Interpolation of daily rainfall using spatiotemporal models and clustering

Handle URI:
http://hdl.handle.net/10754/594086
Title:
Interpolation of daily rainfall using spatiotemporal models and clustering
Authors:
Militino, A. F.; Ugarte, M. D.; Goicoa, T.; Genton, Marc G. ( 0000-0001-6467-2998 )
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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
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.
Publisher:
Wiley-Blackwell
Journal:
International Journal of Climatology
Issue Date:
11-Jun-2014
DOI:
10.1002/joc.4068
Type:
Article
ISSN:
0899-8418
Sponsors:
Spanish Ministry of Science and Education
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorMilitino, A. F.en
dc.contributor.authorUgarte, M. D.en
dc.contributor.authorGoicoa, T.en
dc.contributor.authorGenton, Marc G.en
dc.date.accessioned2016-01-19T13:21:16Zen
dc.date.available2016-01-19T13:21:16Zen
dc.date.issued2014-06-11en
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.en
dc.identifier.issn0899-8418en
dc.identifier.doi10.1002/joc.4068en
dc.identifier.urihttp://hdl.handle.net/10754/594086en
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.en
dc.description.sponsorshipSpanish Ministry of Science and Educationen
dc.publisherWiley-Blackwellen
dc.subjectKrigingen
dc.subjectState-space modelsen
dc.subjectStatistical modelsen
dc.subjectThin-plate splinesen
dc.titleInterpolation of daily rainfall using spatiotemporal models and clusteringen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalInternational Journal of Climatologyen
dc.contributor.institutionDepartment of Statistics and Operations Research; Public University of Navarre; Pamplona Spainen
kaust.authorGenton, Marc G.en
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.