Analysis of Extreme Precipitation Events in the Mountainous Region of Rio de Janeiro, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.3390/cli11030073 http://hdl.handle.net/11449/247056 |
Resumo: | Extreme rainfall events cause diverse loss of life and economic losses. These disasters include flooding, landslides, and erosion. For these intense rainfall events, one can statistically estimate the time when a given rainfall volume will occur. Initially, this work estimated rainfall volumes for the mountainous region of Rio de Janeiro, and the frequency with which rainfall events occur. For this, we analyzed daily precipitation data using the ANOBES method and the Gumbel statistical distribution to estimate return times. Extreme prec’ipitation volumes of up to 240 mm per day were identified in some locations, with 100 years or more return periods. On 11 January 2011 precipitation volumes were high, but on 12 January they were extreme, similar to the 100-year return time data. The analysis method presented enables the determination of the return time of heavy rainfall, assisting in the prevention of its effects. Knowledge of the atmospheric configuration enables decision support. The atmospheric systems that combined to cause the event were local circulations (orographic and sea breeze) and large-scale systems (SACZ and frontal systems). |
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Repositório Institucional da UNESP |
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Analysis of Extreme Precipitation Events in the Mountainous Region of Rio de Janeiro, Brazilextreme precipitation eventsfloodslandslidesrainfallExtreme rainfall events cause diverse loss of life and economic losses. These disasters include flooding, landslides, and erosion. For these intense rainfall events, one can statistically estimate the time when a given rainfall volume will occur. Initially, this work estimated rainfall volumes for the mountainous region of Rio de Janeiro, and the frequency with which rainfall events occur. For this, we analyzed daily precipitation data using the ANOBES method and the Gumbel statistical distribution to estimate return times. Extreme prec’ipitation volumes of up to 240 mm per day were identified in some locations, with 100 years or more return periods. On 11 January 2011 precipitation volumes were high, but on 12 January they were extreme, similar to the 100-year return time data. The analysis method presented enables the determination of the return time of heavy rainfall, assisting in the prevention of its effects. Knowledge of the atmospheric configuration enables decision support. The atmospheric systems that combined to cause the event were local circulations (orographic and sea breeze) and large-scale systems (SACZ and frontal systems).PetrobrasInstituto de Astronômia Geofísica e Ciências Atmosféricas da Universidade de São Paulo Departamento de Ciências AtmosféricaPolytechnic School Universidade de São PauloInstituto de Geociências e Ciências Exatas Universidade Estadual PaulistaInstituto de Geociências e Ciências Exatas Universidade Estadual PaulistaPetrobras: 2014/438-9Universidade de São Paulo (USP)Universidade Estadual Paulista (UNESP)Lopez, Maria del Carmen SanzPinaya, Jorge Luiz DiazPereira Filho, Augusto JoséVemado, Fe-LipeReis, Fábio Augusto Gomes Vieira [UNESP]2023-07-29T12:57:51Z2023-07-29T12:57:51Z2023-03-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.3390/cli11030073Climate, v. 11, n. 3, 2023.2225-1154http://hdl.handle.net/11449/24705610.3390/cli110300732-s2.0-85150985100Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengClimateinfo:eu-repo/semantics/openAccess2023-07-29T12:57:51Zoai:repositorio.unesp.br:11449/247056Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T18:27:47.000270Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Analysis of Extreme Precipitation Events in the Mountainous Region of Rio de Janeiro, Brazil |
title |
Analysis of Extreme Precipitation Events in the Mountainous Region of Rio de Janeiro, Brazil |
spellingShingle |
Analysis of Extreme Precipitation Events in the Mountainous Region of Rio de Janeiro, Brazil Lopez, Maria del Carmen Sanz extreme precipitation events floods landslides rainfall |
title_short |
Analysis of Extreme Precipitation Events in the Mountainous Region of Rio de Janeiro, Brazil |
title_full |
Analysis of Extreme Precipitation Events in the Mountainous Region of Rio de Janeiro, Brazil |
title_fullStr |
Analysis of Extreme Precipitation Events in the Mountainous Region of Rio de Janeiro, Brazil |
title_full_unstemmed |
Analysis of Extreme Precipitation Events in the Mountainous Region of Rio de Janeiro, Brazil |
title_sort |
Analysis of Extreme Precipitation Events in the Mountainous Region of Rio de Janeiro, Brazil |
author |
Lopez, Maria del Carmen Sanz |
author_facet |
Lopez, Maria del Carmen Sanz Pinaya, Jorge Luiz Diaz Pereira Filho, Augusto José Vemado, Fe-Lipe Reis, Fábio Augusto Gomes Vieira [UNESP] |
author_role |
author |
author2 |
Pinaya, Jorge Luiz Diaz Pereira Filho, Augusto José Vemado, Fe-Lipe Reis, Fábio Augusto Gomes Vieira [UNESP] |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade de São Paulo (USP) Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Lopez, Maria del Carmen Sanz Pinaya, Jorge Luiz Diaz Pereira Filho, Augusto José Vemado, Fe-Lipe Reis, Fábio Augusto Gomes Vieira [UNESP] |
dc.subject.por.fl_str_mv |
extreme precipitation events floods landslides rainfall |
topic |
extreme precipitation events floods landslides rainfall |
description |
Extreme rainfall events cause diverse loss of life and economic losses. These disasters include flooding, landslides, and erosion. For these intense rainfall events, one can statistically estimate the time when a given rainfall volume will occur. Initially, this work estimated rainfall volumes for the mountainous region of Rio de Janeiro, and the frequency with which rainfall events occur. For this, we analyzed daily precipitation data using the ANOBES method and the Gumbel statistical distribution to estimate return times. Extreme prec’ipitation volumes of up to 240 mm per day were identified in some locations, with 100 years or more return periods. On 11 January 2011 precipitation volumes were high, but on 12 January they were extreme, similar to the 100-year return time data. The analysis method presented enables the determination of the return time of heavy rainfall, assisting in the prevention of its effects. Knowledge of the atmospheric configuration enables decision support. The atmospheric systems that combined to cause the event were local circulations (orographic and sea breeze) and large-scale systems (SACZ and frontal systems). |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-07-29T12:57:51Z 2023-07-29T12:57:51Z 2023-03-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.3390/cli11030073 Climate, v. 11, n. 3, 2023. 2225-1154 http://hdl.handle.net/11449/247056 10.3390/cli11030073 2-s2.0-85150985100 |
url |
http://dx.doi.org/10.3390/cli11030073 http://hdl.handle.net/11449/247056 |
identifier_str_mv |
Climate, v. 11, n. 3, 2023. 2225-1154 10.3390/cli11030073 2-s2.0-85150985100 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Climate |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128935519584256 |