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1. Identificação
Tipo de ReferênciaArtigo em Revista Científica (Journal Article)
Sitemtc-m21c.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34R/43T9N92
Repositóriosid.inpe.br/mtc-m21c/2021/01.05.16.21   (acesso restrito)
Última Atualização2021:01.05.16.21.05 (UTC) administrator
Repositório de Metadadossid.inpe.br/mtc-m21c/2021/01.05.16.21.05
Última Atualização dos Metadados2022:04.03.22.28.01 (UTC) administrator
DOI10.1016/j.atmosres.2020.105221
ISSN0169-8095
Chave de CitaçãoLimaLyAbOlZeCu:2021:ChUsPr
TítuloExtreme rainfall events over Rio de Janeiro State, Brazil: Characterization using probability distribution functions and clustering analysis
Ano2021
MêsJan
Data de Acesso08 maio 2024
Tipo de Trabalhojournal article
Tipo SecundárioPRE PI
Número de Arquivos1
Tamanho19935 KiB
2. Contextualização
Autor1 Lima, Allana Oliveira
2 Lyra, Gustavo Bastos
3 Abreu, Marcel Carvalho
4 Oliveira Júnior, José Francisco
5 Zeri, Marcelo
6 Cunha Zeri, Gisleine
Grupo1
2
3
4
5
6 DIIAV-CGCT-INPE-MCTI-GOV-BR
Afiliação1 Universidade Federal Fluminense (UFF)
2 Universidade Federal Rural do Rio de Janeiro (UFRRJ)
3 Universidade Federal Rural do Rio de Janeiro (UFRRJ)
4 Universidade Federal de Alagoas (UFAL)
5 Centro Nacional de Monitoramento e Alertas de Desastres Naturais (CEMADEN)
6 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor1
2 gblyra@ufrrj.br
3
4
5
6 gisleine.zeri@inpe.br
RevistaAtmospheric Research
Volume247
Páginase105221
Nota SecundáriaA1_INTERDISCIPLINAR A1_CIÊNCIAS_AMBIENTAIS A2_GEOCIÊNCIAS A2_CIÊNCIAS_AGRÁRIAS_I B1_MATEMÁTICA_/_PROBABILIDADE_E_ESTATÍSTICA B1_ENGENHARIAS_IV B1_ENGENHARIAS_III B1_ENGENHARIAS_II B1_BIODIVERSIDADE B2_ASTRONOMIA_/_FÍSICA
Histórico (UTC)2021-01-05 16:21:05 :: simone -> administrator ::
2021-01-05 16:21:07 :: administrator -> simone :: 2021
2021-01-05 16:22:24 :: simone -> administrator :: 2021
2021-06-22 19:11:12 :: administrator -> simone :: 2021
2021-06-22 20:10:10 :: simone -> administrator :: 2021
2022-04-03 22:28:01 :: administrator -> simone :: 2021
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Tipo de Versãopublisher
ResumoExtreme rainfall events are likely to become more frequent according to recent scenarios of climate change. This issue is especially important over regions with complex topography, which enhances rainfall variability when associated with weather patterns. The state of Rio de Janeiro (SRJ), southeastern Brazil, is characterized by altitudes ranging from the mean sea level up to 2500 m.a.s.l, in mountain ranges and valleys covering significant parts of the region. Time series data of annual maximum daily rainfall were obtained from 110 stations with a data coverage of at least 20 years, from 1960 to 2010. The Probability Distribution Functions (PDFs) normal, log-normal, exponential, gamma, Gumbel, Weibull, and Generalized Extreme Value (GEV) were fitted to maximum rainfall series. Goodness-of-fit tests (Chi-squared - χ2 and Anderson-Darling) revealed that the Gumbel, GEV, and log-normal were found to be the best choices. However,the Gumbel and GEV PDFs were the best ranking by the χ2 and Anderson-Darling test, respectively. Extreme rainfall events with different recurrence intervals (5, 10, 25, 50 and 100 years) were calculated based on the Gumbel and GEV Cumulative Distribution Function (CDF). The differences between extreme values from Gumbell and GEV function increased as the shape parameter increases from zero, with higher probability and extreme value. Five regions with homogeneous patterns of extreme rainfall were identified using clustering analysis (Ward's method) and different recurrence intervals. Overall, the regions with higher values of extreme rainfall in all scenarios and CDFs were the ones close to the coast, within 40 km, and south of Serra dos Órgãos mountain range, located in the middle of the state. The mountain range separates the state in two halves, concentrating higher values of extreme rainfall in the lower part, where the city of Rio de Janeiro, the state's capital, is located. Scenarios for both CDF (GEV and Gumbel) indicated daily rainfall events up to 200 mm, with recurrence intervals of 50 to 100 years. In addition, the southernmost part of the state is subjected to rainfall extremes up to 260 mm in scenarios of 50 to 100 years of recurrence interval. This region, and the state's capital, are characterized by complex topography and a high fraction of population living in slums over hills, or lowlands near the ocean, increasing the vulnerability to events such as landslides and floods associated with extreme rainfall.
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4. Condições de acesso e uso
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5. Fontes relacionadas
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Unidades Imediatamente Superiores8JMKD3MGPCW/46KUATE
DivulgaçãoWEBSCI; PORTALCAPES; COMPENDEX; SCOPUS.
Acervo Hospedeirourlib.net/www/2017/11.22.19.04
6. Notas
Campos Vaziosalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn keywords label lineage mark mirrorrepository nextedition notes number orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup resumeid rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject targetfile tertiarytype url
7. Controle da descrição
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