Construction of a high-resolution gridded rainfall dataset for Peru from 1981 to the present day
Descripción del Articulo
A new gridded rainfall dataset available for Peru is introduced, called PISCOp V2.1 (Peruvian Interpolated data of SENAMHI’s Climatological and Hydrological Observations). PISCOp has been developed for the period 1981 to the present, with an average latency of eight weeks at 0.1° spatial resolution....
Autores: | , , , , , |
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Formato: | artículo |
Fecha de Publicación: | 2020 |
Institución: | Servicio Nacional de Meteorología e Hidrología del Perú |
Repositorio: | SENAMHI-Institucional |
Lenguaje: | inglés |
OAI Identifier: | oai:repositorio.senamhi.gob.pe:20.500.12542/288 |
Enlace del recurso: | https://hdl.handle.net/20.500.12542/288 https://doi.org/10.1080/02626667.2019.1649411 |
Nivel de acceso: | acceso abierto |
Materia: | Climatología Lluvia Abastecimiento de Agua Radar Algoritmo https://purl.org/pe-repo/ocde/ford#1.05.11 precipitacion - Clima y Eventos Naturales |
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dc.title.en_US.fl_str_mv |
Construction of a high-resolution gridded rainfall dataset for Peru from 1981 to the present day |
title |
Construction of a high-resolution gridded rainfall dataset for Peru from 1981 to the present day |
spellingShingle |
Construction of a high-resolution gridded rainfall dataset for Peru from 1981 to the present day Aybar Camacho, Cesar Luis Climatología Lluvia Abastecimiento de Agua Radar Algoritmo https://purl.org/pe-repo/ocde/ford#1.05.11 precipitacion - Clima y Eventos Naturales |
title_short |
Construction of a high-resolution gridded rainfall dataset for Peru from 1981 to the present day |
title_full |
Construction of a high-resolution gridded rainfall dataset for Peru from 1981 to the present day |
title_fullStr |
Construction of a high-resolution gridded rainfall dataset for Peru from 1981 to the present day |
title_full_unstemmed |
Construction of a high-resolution gridded rainfall dataset for Peru from 1981 to the present day |
title_sort |
Construction of a high-resolution gridded rainfall dataset for Peru from 1981 to the present day |
author |
Aybar Camacho, Cesar Luis |
author_facet |
Aybar Camacho, Cesar Luis Fernández, C. Huerta, Adrian Lavado-Casimiro, W. Vega-Jácome, Fiorella Felipe-Obando, Oscar |
author_role |
author |
author2 |
Fernández, C. Huerta, Adrian Lavado-Casimiro, W. Vega-Jácome, Fiorella Felipe-Obando, Oscar |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Aybar Camacho, Cesar Luis Fernández, C. Huerta, Adrian Lavado-Casimiro, W. Vega-Jácome, Fiorella Felipe-Obando, Oscar |
dc.subject.en_US.fl_str_mv |
Climatología Lluvia Abastecimiento de Agua Radar Algoritmo |
topic |
Climatología Lluvia Abastecimiento de Agua Radar Algoritmo https://purl.org/pe-repo/ocde/ford#1.05.11 precipitacion - Clima y Eventos Naturales |
dc.subject.ocde.es_PE.fl_str_mv |
https://purl.org/pe-repo/ocde/ford#1.05.11 |
dc.subject.sinia.es_PE.fl_str_mv |
precipitacion - Clima y Eventos Naturales |
description |
A new gridded rainfall dataset available for Peru is introduced, called PISCOp V2.1 (Peruvian Interpolated data of SENAMHI’s Climatological and Hydrological Observations). PISCOp has been developed for the period 1981 to the present, with an average latency of eight weeks at 0.1° spatial resolution. The merging algorithm is based on geostatistical and deterministic interpolation methods including three different rainfall sources: (i) the national quality-controlled and infilled raingauge dataset, (ii) radar-gauge merged precipitation climatologies and (iii) the Climate Hazards Group Infrared Precipitation (CHIRP) estimates. The validation results suggest that precipitation estimates are acceptable showing the highest performance for the Pacific coast and the western flank of the Andes. Furthermore, a meticulous quality-control and gap-infilling procedure allowed us to reduce the formation of inhomogeneities (non-climatic breaks). The dataset is publicly available at https://piscoprec.github.io/ and is intended to support hydrological studies and water management practices. |
publishDate |
2020 |
dc.date.accessioned.none.fl_str_mv |
2020-03-20T06:12:23Z |
dc.date.available.none.fl_str_mv |
2020-03-20T06:12:23Z |
dc.date.issued.fl_str_mv |
2020 |
dc.type.es_PE.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.sinia.es_PE.fl_str_mv |
text/publicacion cientifica |
format |
article |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12542/288 |
dc.identifier.isni.none.fl_str_mv |
0000 0001 0746 0446 |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1080/02626667.2019.1649411 |
dc.identifier.journal.es_PE.fl_str_mv |
Hydrological Sciences Journal |
dc.identifier.url.none.fl_str_mv |
https://hdl.handle.net/20.500.12542/288 https://hdl.handle.net/20.500.12542/288 https://hdl.handle.net/20.500.12542/288 |
url |
https://hdl.handle.net/20.500.12542/288 https://doi.org/10.1080/02626667.2019.1649411 |
identifier_str_mv |
0000 0001 0746 0446 Hydrological Sciences Journal |
dc.language.iso.es_PE.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.none.fl_str_mv |
urn:issn:2150-3435 |
dc.relation.uri.es_PE.fl_str_mv |
https://www.tandfonline.com/doi/abs/10.1080/02626667.2019.1649411?journalCode=thsj20 |
dc.relation.uri.none.fl_str_mv |
https://www.tandfonline.com/doi/epdf/10.1080/02626667.2019.1649411?needAccess=true |
dc.rights.es_PE.fl_str_mv |
info:eu-repo/semantics/openAccess Reconocimiento - No comercial - Sin obra derivada (CC BY-NC-ND) |
dc.rights.uri.es_PE.fl_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
Reconocimiento - No comercial - Sin obra derivada (CC BY-NC-ND) https://creativecommons.org/licenses/by-nc-nd/4.0/ |
dc.publisher.es_PE.fl_str_mv |
Taylor and Francis |
dc.source.es_PE.fl_str_mv |
Repositorio Institucional - SENAMHI Servicio Nacional de Meteorología e Hidrología del Perú |
dc.source.none.fl_str_mv |
reponame:SENAMHI-Institucional instname:Servicio Nacional de Meteorología e Hidrología del Perú instacron:SENAMHI |
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Servicio Nacional de Meteorología e Hidrología del Perú |
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SENAMHI |
institution |
SENAMHI |
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SENAMHI-Institucional |
collection |
SENAMHI-Institucional |
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Aybar Camacho, Cesar LuisFernández, C.Huerta, AdrianLavado-Casimiro, W.Vega-Jácome, FiorellaFelipe-Obando, Oscar2020-03-20T06:12:23Z2020-03-20T06:12:23Z2020https://hdl.handle.net/20.500.12542/2880000 0001 0746 0446https://doi.org/10.1080/02626667.2019.1649411Hydrological Sciences Journalhttps://hdl.handle.net/20.500.12542/288https://hdl.handle.net/20.500.12542/288https://hdl.handle.net/20.500.12542/288A new gridded rainfall dataset available for Peru is introduced, called PISCOp V2.1 (Peruvian Interpolated data of SENAMHI’s Climatological and Hydrological Observations). PISCOp has been developed for the period 1981 to the present, with an average latency of eight weeks at 0.1° spatial resolution. The merging algorithm is based on geostatistical and deterministic interpolation methods including three different rainfall sources: (i) the national quality-controlled and infilled raingauge dataset, (ii) radar-gauge merged precipitation climatologies and (iii) the Climate Hazards Group Infrared Precipitation (CHIRP) estimates. The validation results suggest that precipitation estimates are acceptable showing the highest performance for the Pacific coast and the western flank of the Andes. Furthermore, a meticulous quality-control and gap-infilling procedure allowed us to reduce the formation of inhomogeneities (non-climatic breaks). The dataset is publicly available at https://piscoprec.github.io/ and is intended to support hydrological studies and water management practices.Por paresengTaylor and Francisurn:issn:2150-3435https://www.tandfonline.com/doi/abs/10.1080/02626667.2019.1649411?journalCode=thsj20https://www.tandfonline.com/doi/epdf/10.1080/02626667.2019.1649411?needAccess=trueinfo:eu-repo/semantics/openAccessReconocimiento - No comercial - Sin obra derivada (CC BY-NC-ND)https://creativecommons.org/licenses/by-nc-nd/4.0/Repositorio Institucional - SENAMHIServicio Nacional de Meteorología e Hidrología del Perúreponame:SENAMHI-Institucionalinstname:Servicio Nacional de Meteorología e Hidrología del Perúinstacron:SENAMHIClimatologíaLluviaAbastecimiento de AguaRadarAlgoritmohttps://purl.org/pe-repo/ocde/ford#1.05.11precipitacion - Clima y Eventos NaturalesConstruction of a high-resolution gridded rainfall dataset for Peru from 1981 to the present dayinfo:eu-repo/semantics/articletext/publicacion cientificaCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; 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Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).