data from 33 automated rainfall gauges in the same region, but placed in different locations than the manual rainfall gauges. Root mean squared error by months and by year are also provided. To illustrate these models, we also map interpolated daily precipitations and standard errors on a 1km2 grid in the whole region. © 2014 Royal Meteorological Society.
    Citation
    Militino AF, Ugarte MD, Goicoa T, Genton M (2014) Interpolation of daily rainfall using spatiotemporal models and clustering. Int J Climatol 35: 1453–1464. Available: http://dx.doi.org/10.1002/joc.4068.
    Sponsors
    Spanish Ministry of Science and Education
    Publisher
    Wiley
    Journal
    International Journal of Climatology
    DOI
    10.1002/joc.4068
    ae974a485f413a2113503eed53cd6c53
    10.1002/joc.4068
    Scopus Count
    Collections
    Articles; Statistics Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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