Model for Multiple Imputation to Estimate Daily Rainfall Data and Filling of Faults

Detalhes bibliográficos
Autor(a) principal: de Carvalho,José Ruy Porto
Data de Publicação: 2017
Outros Autores: Almeida Monteiro,José Eduardo Boffinho, Nakai,Alan Massaru, Assad,Eduardo Delgado
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=S0102-77862017000400575
Resumo: Abstract Modeling by multiple enchained imputation is an area of growing importance. However, its models and methods are frequently developed for specific applications. In this study the model for multiple imputation was used to estimate daily rainfall data. Daily precipitation records from several meteorological stations were used, obtained from system AGRITEMPO for two homogenous climatic zones. The precipitation values obtained for two dates (Jan. 20th 2005 and May 2nd 2005) using the multiple imputation model were compared with geo-statistics techniques ordinary Kriging and Co-kriging with the altitude as an auxiliary variable. The multiple imputation model was 16% better for the first zone and over 23% for the second one, compared to the rainfall estimation obtained by geo-statistical techniques. The model proved to be a versatile technique, presenting coherent results with the conditions of different zones and times.
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spelling Model for Multiple Imputation to Estimate Daily Rainfall Data and Filling of Faultsmodel by multiple imputationchainsprecipitationordinary krigingordinary Co-kriginghomogeneous zonesAbstract Modeling by multiple enchained imputation is an area of growing importance. However, its models and methods are frequently developed for specific applications. In this study the model for multiple imputation was used to estimate daily rainfall data. Daily precipitation records from several meteorological stations were used, obtained from system AGRITEMPO for two homogenous climatic zones. The precipitation values obtained for two dates (Jan. 20th 2005 and May 2nd 2005) using the multiple imputation model were compared with geo-statistics techniques ordinary Kriging and Co-kriging with the altitude as an auxiliary variable. The multiple imputation model was 16% better for the first zone and over 23% for the second one, compared to the rainfall estimation obtained by geo-statistical techniques. The model proved to be a versatile technique, presenting coherent results with the conditions of different zones and times.Sociedade Brasileira de Meteorologia2017-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862017000400575Revista Brasileira de Meteorologia v.32 n.4 2017reponame:Revista Brasileira de Meteorologia (Online)instname:Sociedade Brasileira de Meteorologia (SBMET)instacron:SBMET10.1590/0102-7786324006info:eu-repo/semantics/openAccessde Carvalho,José Ruy PortoAlmeida Monteiro,José Eduardo BoffinhoNakai,Alan MassaruAssad,Eduardo Delgadoeng2019-05-27T00:00:00Zoai:scielo:S0102-77862017000400575Revistahttp://www.rbmet.org.br/port/index.phpONGhttps://old.scielo.br/oai/scielo-oai.php||rbmet@rbmet.org.br1982-43510102-7786opendoar:2019-05-27T00:00Revista Brasileira de Meteorologia (Online) - Sociedade Brasileira de Meteorologia (SBMET)false
dc.title.none.fl_str_mv Model for Multiple Imputation to Estimate Daily Rainfall Data and Filling of Faults
title Model for Multiple Imputation to Estimate Daily Rainfall Data and Filling of Faults
spellingShingle Model for Multiple Imputation to Estimate Daily Rainfall Data and Filling of Faults
de Carvalho,José Ruy Porto
model by multiple imputation
chains
precipitation
ordinary kriging
ordinary Co-kriging
homogeneous zones
title_short Model for Multiple Imputation to Estimate Daily Rainfall Data and Filling of Faults
title_full Model for Multiple Imputation to Estimate Daily Rainfall Data and Filling of Faults
title_fullStr Model for Multiple Imputation to Estimate Daily Rainfall Data and Filling of Faults
title_full_unstemmed Model for Multiple Imputation to Estimate Daily Rainfall Data and Filling of Faults
title_sort Model for Multiple Imputation to Estimate Daily Rainfall Data and Filling of Faults
author de Carvalho,José Ruy Porto
author_facet de Carvalho,José Ruy Porto
Almeida Monteiro,José Eduardo Boffinho
Nakai,Alan Massaru
Assad,Eduardo Delgado
author_role author
author2 Almeida Monteiro,José Eduardo Boffinho
Nakai,Alan Massaru
Assad,Eduardo Delgado
author2_role author
author
author
dc.contributor.author.fl_str_mv de Carvalho,José Ruy Porto
Almeida Monteiro,José Eduardo Boffinho
Nakai,Alan Massaru
Assad,Eduardo Delgado
dc.subject.por.fl_str_mv model by multiple imputation
chains
precipitation
ordinary kriging
ordinary Co-kriging
homogeneous zones
topic model by multiple imputation
chains
precipitation
ordinary kriging
ordinary Co-kriging
homogeneous zones
description Abstract Modeling by multiple enchained imputation is an area of growing importance. However, its models and methods are frequently developed for specific applications. In this study the model for multiple imputation was used to estimate daily rainfall data. Daily precipitation records from several meteorological stations were used, obtained from system AGRITEMPO for two homogenous climatic zones. The precipitation values obtained for two dates (Jan. 20th 2005 and May 2nd 2005) using the multiple imputation model were compared with geo-statistics techniques ordinary Kriging and Co-kriging with the altitude as an auxiliary variable. The multiple imputation model was 16% better for the first zone and over 23% for the second one, compared to the rainfall estimation obtained by geo-statistical techniques. The model proved to be a versatile technique, presenting coherent results with the conditions of different zones and times.
publishDate 2017
dc.date.none.fl_str_mv 2017-12-01
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=S0102-77862017000400575
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862017000400575
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0102-7786324006
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.32 n.4 2017
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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