Does the HadGEM3-GC3.1 GCM overestimate land precipitation at high resolution? A constraint based on observed river discharge

Autores
Müller, Omar Vicente; Vidale, Pier Luigi; Vannière, Benoît; Schiemann, Reinhard; McGuire, Patrick C.
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Previous studies showed that high-resolution GCMs overestimate land precipitation when compared against observation-based data. Particularly, high-resolution HadGEM3-GC3.1 shows a significant precipitation increase in mountainous regions, where the scarcity of gauge stations increases the uncertainty of gridded observations and reanalyses. This work evaluates such precipitation uncertainties indirectly through the assessment of river discharge, considering that an increase of ~10% in land precipitation produces ~28% more runoff when the resolution is enhanced from 1° to 0.25°, and ~50% of the global runoff is produced in 27% of global land dominated by mountains. We diagnosed the river flow by routing the runoff generated by HadGEM3-GC3.1 low- and high-resolution simulations. The river flow is evaluated using a set of 344 monitored catchments distributed around the world. We also infer the global discharge by constraining the simulations with observations following a novel approach that implies bias correction in monitored rivers with two methods, and extension of the correction to the river mouth, and along the coast. Our global discharge estimate is 47.4 ± 1.6 × 103 km3 yr−1, which is closer to the original high-resolution estimate (50.5 × 103 km3 yr−1) than to the low-resolution (39.6 × 103 km3 yr−1). The assessment suggests that high-resolution simulations perform better in mountainous regions, either because the better-defined orography favors the placement of precipitation in the correct catchment, leading to a more accurate distribution of runoff, or the orographic precipitation increases, reducing the dry runoff bias of coarse-resolution simulations. However, high-resolution slightly increases wet biases in catchments dominated by flat terrain. The improvement of model parameterizations and tuning may reduce the remaining errors in high-resolution simulations.
Fil: Müller, Omar Vicente. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingenieria y Ciencias Hidricas. Centro de Estudios de Variabilidad y Cambio Climatico.; Argentina. University Of Reading. Departament Of Meteorology; Reino Unido
Fil: Vidale, Pier Luigi. University Of Reading. Departament Of Meteorology; Reino Unido
Fil: Vannière, Benoît. University Of Reading. Departament Of Meteorology; Reino Unido
Fil: Schiemann, Reinhard. University Of Reading. Departament Of Meteorology; Reino Unido
Fil: McGuire, Patrick C.. University Of Reading. Departament Of Meteorology; Reino Unido
Materia
GLOBAL CLIMATE MODELS
RESOLUTION
GLOBAL RIVER DISCHARGE
GLOBAL LAND PRECIPITATION
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:11336/164943

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network_name_str CONICET Digital (CONICET)
spelling Does the HadGEM3-GC3.1 GCM overestimate land precipitation at high resolution? A constraint based on observed river dischargeMüller, Omar VicenteVidale, Pier LuigiVannière, BenoîtSchiemann, ReinhardMcGuire, Patrick C.GLOBAL CLIMATE MODELSRESOLUTIONGLOBAL RIVER DISCHARGEGLOBAL LAND PRECIPITATIONhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Previous studies showed that high-resolution GCMs overestimate land precipitation when compared against observation-based data. Particularly, high-resolution HadGEM3-GC3.1 shows a significant precipitation increase in mountainous regions, where the scarcity of gauge stations increases the uncertainty of gridded observations and reanalyses. This work evaluates such precipitation uncertainties indirectly through the assessment of river discharge, considering that an increase of ~10% in land precipitation produces ~28% more runoff when the resolution is enhanced from 1° to 0.25°, and ~50% of the global runoff is produced in 27% of global land dominated by mountains. We diagnosed the river flow by routing the runoff generated by HadGEM3-GC3.1 low- and high-resolution simulations. The river flow is evaluated using a set of 344 monitored catchments distributed around the world. We also infer the global discharge by constraining the simulations with observations following a novel approach that implies bias correction in monitored rivers with two methods, and extension of the correction to the river mouth, and along the coast. Our global discharge estimate is 47.4 ± 1.6 × 103 km3 yr−1, which is closer to the original high-resolution estimate (50.5 × 103 km3 yr−1) than to the low-resolution (39.6 × 103 km3 yr−1). The assessment suggests that high-resolution simulations perform better in mountainous regions, either because the better-defined orography favors the placement of precipitation in the correct catchment, leading to a more accurate distribution of runoff, or the orographic precipitation increases, reducing the dry runoff bias of coarse-resolution simulations. However, high-resolution slightly increases wet biases in catchments dominated by flat terrain. The improvement of model parameterizations and tuning may reduce the remaining errors in high-resolution simulations.Fil: Müller, Omar Vicente. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingenieria y Ciencias Hidricas. Centro de Estudios de Variabilidad y Cambio Climatico.; Argentina. University Of Reading. Departament Of Meteorology; Reino UnidoFil: Vidale, Pier Luigi. University Of Reading. Departament Of Meteorology; Reino UnidoFil: Vannière, Benoît. University Of Reading. Departament Of Meteorology; Reino UnidoFil: Schiemann, Reinhard. University Of Reading. Departament Of Meteorology; Reino UnidoFil: McGuire, Patrick C.. University Of Reading. Departament Of Meteorology; Reino UnidoAmerican Meteorological Society2021-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/164943Müller, Omar Vicente; Vidale, Pier Luigi; Vannière, Benoît; Schiemann, Reinhard; McGuire, Patrick C.; Does the HadGEM3-GC3.1 GCM overestimate land precipitation at high resolution? A constraint based on observed river discharge; American Meteorological Society; Journal of Hydrometeorology; 22; 8; 6-2021; 2131-21511525-755XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://journals.ametsoc.org/view/journals/hydr/aop/JHM-D-20-0290.1/JHM-D-20-0290.1.xmlinfo:eu-repo/semantics/altIdentifier/doi/10.1175/JHM-D-20-0290.1info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:48:26Zoai:ri.conicet.gov.ar:11336/164943instacron: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 09:48:26.486CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Does the HadGEM3-GC3.1 GCM overestimate land precipitation at high resolution? A constraint based on observed river discharge
title Does the HadGEM3-GC3.1 GCM overestimate land precipitation at high resolution? A constraint based on observed river discharge
spellingShingle Does the HadGEM3-GC3.1 GCM overestimate land precipitation at high resolution? A constraint based on observed river discharge
Müller, Omar Vicente
GLOBAL CLIMATE MODELS
RESOLUTION
GLOBAL RIVER DISCHARGE
GLOBAL LAND PRECIPITATION
title_short Does the HadGEM3-GC3.1 GCM overestimate land precipitation at high resolution? A constraint based on observed river discharge
title_full Does the HadGEM3-GC3.1 GCM overestimate land precipitation at high resolution? A constraint based on observed river discharge
title_fullStr Does the HadGEM3-GC3.1 GCM overestimate land precipitation at high resolution? A constraint based on observed river discharge
title_full_unstemmed Does the HadGEM3-GC3.1 GCM overestimate land precipitation at high resolution? A constraint based on observed river discharge
title_sort Does the HadGEM3-GC3.1 GCM overestimate land precipitation at high resolution? A constraint based on observed river discharge
dc.creator.none.fl_str_mv Müller, Omar Vicente
Vidale, Pier Luigi
Vannière, Benoît
Schiemann, Reinhard
McGuire, Patrick C.
author Müller, Omar Vicente
author_facet Müller, Omar Vicente
Vidale, Pier Luigi
Vannière, Benoît
Schiemann, Reinhard
McGuire, Patrick C.
author_role author
author2 Vidale, Pier Luigi
Vannière, Benoît
Schiemann, Reinhard
McGuire, Patrick C.
author2_role author
author
author
author
dc.subject.none.fl_str_mv GLOBAL CLIMATE MODELS
RESOLUTION
GLOBAL RIVER DISCHARGE
GLOBAL LAND PRECIPITATION
topic GLOBAL CLIMATE MODELS
RESOLUTION
GLOBAL RIVER DISCHARGE
GLOBAL LAND PRECIPITATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Previous studies showed that high-resolution GCMs overestimate land precipitation when compared against observation-based data. Particularly, high-resolution HadGEM3-GC3.1 shows a significant precipitation increase in mountainous regions, where the scarcity of gauge stations increases the uncertainty of gridded observations and reanalyses. This work evaluates such precipitation uncertainties indirectly through the assessment of river discharge, considering that an increase of ~10% in land precipitation produces ~28% more runoff when the resolution is enhanced from 1° to 0.25°, and ~50% of the global runoff is produced in 27% of global land dominated by mountains. We diagnosed the river flow by routing the runoff generated by HadGEM3-GC3.1 low- and high-resolution simulations. The river flow is evaluated using a set of 344 monitored catchments distributed around the world. We also infer the global discharge by constraining the simulations with observations following a novel approach that implies bias correction in monitored rivers with two methods, and extension of the correction to the river mouth, and along the coast. Our global discharge estimate is 47.4 ± 1.6 × 103 km3 yr−1, which is closer to the original high-resolution estimate (50.5 × 103 km3 yr−1) than to the low-resolution (39.6 × 103 km3 yr−1). The assessment suggests that high-resolution simulations perform better in mountainous regions, either because the better-defined orography favors the placement of precipitation in the correct catchment, leading to a more accurate distribution of runoff, or the orographic precipitation increases, reducing the dry runoff bias of coarse-resolution simulations. However, high-resolution slightly increases wet biases in catchments dominated by flat terrain. The improvement of model parameterizations and tuning may reduce the remaining errors in high-resolution simulations.
Fil: Müller, Omar Vicente. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingenieria y Ciencias Hidricas. Centro de Estudios de Variabilidad y Cambio Climatico.; Argentina. University Of Reading. Departament Of Meteorology; Reino Unido
Fil: Vidale, Pier Luigi. University Of Reading. Departament Of Meteorology; Reino Unido
Fil: Vannière, Benoît. University Of Reading. Departament Of Meteorology; Reino Unido
Fil: Schiemann, Reinhard. University Of Reading. Departament Of Meteorology; Reino Unido
Fil: McGuire, Patrick C.. University Of Reading. Departament Of Meteorology; Reino Unido
description Previous studies showed that high-resolution GCMs overestimate land precipitation when compared against observation-based data. Particularly, high-resolution HadGEM3-GC3.1 shows a significant precipitation increase in mountainous regions, where the scarcity of gauge stations increases the uncertainty of gridded observations and reanalyses. This work evaluates such precipitation uncertainties indirectly through the assessment of river discharge, considering that an increase of ~10% in land precipitation produces ~28% more runoff when the resolution is enhanced from 1° to 0.25°, and ~50% of the global runoff is produced in 27% of global land dominated by mountains. We diagnosed the river flow by routing the runoff generated by HadGEM3-GC3.1 low- and high-resolution simulations. The river flow is evaluated using a set of 344 monitored catchments distributed around the world. We also infer the global discharge by constraining the simulations with observations following a novel approach that implies bias correction in monitored rivers with two methods, and extension of the correction to the river mouth, and along the coast. Our global discharge estimate is 47.4 ± 1.6 × 103 km3 yr−1, which is closer to the original high-resolution estimate (50.5 × 103 km3 yr−1) than to the low-resolution (39.6 × 103 km3 yr−1). The assessment suggests that high-resolution simulations perform better in mountainous regions, either because the better-defined orography favors the placement of precipitation in the correct catchment, leading to a more accurate distribution of runoff, or the orographic precipitation increases, reducing the dry runoff bias of coarse-resolution simulations. However, high-resolution slightly increases wet biases in catchments dominated by flat terrain. The improvement of model parameterizations and tuning may reduce the remaining errors in high-resolution simulations.
publishDate 2021
dc.date.none.fl_str_mv 2021-06
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/11336/164943
Müller, Omar Vicente; Vidale, Pier Luigi; Vannière, Benoît; Schiemann, Reinhard; McGuire, Patrick C.; Does the HadGEM3-GC3.1 GCM overestimate land precipitation at high resolution? A constraint based on observed river discharge; American Meteorological Society; Journal of Hydrometeorology; 22; 8; 6-2021; 2131-2151
1525-755X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/164943
identifier_str_mv Müller, Omar Vicente; Vidale, Pier Luigi; Vannière, Benoît; Schiemann, Reinhard; McGuire, Patrick C.; Does the HadGEM3-GC3.1 GCM overestimate land precipitation at high resolution? A constraint based on observed river discharge; American Meteorological Society; Journal of Hydrometeorology; 22; 8; 6-2021; 2131-2151
1525-755X
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://journals.ametsoc.org/view/journals/hydr/aop/JHM-D-20-0290.1/JHM-D-20-0290.1.xml
info:eu-repo/semantics/altIdentifier/doi/10.1175/JHM-D-20-0290.1
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 American Meteorological Society
publisher.none.fl_str_mv American Meteorological Society
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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