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dc.contributor.authorMilitino, A. F.
dc.contributor.authorUgarte, M. D.
dc.contributor.authorGoicoa, T.
dc.contributor.authorGenton, Marc G.
dc.date.accessioned2016-01-19T13:21:16Z
dc.date.available2016-01-19T13:21:16Z
dc.date.issued2014-06-11
dc.identifier.citationMilitino 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.
dc.identifier.issn0899-8418
dc.identifier.doi10.1002/joc.4068
dc.identifier.urihttp://hdl.handle.net/10754/594086
dc.description.abstractAccumulated 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.
dc.description.sponsorshipSpanish Ministry of Science and Education
dc.publisherWiley-Blackwell
dc.subjectKriging
dc.subjectState-space models
dc.subjectStatistical models
dc.subjectThin-plate splines
dc.titleInterpolation of daily rainfall using spatiotemporal models and clustering
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalInternational Journal of Climatology
dc.contributor.institutionDepartment of Statistics and Operations Research; Public University of Navarre; Pamplona Spain
kaust.personGenton, Marc G.


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