Multi-model assessment of sub-seasonal predictive skill for year-round Atlantic–European weather regimes

Autores
Osman, Marisol; Beerli, Remo; Büeler, Dominik; Grams, Christian M.
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The prediction skill of sub-seasonal forecast models is evaluated for seven year-round weather regimes in the Atlantic–European region. Reforecasts based on models from three prediction centers are considered and verified against weather regimes obtained from ERA-Interim reanalysis. Results show that predicting weather regimes as a proxy for the large-scale circulation outperforms the prediction of raw geopotential height. Greenland blocking tends to have the longest year-round skill horizon for all three models, especially in winter. On the other hand, the skill is lowest for the European blocking regime for all three models, followed by the Scandinavian blocking regime. Furthermore, all models struggle to forecast flow situations that cannot be assigned to a weather regime (so-called no regime), in comparison with weather regimes. Related to this, variability in the occurrence of no regime, which is most frequent in the transition seasons, partly explains the predictability gap between transition seasons and winter and summer. We also show that models have difficulties in discriminating between related regimes. This can lead to misassignments in the predicted regime during flow situations in which related regimes manifest. Finally, we document the changes in skill between model versions, showing important improvements for the ECMWF and NCEP models. This study is the first multi-model assessment of year-round weather regimes in the Atlantic–European domain. It advances our understanding of the predictive skill for weather regimes, reveals strengths and weaknesses of each model, and thus increases our confidence in the forecasts and their usefulness for decision-making.
Fil: Osman, Marisol. Karlsruhe Institute of Technology; Alemania. 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
Fil: Beerli, Remo. No especifíca;
Fil: Büeler, Dominik. Institute for Atmospheric and Climate Science; Suiza
Fil: Grams, Christian M.. Karlsruhe Institute of Technology; Alemania
Materia
BLOCKING
EUROPE
NORTH ATLANTIC OSCILLATION
WINDOWS OF OPPORTUNITY
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:11336/237117

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network_name_str CONICET Digital (CONICET)
spelling Multi-model assessment of sub-seasonal predictive skill for year-round Atlantic–European weather regimesOsman, MarisolBeerli, RemoBüeler, DominikGrams, Christian M.BLOCKINGEUROPENORTH ATLANTIC OSCILLATIONWINDOWS OF OPPORTUNITYhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1The prediction skill of sub-seasonal forecast models is evaluated for seven year-round weather regimes in the Atlantic–European region. Reforecasts based on models from three prediction centers are considered and verified against weather regimes obtained from ERA-Interim reanalysis. Results show that predicting weather regimes as a proxy for the large-scale circulation outperforms the prediction of raw geopotential height. Greenland blocking tends to have the longest year-round skill horizon for all three models, especially in winter. On the other hand, the skill is lowest for the European blocking regime for all three models, followed by the Scandinavian blocking regime. Furthermore, all models struggle to forecast flow situations that cannot be assigned to a weather regime (so-called no regime), in comparison with weather regimes. Related to this, variability in the occurrence of no regime, which is most frequent in the transition seasons, partly explains the predictability gap between transition seasons and winter and summer. We also show that models have difficulties in discriminating between related regimes. This can lead to misassignments in the predicted regime during flow situations in which related regimes manifest. Finally, we document the changes in skill between model versions, showing important improvements for the ECMWF and NCEP models. This study is the first multi-model assessment of year-round weather regimes in the Atlantic–European domain. It advances our understanding of the predictive skill for weather regimes, reveals strengths and weaknesses of each model, and thus increases our confidence in the forecasts and their usefulness for decision-making.Fil: Osman, Marisol. Karlsruhe Institute of Technology; Alemania. 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; ArgentinaFil: Beerli, Remo. No especifíca;Fil: Büeler, Dominik. Institute for Atmospheric and Climate Science; SuizaFil: Grams, Christian M.. Karlsruhe Institute of Technology; AlemaniaJohn Wiley & Sons Ltd2023-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/237117Osman, Marisol; Beerli, Remo; Büeler, Dominik; Grams, Christian M.; Multi-model assessment of sub-seasonal predictive skill for year-round Atlantic–European weather regimes; John Wiley & Sons Ltd; Quarterly Journal of the Royal Meteorological Society; 149; 755; 7-2023; 2386-24080035-9009CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1002/qj.4512info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:17:55Zoai:ri.conicet.gov.ar:11336/237117instacron: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 10:17:55.373CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Multi-model assessment of sub-seasonal predictive skill for year-round Atlantic–European weather regimes
title Multi-model assessment of sub-seasonal predictive skill for year-round Atlantic–European weather regimes
spellingShingle Multi-model assessment of sub-seasonal predictive skill for year-round Atlantic–European weather regimes
Osman, Marisol
BLOCKING
EUROPE
NORTH ATLANTIC OSCILLATION
WINDOWS OF OPPORTUNITY
title_short Multi-model assessment of sub-seasonal predictive skill for year-round Atlantic–European weather regimes
title_full Multi-model assessment of sub-seasonal predictive skill for year-round Atlantic–European weather regimes
title_fullStr Multi-model assessment of sub-seasonal predictive skill for year-round Atlantic–European weather regimes
title_full_unstemmed Multi-model assessment of sub-seasonal predictive skill for year-round Atlantic–European weather regimes
title_sort Multi-model assessment of sub-seasonal predictive skill for year-round Atlantic–European weather regimes
dc.creator.none.fl_str_mv Osman, Marisol
Beerli, Remo
Büeler, Dominik
Grams, Christian M.
author Osman, Marisol
author_facet Osman, Marisol
Beerli, Remo
Büeler, Dominik
Grams, Christian M.
author_role author
author2 Beerli, Remo
Büeler, Dominik
Grams, Christian M.
author2_role author
author
author
dc.subject.none.fl_str_mv BLOCKING
EUROPE
NORTH ATLANTIC OSCILLATION
WINDOWS OF OPPORTUNITY
topic BLOCKING
EUROPE
NORTH ATLANTIC OSCILLATION
WINDOWS OF OPPORTUNITY
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The prediction skill of sub-seasonal forecast models is evaluated for seven year-round weather regimes in the Atlantic–European region. Reforecasts based on models from three prediction centers are considered and verified against weather regimes obtained from ERA-Interim reanalysis. Results show that predicting weather regimes as a proxy for the large-scale circulation outperforms the prediction of raw geopotential height. Greenland blocking tends to have the longest year-round skill horizon for all three models, especially in winter. On the other hand, the skill is lowest for the European blocking regime for all three models, followed by the Scandinavian blocking regime. Furthermore, all models struggle to forecast flow situations that cannot be assigned to a weather regime (so-called no regime), in comparison with weather regimes. Related to this, variability in the occurrence of no regime, which is most frequent in the transition seasons, partly explains the predictability gap between transition seasons and winter and summer. We also show that models have difficulties in discriminating between related regimes. This can lead to misassignments in the predicted regime during flow situations in which related regimes manifest. Finally, we document the changes in skill between model versions, showing important improvements for the ECMWF and NCEP models. This study is the first multi-model assessment of year-round weather regimes in the Atlantic–European domain. It advances our understanding of the predictive skill for weather regimes, reveals strengths and weaknesses of each model, and thus increases our confidence in the forecasts and their usefulness for decision-making.
Fil: Osman, Marisol. Karlsruhe Institute of Technology; Alemania. 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
Fil: Beerli, Remo. No especifíca;
Fil: Büeler, Dominik. Institute for Atmospheric and Climate Science; Suiza
Fil: Grams, Christian M.. Karlsruhe Institute of Technology; Alemania
description The prediction skill of sub-seasonal forecast models is evaluated for seven year-round weather regimes in the Atlantic–European region. Reforecasts based on models from three prediction centers are considered and verified against weather regimes obtained from ERA-Interim reanalysis. Results show that predicting weather regimes as a proxy for the large-scale circulation outperforms the prediction of raw geopotential height. Greenland blocking tends to have the longest year-round skill horizon for all three models, especially in winter. On the other hand, the skill is lowest for the European blocking regime for all three models, followed by the Scandinavian blocking regime. Furthermore, all models struggle to forecast flow situations that cannot be assigned to a weather regime (so-called no regime), in comparison with weather regimes. Related to this, variability in the occurrence of no regime, which is most frequent in the transition seasons, partly explains the predictability gap between transition seasons and winter and summer. We also show that models have difficulties in discriminating between related regimes. This can lead to misassignments in the predicted regime during flow situations in which related regimes manifest. Finally, we document the changes in skill between model versions, showing important improvements for the ECMWF and NCEP models. This study is the first multi-model assessment of year-round weather regimes in the Atlantic–European domain. It advances our understanding of the predictive skill for weather regimes, reveals strengths and weaknesses of each model, and thus increases our confidence in the forecasts and their usefulness for decision-making.
publishDate 2023
dc.date.none.fl_str_mv 2023-07
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/11336/237117
Osman, Marisol; Beerli, Remo; Büeler, Dominik; Grams, Christian M.; Multi-model assessment of sub-seasonal predictive skill for year-round Atlantic–European weather regimes; John Wiley & Sons Ltd; Quarterly Journal of the Royal Meteorological Society; 149; 755; 7-2023; 2386-2408
0035-9009
CONICET Digital
CONICET
url http://hdl.handle.net/11336/237117
identifier_str_mv Osman, Marisol; Beerli, Remo; Büeler, Dominik; Grams, Christian M.; Multi-model assessment of sub-seasonal predictive skill for year-round Atlantic–European weather regimes; John Wiley & Sons Ltd; Quarterly Journal of the Royal Meteorological Society; 149; 755; 7-2023; 2386-2408
0035-9009
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1002/qj.4512
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 John Wiley & Sons Ltd
publisher.none.fl_str_mv John Wiley & Sons Ltd
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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