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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/164943
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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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1842268923790098432 |
score |
13.13397 |