A Matérn model of the spatial covariance structure of point rain rates

Handle URI:
http://hdl.handle.net/10754/552393
Title:
A Matérn model of the spatial covariance structure of point rain rates
Authors:
Sun, Ying ( 0000-0001-6703-4270 ) ; Bowman, Kenneth P.; Genton, Marc G. ( 0000-0001-6467-2998 ) ; Tokay, Ali
Abstract:
It 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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
A Matérn model of the spatial covariance structure of point rain rates 2014, 29 (2):411 Stochastic Environmental Research and Risk Assessment
Journal:
Stochastic Environmental Research and Risk Assessment
Issue Date:
15-Jul-2014
DOI:
10.1007/s00477-014-0923-2
Type:
Article
ISSN:
1436-3240; 1436-3259
Additional Links:
http://link.springer.com/10.1007/s00477-014-0923-2
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorSun, Yingen
dc.contributor.authorBowman, Kenneth P.en
dc.contributor.authorGenton, Marc G.en
dc.contributor.authorTokay, Alien
dc.date.accessioned2015-05-06T13:33:10Zen
dc.date.available2015-05-06T13:33:10Zen
dc.date.issued2014-07-15en
dc.identifier.citationA Matérn model of the spatial covariance structure of point rain rates 2014, 29 (2):411 Stochastic Environmental Research and Risk Assessmenten
dc.identifier.issn1436-3240en
dc.identifier.issn1436-3259en
dc.identifier.doi10.1007/s00477-014-0923-2en
dc.identifier.urihttp://hdl.handle.net/10754/552393en
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.en
dc.relation.urlhttp://link.springer.com/10.1007/s00477-014-0923-2en
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/s00477-014-0923-2en
dc.subjectCovariance modelen
dc.subjectExponential covarianceen
dc.subjectMatérn covarianceen
dc.subjectPoint rain ratesen
dc.subjectSpectral modelen
dc.subjectTime scalesen
dc.titleA Matérn model of the spatial covariance structure of point rain ratesen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalStochastic Environmental Research and Risk Assessmenten
dc.eprint.versionPost-printen
dc.contributor.institutionDepartment of Statistics, Ohio State University, Columbus, OH, 43210, USAen
dc.contributor.institutionDepartment of Atmospheric Sciences, Texas A&M University, College Station, TX, 77843, USAen
dc.contributor.institutionJoint Center for Earth Systems Technology, University of Maryland Baltimore County, Baltimore, MD, 21228, USAen
dc.contributor.institutionNASA Goddard Space Flight Center, Greenbelt, MD, 20771, USAen
kaust.authorGenton, Marc G.en
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