Using stochastic space-time models to map extreme precipitation in southern Portugal
Autor(a) principal: | |
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Data de Publicação: | 2008 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://doi.org/10.5194/nhess-8-763-2008 |
Resumo: | The topographic characteristics and spatial climatic diversity are significant in the South of continental Portugal where the rainfall regime is typically Mediterranean. Direct sequential cosimulation is proposed for mapping an extreme precipitation index in southern Portugal using elevation as auxiliary information. The analysed index (R5D) can be considered a flood indicator because it provides a measure of medium-term precipitation total. The methodology accounts for local data variability and incorporates space-time models that allow capturing long-term trends of extreme precipitation, and local changes in the relationship between elevation and extreme precipitation through time. Annual gridded datasets of the flood indicator are produced from 1940 to 1999 on 800 m×800 m grids by using the space-time relationship between elevation and the index. Uncertainty evaluations of the proposed scenarios are also produced for each year. The results indicate that the relationship between elevation and extreme precipitation varies locally and has decreased through time over the study region. In wetter years the flood indicator exhibits the highest values in mountainous regions of the South, while in drier years the spatial pattern of extreme precipitation has much less variability over the study region. The uncertainty of extreme precipitation estimates also varies in time and space, and in earlier decades is strongly dependent on the density of the monitoring stations network. The produced maps will be useful in regional and local studies related to climate change, desertification, land and water resources management, hydrological modelling, and flood mitigation planning. |
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Using stochastic space-time models to map extreme precipitation in southern PortugalEarth and Planetary Sciences(all)SDG 13 - Climate ActionSDG 15 - Life on LandThe topographic characteristics and spatial climatic diversity are significant in the South of continental Portugal where the rainfall regime is typically Mediterranean. Direct sequential cosimulation is proposed for mapping an extreme precipitation index in southern Portugal using elevation as auxiliary information. The analysed index (R5D) can be considered a flood indicator because it provides a measure of medium-term precipitation total. The methodology accounts for local data variability and incorporates space-time models that allow capturing long-term trends of extreme precipitation, and local changes in the relationship between elevation and extreme precipitation through time. Annual gridded datasets of the flood indicator are produced from 1940 to 1999 on 800 m×800 m grids by using the space-time relationship between elevation and the index. Uncertainty evaluations of the proposed scenarios are also produced for each year. The results indicate that the relationship between elevation and extreme precipitation varies locally and has decreased through time over the study region. In wetter years the flood indicator exhibits the highest values in mountainous regions of the South, while in drier years the spatial pattern of extreme precipitation has much less variability over the study region. The uncertainty of extreme precipitation estimates also varies in time and space, and in earlier decades is strongly dependent on the density of the monitoring stations network. The produced maps will be useful in regional and local studies related to climate change, desertification, land and water resources management, hydrological modelling, and flood mitigation planning.NOVA Information Management School (NOVA IMS)RUNCosta, Ana CristinaDurão, R.Pereira, Maria JoãoSoares, Amílcar2018-01-11T23:22:56Z2008-07-012008-07-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article11application/pdfhttps://doi.org/10.5194/nhess-8-763-2008eng1561-8633PURE: 3263392http://www.scopus.com/inward/record.url?scp=49049120096&partnerID=8YFLogxKhttps://doi.org/10.5194/nhess-8-763-2008info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:14:58Zoai:run.unl.pt:10362/28027Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:28:50.998817Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Using stochastic space-time models to map extreme precipitation in southern Portugal |
title |
Using stochastic space-time models to map extreme precipitation in southern Portugal |
spellingShingle |
Using stochastic space-time models to map extreme precipitation in southern Portugal Costa, Ana Cristina Earth and Planetary Sciences(all) SDG 13 - Climate Action SDG 15 - Life on Land |
title_short |
Using stochastic space-time models to map extreme precipitation in southern Portugal |
title_full |
Using stochastic space-time models to map extreme precipitation in southern Portugal |
title_fullStr |
Using stochastic space-time models to map extreme precipitation in southern Portugal |
title_full_unstemmed |
Using stochastic space-time models to map extreme precipitation in southern Portugal |
title_sort |
Using stochastic space-time models to map extreme precipitation in southern Portugal |
author |
Costa, Ana Cristina |
author_facet |
Costa, Ana Cristina Durão, R. Pereira, Maria João Soares, Amílcar |
author_role |
author |
author2 |
Durão, R. Pereira, Maria João Soares, Amílcar |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
NOVA Information Management School (NOVA IMS) RUN |
dc.contributor.author.fl_str_mv |
Costa, Ana Cristina Durão, R. Pereira, Maria João Soares, Amílcar |
dc.subject.por.fl_str_mv |
Earth and Planetary Sciences(all) SDG 13 - Climate Action SDG 15 - Life on Land |
topic |
Earth and Planetary Sciences(all) SDG 13 - Climate Action SDG 15 - Life on Land |
description |
The topographic characteristics and spatial climatic diversity are significant in the South of continental Portugal where the rainfall regime is typically Mediterranean. Direct sequential cosimulation is proposed for mapping an extreme precipitation index in southern Portugal using elevation as auxiliary information. The analysed index (R5D) can be considered a flood indicator because it provides a measure of medium-term precipitation total. The methodology accounts for local data variability and incorporates space-time models that allow capturing long-term trends of extreme precipitation, and local changes in the relationship between elevation and extreme precipitation through time. Annual gridded datasets of the flood indicator are produced from 1940 to 1999 on 800 m×800 m grids by using the space-time relationship between elevation and the index. Uncertainty evaluations of the proposed scenarios are also produced for each year. The results indicate that the relationship between elevation and extreme precipitation varies locally and has decreased through time over the study region. In wetter years the flood indicator exhibits the highest values in mountainous regions of the South, while in drier years the spatial pattern of extreme precipitation has much less variability over the study region. The uncertainty of extreme precipitation estimates also varies in time and space, and in earlier decades is strongly dependent on the density of the monitoring stations network. The produced maps will be useful in regional and local studies related to climate change, desertification, land and water resources management, hydrological modelling, and flood mitigation planning. |
publishDate |
2008 |
dc.date.none.fl_str_mv |
2008-07-01 2008-07-01T00:00:00Z 2018-01-11T23:22:56Z |
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 |
https://doi.org/10.5194/nhess-8-763-2008 |
url |
https://doi.org/10.5194/nhess-8-763-2008 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1561-8633 PURE: 3263392 http://www.scopus.com/inward/record.url?scp=49049120096&partnerID=8YFLogxK https://doi.org/10.5194/nhess-8-763-2008 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
11 application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799137914087538688 |