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dc.contributor.authorSun, Ying
dc.contributor.authorBowman, Kenneth P.
dc.contributor.authorGenton, Marc G.
dc.contributor.authorTokay, Ali
dc.date.accessioned2015-05-06T13:33:10Z
dc.date.available2015-05-06T13:33:10Z
dc.date.issued2014-07-15
dc.identifier.citationA Matérn model of the spatial covariance structure of point rain rates 2014, 29 (2):411 Stochastic Environmental Research and Risk Assessment
dc.identifier.issn1436-3240
dc.identifier.issn1436-3259
dc.identifier.doi10.1007/s00477-014-0923-2
dc.identifier.urihttp://hdl.handle.net/10754/552393
dc.description.abstractIt is challenging to model a precipitation field due to its intermittent and highly scale-dependent nature. Many models of point rain rates or areal rainfall observations have been proposed and studied for different time scales. Among them, the spectral model based on a stochastic dynamical equation for the instantaneous point rain rate field is attractive, since it naturally leads to a consistent space–time model. In this paper, we note that the spatial covariance structure of the spectral model is equivalent to the well-known Matérn covariance model. Using high-quality rain gauge data, we estimate the parameters of the Matérn model for different time scales and demonstrate that the Matérn model is superior to an exponential model, particularly at short time scales.
dc.publisherSpringer Nature
dc.relation.urlhttp://link.springer.com/10.1007/s00477-014-0923-2
dc.rightsArchived with thanks to Stochastic Environmental Research and Risk Assessment.The final publication is available at Springer via http://dx.doi.org/10.1007/s00477-014-0923-2
dc.subjectCovariance model
dc.subjectExponential covariance
dc.subjectMatérn covariance
dc.subjectPoint rain rates
dc.subjectSpectral model
dc.subjectTime scales
dc.titleA Matérn model of the spatial covariance structure of point rain rates
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentSpatio-Temporal Statistics and Data Analysis Group
dc.contributor.departmentStatistics Program
dc.identifier.journalStochastic Environmental Research and Risk Assessment
dc.eprint.versionPost-print
dc.contributor.institutionDepartment of Statistics, Ohio State University, Columbus, OH, 43210, USA
dc.contributor.institutionDepartment of Atmospheric Sciences, Texas A&M University, College Station, TX, 77843, USA
dc.contributor.institutionJoint Center for Earth Systems Technology, University of Maryland Baltimore County, Baltimore, MD, 21228, USA
dc.contributor.institutionNASA Goddard Space Flight Center, Greenbelt, MD, 20771, USA
kaust.personGenton, Marc G.
refterms.dateFOA2015-07-15T00:00:00Z
dc.date.published-online2014-07-15
dc.date.published-print2015-02


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