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....

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Detalles Bibliográficos
Autores: Aybar Camacho, Cesar Luis, Fernández, C., Huerta, Adrian, Lavado-Casimiro, W., Vega-Jácome, Fiorella, Felipe-Obando, Oscar
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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network_name_str SENAMHI-Institucional
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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
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dc.rights.es_PE.fl_str_mv info:eu-repo/semantics/openAccess
Reconocimiento - No comercial - Sin obra derivada (CC BY-NC-ND)
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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
instname_str Servicio Nacional de Meteorología e Hidrología del Perú
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spelling 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). 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