Fechar
Metadados

1. Identificação
Tipo de ReferênciaArtigo em Revista Científica (Journal Article)
Sitemtc-m21d.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34T/48AP4UB
Repositóriosid.inpe.br/mtc-m21d/2023/01.04.12.51   (acesso restrito)
Última Atualização2023:01.04.12.51.45 (UTC) simone
Repositório de Metadadossid.inpe.br/mtc-m21d/2023/01.04.12.51.45
Última Atualização dos Metadados2023:01.08.09.48.24 (UTC) administrator
DOI10.1002/joc.7782
ISSN0899-8418
Chave de CitaçãoBregaPaivChouColl:2022:HyPeSo
TítuloAssessing extreme precipitation from a regional climate model in different spatial-temporal scales: A hydrological perspective in South America
Ano2022
MêsDec.
Data de Acesso18 maio 2024
Tipo de Trabalhojournal article
Tipo SecundárioPRE PI
Número de Arquivos1
Tamanho8375 KiB
2. Contextualização
Autor1 Brega, João Paulo Lyra Fialho
2 Paiva, Rodrigo Cauduro Dias de
3 Chou, Sin Chan
4 Collischonn, Walter
ORCID1 0000-0002-8360-1308
2 0000-0003-2918-6681
3 0000-0002-8973-1808
4 0000-0002-8973-1808
Grupo1
2
3 DIMNT-CGCT-INPE-MCTI-GOV-BR
Afiliação1 Universidade Federal do Rio Grande do Sul (UFRGS)
2 Universidade Federal do Rio Grande do Sul (UFRGS)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Universidade Federal do Rio Grande do Sul (UFRGS)
Endereço de e-Mail do Autor1 joaopaulolfb@gmail.com
2
3 chou.chan@inpe.br
RevistaInternational Journal of Climatology
Volume42
Número16
Páginas8904-8927
Nota SecundáriaA1_GEOCIÊNCIAS A1_ENGENHARIAS_I A1_CIÊNCIAS_AMBIENTAIS A1_CIÊNCIAS_AGRÁRIAS_I A2_INTERDISCIPLINAR A2_BIODIVERSIDADE B1_CIÊNCIAS_BIOLÓGICAS_I
Histórico (UTC)2023-01-04 12:51:45 :: simone -> administrator ::
2023-01-04 12:51:46 :: administrator -> simone :: 2022
2023-01-04 12:52:24 :: simone -> administrator :: 2022
2023-01-08 09:48:24 :: administrator -> simone :: 2022
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Tipo de Versãopublisher
Palavras-Chavecross-scale assessment
Eta
hydrological impact studies
IDF curves
MGB
streamflow
ResumoGlobal and regional climate models (GCM and RCM respectively) are the current mathematical tools used to project alterations on precipitation regimes given different greenhouse gases emissions scenarios. However, these models have specific resolutions, physical equations and numerical approaches that provide a diverse set of performances across different regions and spatial-temporal scales. In South America, most hydrological impact studies have used the Eta RCM to yield precipitation projections without a proper uncertainty analysis. It is important to acknowledge its uncertainties prior to any hydrological assessment to adequately support climate change investigations and related water decision making. Therefore, we aim to investigate how Eta extreme precipitation biases vary in different spatial-temporal scales from a hydrological perspective. Thus, we evaluate the extreme precipitation generated by the Eta RCM driven by four different GCMs. It is investigated Eta biases across different temporal (3 hr-5 days) and spatial scales (0.2-1.0 degrees) and how those errors affect river streamflow simulations. It is used local intensity-duration-frequency (IDF) curves and gridded precipitation datasets (MSWEP and ERA5-Land) as references for Eta assessment. In general, Eta underestimates subdaily extreme precipitation across South America, regardless of the driven GCM. The median bias of a 10-year return period daily precipitation is -36 mm (1st and 3rd quantiles -58 and -17 mm) compared to MSWEP and -26 mm (1st and 3rd quantiles -45 and -11 mm) compared to ERA5-Land. However, the relative errors reduce with temporal and spatial aggregation. For example, the average bias of extreme precipitation decreases 8.4 and 5.4 percentage points from 1- to 5-day duration compared to MSWEP and ERA5-Land, respectively. The negative biases observed for precipitation (approximate to$$ \approx $$20%) are propagated to the flood discharges (approximate to$$ \approx $$40%), and these errors reduce with the drainage area. In general, there are greater biases in extreme discharges for small basins, but these errors considerably reduce for basins larger than 30,000 km(2) compared to MGB-MSWEP simulations. Compared to MGB-ERA5-Land simulations, MGB-Eta presents relatively similar errors for basins of different sizes, probably due to the high negative bias for not only extreme but average precipitation as well.
ÁreaMET
Arranjourlib.net > Fonds > Produção a partir de 2021 > CGCT > Assessing extreme precipitation...
Conteúdo da Pasta docacessar
Conteúdo da Pasta sourcenão têm arquivos
Conteúdo da Pasta agreement
agreement.html 04/01/2023 09:51 1.0 KiB 
4. Condições de acesso e uso
Idiomaen
Arquivo AlvoIntl Journal of Climatology - 2022 - Br da - Assessing extreme precipitation from a regional climate model in different.pdf
Grupo de Usuáriossimone
Grupo de Leitoresadministrator
simone
Visibilidadeshown
Política de Arquivamentodenypublisher denyfinaldraft
Permissão de Leituradeny from all and allow from 150.163
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Repositório Espelhourlib.net/www/2021/06.04.03.40.25
Unidades Imediatamente Superiores8JMKD3MGPCW/46KUATE
Lista de Itens Citandosid.inpe.br/bibdigital/2022/04.03.22.23 2
DivulgaçãoWEBSCI; PORTALCAPES; COMPENDEX; SCOPUS.
Acervo Hospedeirourlib.net/www/2021/06.04.03.40
6. Notas
Campos Vaziosalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark nextedition notes parameterlist parentrepositories previousedition previouslowerunit progress project resumeid rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url
7. Controle da descrição
e-Mail (login)simone
atualizar 


Fechar