Do CMIP models capture long-term observed annual precipitation trends?

This study provides a long-term (1891-2014) global assessment of precipitation trends using data from two station-based gridded datasets and climate model outputs evolved through the fifth and sixth phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively). Our analysis emp...

Descripción completa

Detalles Bibliográficos
Autores: Vicente Serrano, S.M., García Herrera, Ricardo Francisco, Peña Angulo, D., Tomas‑Burguera, M., Domínguez Castro, F., Noguera, I., Calvo Fernández, Natalia, Murphy, C., Nieto, R., Gimeno, L., Gutiérrez, J.M., Azorín Molina, César, El Kenawy, A.
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/4906
Acceso en línea:https://hdl.handle.net/20.500.14352/4906
Access Level:acceso abierto
Palabra clave:52
Global climate models
Low-top versions
Simulations
20th-century
Temperature
Variability
Stratosphere
Enso
Atmosphere
Extremes
Astrofísica
id ES_9eeb9518edc2092d1f64d6fbb5eca1d4
oai_identifier_str oai:docta.ucm.es:20.500.14352/4906
network_acronym_str ES
network_name_str España
repository_id_str
spelling Do CMIP models capture long-term observed annual precipitation trends?Vicente Serrano, S.M.García Herrera, Ricardo FranciscoPeña Angulo, D.Tomas‑Burguera, M.Domínguez Castro, F.Noguera, I.Calvo Fernández, NataliaMurphy, C.Nieto, R.Gimeno, L.Gutiérrez, J.M.Azorín Molina, CésarEl Kenawy, A.52Global climate modelsLow-top versionsSimulations20th-centuryTemperatureVariabilityStratosphereEnsoAtmosphereExtremesAstrofísicaThis study provides a long-term (1891-2014) global assessment of precipitation trends using data from two station-based gridded datasets and climate model outputs evolved through the fifth and sixth phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively). Our analysis employs a variety of modeling groups that incorporate low- and high-top level members, with the aim of assessing the possible effects of including a well-resolved stratosphere on the model's ability to reproduce long-term observed annual precipitation trends. Results demonstrate that only a few regions show statistically significant differences in precipitation trends between observations and models. Nevertheless, this pattern is mostly caused by the strong interannual variability of precipitation in most of the world regions. Thus, statistically significant model-observation differences on trends (1891-2014) are found at the zonal mean scale. The different model groups clearly fail to reproduce the spatial patterns of annual precipitation trends and the regions where stronger increases or decreases are recorded. This study also stresses that there are no significant differences between low- and high-top models in capturing observed precipitation trends, indicating that having a well-resolved stratosphere has a low impact on the accuracy of precipitation projections.SpringerUniversidad Complutense de Madrid20212021-11-0620212021-11-06journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.14352/4906reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Atribución 3.0 Españahttps://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/49062026-06-02T12:44:21Z
dc.title.none.fl_str_mv Do CMIP models capture long-term observed annual precipitation trends?
title Do CMIP models capture long-term observed annual precipitation trends?
spellingShingle Do CMIP models capture long-term observed annual precipitation trends?
Vicente Serrano, S.M.
52
Global climate models
Low-top versions
Simulations
20th-century
Temperature
Variability
Stratosphere
Enso
Atmosphere
Extremes
Astrofísica
title_short Do CMIP models capture long-term observed annual precipitation trends?
title_full Do CMIP models capture long-term observed annual precipitation trends?
title_fullStr Do CMIP models capture long-term observed annual precipitation trends?
title_full_unstemmed Do CMIP models capture long-term observed annual precipitation trends?
title_sort Do CMIP models capture long-term observed annual precipitation trends?
dc.creator.none.fl_str_mv Vicente Serrano, S.M.
García Herrera, Ricardo Francisco
Peña Angulo, D.
Tomas‑Burguera, M.
Domínguez Castro, F.
Noguera, I.
Calvo Fernández, Natalia
Murphy, C.
Nieto, R.
Gimeno, L.
Gutiérrez, J.M.
Azorín Molina, César
El Kenawy, A.
author Vicente Serrano, S.M.
author_facet Vicente Serrano, S.M.
García Herrera, Ricardo Francisco
Peña Angulo, D.
Tomas‑Burguera, M.
Domínguez Castro, F.
Noguera, I.
Calvo Fernández, Natalia
Murphy, C.
Nieto, R.
Gimeno, L.
Gutiérrez, J.M.
Azorín Molina, César
El Kenawy, A.
author_role author
author2 García Herrera, Ricardo Francisco
Peña Angulo, D.
Tomas‑Burguera, M.
Domínguez Castro, F.
Noguera, I.
Calvo Fernández, Natalia
Murphy, C.
Nieto, R.
Gimeno, L.
Gutiérrez, J.M.
Azorín Molina, César
El Kenawy, A.
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv 52
Global climate models
Low-top versions
Simulations
20th-century
Temperature
Variability
Stratosphere
Enso
Atmosphere
Extremes
Astrofísica
topic 52
Global climate models
Low-top versions
Simulations
20th-century
Temperature
Variability
Stratosphere
Enso
Atmosphere
Extremes
Astrofísica
description This study provides a long-term (1891-2014) global assessment of precipitation trends using data from two station-based gridded datasets and climate model outputs evolved through the fifth and sixth phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively). Our analysis employs a variety of modeling groups that incorporate low- and high-top level members, with the aim of assessing the possible effects of including a well-resolved stratosphere on the model's ability to reproduce long-term observed annual precipitation trends. Results demonstrate that only a few regions show statistically significant differences in precipitation trends between observations and models. Nevertheless, this pattern is mostly caused by the strong interannual variability of precipitation in most of the world regions. Thus, statistically significant model-observation differences on trends (1891-2014) are found at the zonal mean scale. The different model groups clearly fail to reproduce the spatial patterns of annual precipitation trends and the regions where stronger increases or decreases are recorded. This study also stresses that there are no significant differences between low- and high-top models in capturing observed precipitation trends, indicating that having a well-resolved stratosphere has a low impact on the accuracy of precipitation projections.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-11-06
2021
2021-11-06
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/4906
url https://hdl.handle.net/20.500.14352/4906
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución 3.0 España
https://creativecommons.org/licenses/by/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución 3.0 España
https://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869414866672943104
score 15,300719

Similares en LA Referencia