Spatio-Temporal Modeling of Data Imputation for Daily Rainfall Series in Homogeneous Zones

Detalhes bibliográficos
Autor(a) principal: Carvalho,José Ruy Porto De
Data de Publicação: 2016
Outros Autores: Nakai,Alan Massaru, Monteiro,José Eduardo B.A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Brasileira de Meteorologia (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862016000200196
Resumo: Abstract Spatio-temporal modelling is an area of increasing importance in which models and methods have often been developed to deal with specific applications. In this study, a spatio-temporal model was used to estimate daily rainfall data. Rainfall records from several weather stations, obtained from the Agritempo system for two climatic homogeneous zones, were used. Rainfall values obtained for two fixed dates (January 1 and May 1, 2012) using the spatio-temporal model were compared with the geostatisticals techniques of ordinary kriging and ordinary cokriging with altitude as auxiliary variable. The spatio-temporal model was more than 17% better at producing estimates of daily precipitation compared to kriging and cokriging in the first zone and more than 18% in the second zone. The spatio-temporal model proved to be a versatile technique, adapting to different seasons and dates.
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spelling Spatio-Temporal Modeling of Data Imputation for Daily Rainfall Series in Homogeneous Zonesspatio-temporal modelrainfall dataordinary krigingordinary cokriginghomogeneous zonesAbstract Spatio-temporal modelling is an area of increasing importance in which models and methods have often been developed to deal with specific applications. In this study, a spatio-temporal model was used to estimate daily rainfall data. Rainfall records from several weather stations, obtained from the Agritempo system for two climatic homogeneous zones, were used. Rainfall values obtained for two fixed dates (January 1 and May 1, 2012) using the spatio-temporal model were compared with the geostatisticals techniques of ordinary kriging and ordinary cokriging with altitude as auxiliary variable. The spatio-temporal model was more than 17% better at producing estimates of daily precipitation compared to kriging and cokriging in the first zone and more than 18% in the second zone. The spatio-temporal model proved to be a versatile technique, adapting to different seasons and dates.Sociedade Brasileira de Meteorologia2016-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862016000200196Revista Brasileira de Meteorologia v.31 n.2 2016reponame:Revista Brasileira de Meteorologia (Online)instname:Sociedade Brasileira de Meteorologia (SBMET)instacron:SBMET10.1590/0102-778631220150025info:eu-repo/semantics/openAccessCarvalho,José Ruy Porto DeNakai,Alan MassaruMonteiro,José Eduardo B.A.eng2016-06-28T00:00:00Zoai:scielo:S0102-77862016000200196Revistahttp://www.rbmet.org.br/port/index.phpONGhttps://old.scielo.br/oai/scielo-oai.php||rbmet@rbmet.org.br1982-43510102-7786opendoar:2016-06-28T00:00Revista Brasileira de Meteorologia (Online) - Sociedade Brasileira de Meteorologia (SBMET)false
dc.title.none.fl_str_mv Spatio-Temporal Modeling of Data Imputation for Daily Rainfall Series in Homogeneous Zones
title Spatio-Temporal Modeling of Data Imputation for Daily Rainfall Series in Homogeneous Zones
spellingShingle Spatio-Temporal Modeling of Data Imputation for Daily Rainfall Series in Homogeneous Zones
Carvalho,José Ruy Porto De
spatio-temporal model
rainfall data
ordinary kriging
ordinary cokriging
homogeneous zones
title_short Spatio-Temporal Modeling of Data Imputation for Daily Rainfall Series in Homogeneous Zones
title_full Spatio-Temporal Modeling of Data Imputation for Daily Rainfall Series in Homogeneous Zones
title_fullStr Spatio-Temporal Modeling of Data Imputation for Daily Rainfall Series in Homogeneous Zones
title_full_unstemmed Spatio-Temporal Modeling of Data Imputation for Daily Rainfall Series in Homogeneous Zones
title_sort Spatio-Temporal Modeling of Data Imputation for Daily Rainfall Series in Homogeneous Zones
author Carvalho,José Ruy Porto De
author_facet Carvalho,José Ruy Porto De
Nakai,Alan Massaru
Monteiro,José Eduardo B.A.
author_role author
author2 Nakai,Alan Massaru
Monteiro,José Eduardo B.A.
author2_role author
author
dc.contributor.author.fl_str_mv Carvalho,José Ruy Porto De
Nakai,Alan Massaru
Monteiro,José Eduardo B.A.
dc.subject.por.fl_str_mv spatio-temporal model
rainfall data
ordinary kriging
ordinary cokriging
homogeneous zones
topic spatio-temporal model
rainfall data
ordinary kriging
ordinary cokriging
homogeneous zones
description Abstract Spatio-temporal modelling is an area of increasing importance in which models and methods have often been developed to deal with specific applications. In this study, a spatio-temporal model was used to estimate daily rainfall data. Rainfall records from several weather stations, obtained from the Agritempo system for two climatic homogeneous zones, were used. Rainfall values obtained for two fixed dates (January 1 and May 1, 2012) using the spatio-temporal model were compared with the geostatisticals techniques of ordinary kriging and ordinary cokriging with altitude as auxiliary variable. The spatio-temporal model was more than 17% better at producing estimates of daily precipitation compared to kriging and cokriging in the first zone and more than 18% in the second zone. The spatio-temporal model proved to be a versatile technique, adapting to different seasons and dates.
publishDate 2016
dc.date.none.fl_str_mv 2016-06-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862016000200196
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862016000200196
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0102-778631220150025
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Meteorologia
publisher.none.fl_str_mv Sociedade Brasileira de Meteorologia
dc.source.none.fl_str_mv Revista Brasileira de Meteorologia v.31 n.2 2016
reponame:Revista Brasileira de Meteorologia (Online)
instname:Sociedade Brasileira de Meteorologia (SBMET)
instacron:SBMET
instname_str Sociedade Brasileira de Meteorologia (SBMET)
instacron_str SBMET
institution SBMET
reponame_str Revista Brasileira de Meteorologia (Online)
collection Revista Brasileira de Meteorologia (Online)
repository.name.fl_str_mv Revista Brasileira de Meteorologia (Online) - Sociedade Brasileira de Meteorologia (SBMET)
repository.mail.fl_str_mv ||rbmet@rbmet.org.br
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