A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023

Autores
Canziani, Pablo Osvaldo; Lakkis, Susan Gabriela; Yuchechen, Adrian Enrique
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This study investigates the long-term variability and extremes of monthly precipitation during 150 years or more at 4 locations in Argentina: Corrientes, Córdoba, Buenos Aires, and Bahía Blanca. Annual and seasonal trends, extreme dry and wet months over the whole period, and the relationships between large-scale climate drivers and monthly rainfall are considered. Results show that, except for Córdoba, the complete anomaly timeseries trend analysis for all other stations yielded null trends over the centennial study period. Considerable month-to-month variability is observed for all locations together with the existence of low-frequency decadal to interdecadal variability, both for monthly precipitation anomalies and for statistically significant excess and deficit months. Linear fits considering oceanic climate indicators as drivers of variability yield significant differences between locations, while not between full records and seasonally sampled. Issues regarding the use of linear analysis to quantify variability, the dispersion along the timeline of record extreme rainy months at each location, together with the evidence of severe daily precipitation events not necessarily coinciding with the ranking of the rainiest months at each location, highlights the challenges of understanding the drivers of variability of both monthly and severe daily precipitation and the need of using extended centennial timeseries whenever possible.
Fil: Canziani, Pablo Osvaldo. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Unidad de Investigación y Desarrollo de las Ingenierías; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Lakkis, Susan Gabriela. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Unidad de Investigación y Desarrollo de las Ingenierías; Argentina
Fil: Yuchechen, Adrian Enrique. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Unidad de Investigación y Desarrollo de las Ingenierías; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
ARGENTINA
LONG-TERM DATA
MONTHLY PRECIPITATION
EXTREME EVENTS
CLIMATE INDICES
TRENDS
LOW-FREQUENCY VARIABILITY
CLIMATE CHANGE
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/271250
Acceder
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network_name_str CONICET Digital (CONICET)
spelling A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023Canziani, Pablo OsvaldoLakkis, Susan GabrielaYuchechen, Adrian EnriqueARGENTINALONG-TERM DATAMONTHLY PRECIPITATIONEXTREME EVENTSCLIMATE INDICESTRENDSLOW-FREQUENCY VARIABILITYCLIMATE CHANGEhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1https://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1This study investigates the long-term variability and extremes of monthly precipitation during 150 years or more at 4 locations in Argentina: Corrientes, Córdoba, Buenos Aires, and Bahía Blanca. Annual and seasonal trends, extreme dry and wet months over the whole period, and the relationships between large-scale climate drivers and monthly rainfall are considered. Results show that, except for Córdoba, the complete anomaly timeseries trend analysis for all other stations yielded null trends over the centennial study period. Considerable month-to-month variability is observed for all locations together with the existence of low-frequency decadal to interdecadal variability, both for monthly precipitation anomalies and for statistically significant excess and deficit months. Linear fits considering oceanic climate indicators as drivers of variability yield significant differences between locations, while not between full records and seasonally sampled. Issues regarding the use of linear analysis to quantify variability, the dispersion along the timeline of record extreme rainy months at each location, together with the evidence of severe daily precipitation events not necessarily coinciding with the ranking of the rainiest months at each location, highlights the challenges of understanding the drivers of variability of both monthly and severe daily precipitation and the need of using extended centennial timeseries whenever possible.Fil: Canziani, Pablo Osvaldo. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Unidad de Investigación y Desarrollo de las Ingenierías; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lakkis, Susan Gabriela. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Unidad de Investigación y Desarrollo de las Ingenierías; ArgentinaFil: Yuchechen, Adrian Enrique. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Unidad de Investigación y Desarrollo de las Ingenierías; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaMDPI2025-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/271250Canziani, Pablo Osvaldo; Lakkis, Susan Gabriela; Yuchechen, Adrian Enrique; A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023; MDPI; Atmosphere; 16; 8; 7-2025; 1-272073-4433CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2073-4433/16/8/914info:eu-repo/semantics/altIdentifier/doi/10.3390/atmos16080914info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:06:00Zoai:ri.conicet.gov.ar:11336/271250instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:06:00.464CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023
title A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023
spellingShingle A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023
Canziani, Pablo Osvaldo
ARGENTINA
LONG-TERM DATA
MONTHLY PRECIPITATION
EXTREME EVENTS
CLIMATE INDICES
TRENDS
LOW-FREQUENCY VARIABILITY
CLIMATE CHANGE
title_short A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023
title_full A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023
title_fullStr A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023
title_full_unstemmed A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023
title_sort A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023
dc.creator.none.fl_str_mv Canziani, Pablo Osvaldo
Lakkis, Susan Gabriela
Yuchechen, Adrian Enrique
author Canziani, Pablo Osvaldo
author_facet Canziani, Pablo Osvaldo
Lakkis, Susan Gabriela
Yuchechen, Adrian Enrique
author_role author
author2 Lakkis, Susan Gabriela
Yuchechen, Adrian Enrique
author2_role author
author
dc.subject.none.fl_str_mv ARGENTINA
LONG-TERM DATA
MONTHLY PRECIPITATION
EXTREME EVENTS
CLIMATE INDICES
TRENDS
LOW-FREQUENCY VARIABILITY
CLIMATE CHANGE
topic ARGENTINA
LONG-TERM DATA
MONTHLY PRECIPITATION
EXTREME EVENTS
CLIMATE INDICES
TRENDS
LOW-FREQUENCY VARIABILITY
CLIMATE CHANGE
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv This study investigates the long-term variability and extremes of monthly precipitation during 150 years or more at 4 locations in Argentina: Corrientes, Córdoba, Buenos Aires, and Bahía Blanca. Annual and seasonal trends, extreme dry and wet months over the whole period, and the relationships between large-scale climate drivers and monthly rainfall are considered. Results show that, except for Córdoba, the complete anomaly timeseries trend analysis for all other stations yielded null trends over the centennial study period. Considerable month-to-month variability is observed for all locations together with the existence of low-frequency decadal to interdecadal variability, both for monthly precipitation anomalies and for statistically significant excess and deficit months. Linear fits considering oceanic climate indicators as drivers of variability yield significant differences between locations, while not between full records and seasonally sampled. Issues regarding the use of linear analysis to quantify variability, the dispersion along the timeline of record extreme rainy months at each location, together with the evidence of severe daily precipitation events not necessarily coinciding with the ranking of the rainiest months at each location, highlights the challenges of understanding the drivers of variability of both monthly and severe daily precipitation and the need of using extended centennial timeseries whenever possible.
Fil: Canziani, Pablo Osvaldo. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Unidad de Investigación y Desarrollo de las Ingenierías; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Lakkis, Susan Gabriela. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Unidad de Investigación y Desarrollo de las Ingenierías; Argentina
Fil: Yuchechen, Adrian Enrique. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Unidad de Investigación y Desarrollo de las Ingenierías; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description This study investigates the long-term variability and extremes of monthly precipitation during 150 years or more at 4 locations in Argentina: Corrientes, Córdoba, Buenos Aires, and Bahía Blanca. Annual and seasonal trends, extreme dry and wet months over the whole period, and the relationships between large-scale climate drivers and monthly rainfall are considered. Results show that, except for Córdoba, the complete anomaly timeseries trend analysis for all other stations yielded null trends over the centennial study period. Considerable month-to-month variability is observed for all locations together with the existence of low-frequency decadal to interdecadal variability, both for monthly precipitation anomalies and for statistically significant excess and deficit months. Linear fits considering oceanic climate indicators as drivers of variability yield significant differences between locations, while not between full records and seasonally sampled. Issues regarding the use of linear analysis to quantify variability, the dispersion along the timeline of record extreme rainy months at each location, together with the evidence of severe daily precipitation events not necessarily coinciding with the ranking of the rainiest months at each location, highlights the challenges of understanding the drivers of variability of both monthly and severe daily precipitation and the need of using extended centennial timeseries whenever possible.
publishDate 2025
dc.date.none.fl_str_mv 2025-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/271250
Canziani, Pablo Osvaldo; Lakkis, Susan Gabriela; Yuchechen, Adrian Enrique; A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023; MDPI; Atmosphere; 16; 8; 7-2025; 1-27
2073-4433
CONICET Digital
CONICET
url http://hdl.handle.net/11336/271250
identifier_str_mv Canziani, Pablo Osvaldo; Lakkis, Susan Gabriela; Yuchechen, Adrian Enrique; A Study of Monthly Precipitation Timeseries from Argentina (Corrientes, Córdoba, Buenos Aires, and Bahía Blanca) for the Period of 1860–2023; MDPI; Atmosphere; 16; 8; 7-2025; 1-27
2073-4433
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2073-4433/16/8/914
info:eu-repo/semantics/altIdentifier/doi/10.3390/atmos16080914
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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