Performance of Regional Climate Model Precipitation Simulations Over the Terrain‐Complex Andes‐Amazon Transition Region

Autores
Gutierrez, Ricardo A.; Junquas, Clémentine; Armijos, Elisa; Sörensson, Anna; Espinoza, Jhan Carlo
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Regional climate models (RCMs) are widely used to assess future impacts associated with climate change at regional and local scales. RCMs must represent relevant climate variables in the present-day climate to be considered fit-for-purpose for impact assessment. This condition is particularly difficult to meet over complex regions such as the Andes-Amazon transition region, where the Andean topography and abundance of tropical rainfall regimes remain a challenge for numerical climate models. In this study, we evaluate the ability of 30 regional climate simulations (6 RCMs driven by 10 global climate models) to reproduce historical (1981–2005) rainfall climatology and temporal variability over the Andes-Amazon transition region. We assess spatio-temporal features such as spatial distribution of rainfall, focusing on the orographic effects over the Andes-Amazon “rainfall hotspots” region, and seasonal and interannual precipitation variability. The Eta RCM exhibits the highest spatial correlation (up to 0.6) and accurately reproduces mean annual precipitation and orographic precipitation patterns across the region, while some other RCMs have good performances at specific locations. Most RCMs simulate a wet bias over the highlands, particularly at the eastern Andean summits, as evidenced by the 100%–2,500% overestimations of precipitation in these regions. Annual cycles are well represented by most RCMs, but peak seasons are exaggerated, especially at equatorial locations. No RCM is particularly skillful in reproducing the interannual variability patterns. Results highlight skills and weaknesses of the different regional climate simulations, and can assist in the selection of regional climate simulations for impact studies in the Andes-Amazon transition zone.
Fil: Gutierrez, Ricardo A.. Universidad Nacional Agraria La Molina; Perú. Instituto Geofísico del Perú; Perú
Fil: Junquas, Clémentine. Universite Grenoble Alpes; Francia. Servicio Nacional de Meteorología e Hidrología; Perú
Fil: Armijos, Elisa. Universidad Nacional Agraria La Molina; Perú. Instituto Geofísico del Peru; Perú
Fil: Sörensson, Anna. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios del Clima y sus Impactos; Argentina
Fil: Espinoza, Jhan Carlo. Universite Grenoble Alpes; Francia. Pontificia Universidad Católica de Perú; Perú
Materia
REGIONAL CLIMATE MODELLING
ANDES-AMAZON TRANSITION ZONE
PRECIPITATION
ETA RCM
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:11336/261111
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Performance of Regional Climate Model Precipitation Simulations Over the Terrain‐Complex Andes‐Amazon Transition RegionGutierrez, Ricardo A.Junquas, ClémentineArmijos, ElisaSörensson, AnnaEspinoza, Jhan CarloREGIONAL CLIMATE MODELLINGANDES-AMAZON TRANSITION ZONEPRECIPITATIONETA RCMhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Regional climate models (RCMs) are widely used to assess future impacts associated with climate change at regional and local scales. RCMs must represent relevant climate variables in the present-day climate to be considered fit-for-purpose for impact assessment. This condition is particularly difficult to meet over complex regions such as the Andes-Amazon transition region, where the Andean topography and abundance of tropical rainfall regimes remain a challenge for numerical climate models. In this study, we evaluate the ability of 30 regional climate simulations (6 RCMs driven by 10 global climate models) to reproduce historical (1981–2005) rainfall climatology and temporal variability over the Andes-Amazon transition region. We assess spatio-temporal features such as spatial distribution of rainfall, focusing on the orographic effects over the Andes-Amazon “rainfall hotspots” region, and seasonal and interannual precipitation variability. The Eta RCM exhibits the highest spatial correlation (up to 0.6) and accurately reproduces mean annual precipitation and orographic precipitation patterns across the region, while some other RCMs have good performances at specific locations. Most RCMs simulate a wet bias over the highlands, particularly at the eastern Andean summits, as evidenced by the 100%–2,500% overestimations of precipitation in these regions. Annual cycles are well represented by most RCMs, but peak seasons are exaggerated, especially at equatorial locations. No RCM is particularly skillful in reproducing the interannual variability patterns. Results highlight skills and weaknesses of the different regional climate simulations, and can assist in the selection of regional climate simulations for impact studies in the Andes-Amazon transition zone.Fil: Gutierrez, Ricardo A.. Universidad Nacional Agraria La Molina; Perú. Instituto Geofísico del Perú; PerúFil: Junquas, Clémentine. Universite Grenoble Alpes; Francia. Servicio Nacional de Meteorología e Hidrología; PerúFil: Armijos, Elisa. Universidad Nacional Agraria La Molina; Perú. Instituto Geofísico del Peru; PerúFil: Sörensson, Anna. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios del Clima y sus Impactos; ArgentinaFil: Espinoza, Jhan Carlo. Universite Grenoble Alpes; Francia. Pontificia Universidad Católica de Perú; PerúWiley2024-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/261111Gutierrez, Ricardo A.; Junquas, Clémentine; Armijos, Elisa; Sörensson, Anna; Espinoza, Jhan Carlo; Performance of Regional Climate Model Precipitation Simulations Over the Terrain‐Complex Andes‐Amazon Transition Region; Wiley; Journal of Geophysical Research; 129; 1; 1-2024; 1-232169-897X2169-8996CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JD038618info:eu-repo/semantics/altIdentifier/doi/10.1029/2023JD038618info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:56:00Zoai:ri.conicet.gov.ar:11336/261111instacron: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:34982025-09-03 09:56:01.07CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Performance of Regional Climate Model Precipitation Simulations Over the Terrain‐Complex Andes‐Amazon Transition Region
title Performance of Regional Climate Model Precipitation Simulations Over the Terrain‐Complex Andes‐Amazon Transition Region
spellingShingle Performance of Regional Climate Model Precipitation Simulations Over the Terrain‐Complex Andes‐Amazon Transition Region
Gutierrez, Ricardo A.
REGIONAL CLIMATE MODELLING
ANDES-AMAZON TRANSITION ZONE
PRECIPITATION
ETA RCM
title_short Performance of Regional Climate Model Precipitation Simulations Over the Terrain‐Complex Andes‐Amazon Transition Region
title_full Performance of Regional Climate Model Precipitation Simulations Over the Terrain‐Complex Andes‐Amazon Transition Region
title_fullStr Performance of Regional Climate Model Precipitation Simulations Over the Terrain‐Complex Andes‐Amazon Transition Region
title_full_unstemmed Performance of Regional Climate Model Precipitation Simulations Over the Terrain‐Complex Andes‐Amazon Transition Region
title_sort Performance of Regional Climate Model Precipitation Simulations Over the Terrain‐Complex Andes‐Amazon Transition Region
dc.creator.none.fl_str_mv Gutierrez, Ricardo A.
Junquas, Clémentine
Armijos, Elisa
Sörensson, Anna
Espinoza, Jhan Carlo
author Gutierrez, Ricardo A.
author_facet Gutierrez, Ricardo A.
Junquas, Clémentine
Armijos, Elisa
Sörensson, Anna
Espinoza, Jhan Carlo
author_role author
author2 Junquas, Clémentine
Armijos, Elisa
Sörensson, Anna
Espinoza, Jhan Carlo
author2_role author
author
author
author
dc.subject.none.fl_str_mv REGIONAL CLIMATE MODELLING
ANDES-AMAZON TRANSITION ZONE
PRECIPITATION
ETA RCM
topic REGIONAL CLIMATE MODELLING
ANDES-AMAZON TRANSITION ZONE
PRECIPITATION
ETA RCM
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Regional climate models (RCMs) are widely used to assess future impacts associated with climate change at regional and local scales. RCMs must represent relevant climate variables in the present-day climate to be considered fit-for-purpose for impact assessment. This condition is particularly difficult to meet over complex regions such as the Andes-Amazon transition region, where the Andean topography and abundance of tropical rainfall regimes remain a challenge for numerical climate models. In this study, we evaluate the ability of 30 regional climate simulations (6 RCMs driven by 10 global climate models) to reproduce historical (1981–2005) rainfall climatology and temporal variability over the Andes-Amazon transition region. We assess spatio-temporal features such as spatial distribution of rainfall, focusing on the orographic effects over the Andes-Amazon “rainfall hotspots” region, and seasonal and interannual precipitation variability. The Eta RCM exhibits the highest spatial correlation (up to 0.6) and accurately reproduces mean annual precipitation and orographic precipitation patterns across the region, while some other RCMs have good performances at specific locations. Most RCMs simulate a wet bias over the highlands, particularly at the eastern Andean summits, as evidenced by the 100%–2,500% overestimations of precipitation in these regions. Annual cycles are well represented by most RCMs, but peak seasons are exaggerated, especially at equatorial locations. No RCM is particularly skillful in reproducing the interannual variability patterns. Results highlight skills and weaknesses of the different regional climate simulations, and can assist in the selection of regional climate simulations for impact studies in the Andes-Amazon transition zone.
Fil: Gutierrez, Ricardo A.. Universidad Nacional Agraria La Molina; Perú. Instituto Geofísico del Perú; Perú
Fil: Junquas, Clémentine. Universite Grenoble Alpes; Francia. Servicio Nacional de Meteorología e Hidrología; Perú
Fil: Armijos, Elisa. Universidad Nacional Agraria La Molina; Perú. Instituto Geofísico del Peru; Perú
Fil: Sörensson, Anna. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios del Clima y sus Impactos; Argentina
Fil: Espinoza, Jhan Carlo. Universite Grenoble Alpes; Francia. Pontificia Universidad Católica de Perú; Perú
description Regional climate models (RCMs) are widely used to assess future impacts associated with climate change at regional and local scales. RCMs must represent relevant climate variables in the present-day climate to be considered fit-for-purpose for impact assessment. This condition is particularly difficult to meet over complex regions such as the Andes-Amazon transition region, where the Andean topography and abundance of tropical rainfall regimes remain a challenge for numerical climate models. In this study, we evaluate the ability of 30 regional climate simulations (6 RCMs driven by 10 global climate models) to reproduce historical (1981–2005) rainfall climatology and temporal variability over the Andes-Amazon transition region. We assess spatio-temporal features such as spatial distribution of rainfall, focusing on the orographic effects over the Andes-Amazon “rainfall hotspots” region, and seasonal and interannual precipitation variability. The Eta RCM exhibits the highest spatial correlation (up to 0.6) and accurately reproduces mean annual precipitation and orographic precipitation patterns across the region, while some other RCMs have good performances at specific locations. Most RCMs simulate a wet bias over the highlands, particularly at the eastern Andean summits, as evidenced by the 100%–2,500% overestimations of precipitation in these regions. Annual cycles are well represented by most RCMs, but peak seasons are exaggerated, especially at equatorial locations. No RCM is particularly skillful in reproducing the interannual variability patterns. Results highlight skills and weaknesses of the different regional climate simulations, and can assist in the selection of regional climate simulations for impact studies in the Andes-Amazon transition zone.
publishDate 2024
dc.date.none.fl_str_mv 2024-01
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/11336/261111
Gutierrez, Ricardo A.; Junquas, Clémentine; Armijos, Elisa; Sörensson, Anna; Espinoza, Jhan Carlo; Performance of Regional Climate Model Precipitation Simulations Over the Terrain‐Complex Andes‐Amazon Transition Region; Wiley; Journal of Geophysical Research; 129; 1; 1-2024; 1-23
2169-897X
2169-8996
CONICET Digital
CONICET
url http://hdl.handle.net/11336/261111
identifier_str_mv Gutierrez, Ricardo A.; Junquas, Clémentine; Armijos, Elisa; Sörensson, Anna; Espinoza, Jhan Carlo; Performance of Regional Climate Model Precipitation Simulations Over the Terrain‐Complex Andes‐Amazon Transition Region; Wiley; Journal of Geophysical Research; 129; 1; 1-2024; 1-23
2169-897X
2169-8996
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://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JD038618
info:eu-repo/semantics/altIdentifier/doi/10.1029/2023JD038618
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 Wiley
publisher.none.fl_str_mv Wiley
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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