Modelando precipitação extrema no Brasil pela teoria dos valores extremos
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Tipo de documento: | Tese |
Idioma: | por |
Título da fonte: | Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) |
Texto Completo: | http://repositorio.uem.br:8080/jspui/handle/1/4363 |
Resumo: | : The accurate modeling of extreme events is growing in relevance, particularly in the environmental sciences in which such events can be seen as a result of climate change. In particular, measuring rainfall risk is also important for the design of hydraulic structures (dams, levees, drainage systems, bridges, etc.) and for flood mapping and zoning. The Brazilian regulatory agency, Agência Nacional de Águas (ANA), makes available rainfall series for 11,368 rain stations throughout Brazil, some of them dating from the 19th century. One of our goals was to produce, using the framework of extreme value theory, maps with reliable estimates of the 25-year return level of a extreme rainfall for each locality covered by ANA. Such dataset present many complex challenges: first, evaluating its quality; then, modeling spatial extremes over large random fields; modeling temporal nonstationarity of the extreme rainfall process due to natural climate seasonality and due to a possible trend owing to climate change; correcting biases resulting from misspecification of the model or from a small sample. In this study, we tackle all these issues. We perform a detailed quality control, and we make a deep discussion of biases resulting either from misspecification of the model or from a small sample, while providing important information regarding the modeling of rainfall extremes, and complementing recent previous studies. In particular, the shape parameter of the extreme-value model seems to have a mean asymptotic value of 0.06. |
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Modelando precipitação extrema no Brasil pela teoria dos valores extremosModeling daily rainfall in Brazil with extreme value theoryTeoria estatística bayesianaDecisões estatísticasModelo hierárquico bayesianaPrecipitação pluviométricaAnáliseAnálise estatísticaBrasil.Bayesian hierarchical modelPenultimate biasPrecipitation fieldReturn level mapSmall sample biasBrazil.Ciências Exatas e da TerraEstatística: The accurate modeling of extreme events is growing in relevance, particularly in the environmental sciences in which such events can be seen as a result of climate change. In particular, measuring rainfall risk is also important for the design of hydraulic structures (dams, levees, drainage systems, bridges, etc.) and for flood mapping and zoning. The Brazilian regulatory agency, Agência Nacional de Águas (ANA), makes available rainfall series for 11,368 rain stations throughout Brazil, some of them dating from the 19th century. One of our goals was to produce, using the framework of extreme value theory, maps with reliable estimates of the 25-year return level of a extreme rainfall for each locality covered by ANA. Such dataset present many complex challenges: first, evaluating its quality; then, modeling spatial extremes over large random fields; modeling temporal nonstationarity of the extreme rainfall process due to natural climate seasonality and due to a possible trend owing to climate change; correcting biases resulting from misspecification of the model or from a small sample. In this study, we tackle all these issues. We perform a detailed quality control, and we make a deep discussion of biases resulting either from misspecification of the model or from a small sample, while providing important information regarding the modeling of rainfall extremes, and complementing recent previous studies. In particular, the shape parameter of the extreme-value model seems to have a mean asymptotic value of 0.06.69 fUniversidade Estadual de MaringáBrasilDepartamento de EstatísticaPrograma de Pós-Graduação em BioestatísticaUEMMaringá, PRCentro de Ciências ExatasIsolde Terezinha Santos PrevidelliSilvia Lopes de Paula Ferrari - USPEniuce Menezes de Souza - UEMPereira, Paulo Vitor da Costa2018-04-18T20:15:55Z2018-04-18T20:15:55Z2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesishttp://repositorio.uem.br:8080/jspui/handle/1/4363porinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da Universidade Estadual de Maringá (RI-UEM)instname:Universidade Estadual de Maringá (UEM)instacron:UEM2018-10-10T18:37:02Zoai:localhost:1/4363Repositório InstitucionalPUBhttp://repositorio.uem.br:8080/oai/requestopendoar:2024-04-23T14:57:31.477206Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) - Universidade Estadual de Maringá (UEM)false |
dc.title.none.fl_str_mv |
Modelando precipitação extrema no Brasil pela teoria dos valores extremos Modeling daily rainfall in Brazil with extreme value theory |
title |
Modelando precipitação extrema no Brasil pela teoria dos valores extremos |
spellingShingle |
Modelando precipitação extrema no Brasil pela teoria dos valores extremos Pereira, Paulo Vitor da Costa Teoria estatística bayesiana Decisões estatísticas Modelo hierárquico bayesiana Precipitação pluviométrica Análise Análise estatística Brasil. Bayesian hierarchical model Penultimate bias Precipitation field Return level map Small sample bias Brazil. Ciências Exatas e da Terra Estatística |
title_short |
Modelando precipitação extrema no Brasil pela teoria dos valores extremos |
title_full |
Modelando precipitação extrema no Brasil pela teoria dos valores extremos |
title_fullStr |
Modelando precipitação extrema no Brasil pela teoria dos valores extremos |
title_full_unstemmed |
Modelando precipitação extrema no Brasil pela teoria dos valores extremos |
title_sort |
Modelando precipitação extrema no Brasil pela teoria dos valores extremos |
author |
Pereira, Paulo Vitor da Costa |
author_facet |
Pereira, Paulo Vitor da Costa |
author_role |
author |
dc.contributor.none.fl_str_mv |
Isolde Terezinha Santos Previdelli Silvia Lopes de Paula Ferrari - USP Eniuce Menezes de Souza - UEM |
dc.contributor.author.fl_str_mv |
Pereira, Paulo Vitor da Costa |
dc.subject.por.fl_str_mv |
Teoria estatística bayesiana Decisões estatísticas Modelo hierárquico bayesiana Precipitação pluviométrica Análise Análise estatística Brasil. Bayesian hierarchical model Penultimate bias Precipitation field Return level map Small sample bias Brazil. Ciências Exatas e da Terra Estatística |
topic |
Teoria estatística bayesiana Decisões estatísticas Modelo hierárquico bayesiana Precipitação pluviométrica Análise Análise estatística Brasil. Bayesian hierarchical model Penultimate bias Precipitation field Return level map Small sample bias Brazil. Ciências Exatas e da Terra Estatística |
description |
: The accurate modeling of extreme events is growing in relevance, particularly in the environmental sciences in which such events can be seen as a result of climate change. In particular, measuring rainfall risk is also important for the design of hydraulic structures (dams, levees, drainage systems, bridges, etc.) and for flood mapping and zoning. The Brazilian regulatory agency, Agência Nacional de Águas (ANA), makes available rainfall series for 11,368 rain stations throughout Brazil, some of them dating from the 19th century. One of our goals was to produce, using the framework of extreme value theory, maps with reliable estimates of the 25-year return level of a extreme rainfall for each locality covered by ANA. Such dataset present many complex challenges: first, evaluating its quality; then, modeling spatial extremes over large random fields; modeling temporal nonstationarity of the extreme rainfall process due to natural climate seasonality and due to a possible trend owing to climate change; correcting biases resulting from misspecification of the model or from a small sample. In this study, we tackle all these issues. We perform a detailed quality control, and we make a deep discussion of biases resulting either from misspecification of the model or from a small sample, while providing important information regarding the modeling of rainfall extremes, and complementing recent previous studies. In particular, the shape parameter of the extreme-value model seems to have a mean asymptotic value of 0.06. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016 2018-04-18T20:15:55Z 2018-04-18T20:15:55Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.uem.br:8080/jspui/handle/1/4363 |
url |
http://repositorio.uem.br:8080/jspui/handle/1/4363 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Estadual de Maringá Brasil Departamento de Estatística Programa de Pós-Graduação em Bioestatística UEM Maringá, PR Centro de Ciências Exatas |
publisher.none.fl_str_mv |
Universidade Estadual de Maringá Brasil Departamento de Estatística Programa de Pós-Graduação em Bioestatística UEM Maringá, PR Centro de Ciências Exatas |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) instname:Universidade Estadual de Maringá (UEM) instacron:UEM |
instname_str |
Universidade Estadual de Maringá (UEM) |
instacron_str |
UEM |
institution |
UEM |
reponame_str |
Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) |
collection |
Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) |
repository.name.fl_str_mv |
Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) - Universidade Estadual de Maringá (UEM) |
repository.mail.fl_str_mv |
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1801841417164685312 |