Multi-model skill assessment of seasonal temperature and precipitation forecasts over Europe

There is now a wide range of forecasts and observations of seasonal climatic conditions that can be used across a range of application sectors, including hydrological risk forecasting, planning and management. As we rely more on seasonal climate forecasts, it becomes essential to also assess its qua...

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Detalhes bibliográficos
Autores: Mishra, Niti, Prodhomme, Chloé, Guemas, Virginie
Tipo de documento: artigo
Data de publicação:2018
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositório:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglês
OAI Identifier:oai:upcommons.upc.edu:2117/122724
Acesso em linha:https://hdl.handle.net/2117/122724
https://dx.doi.org/10.1007/s00382-018-4404-z
Access Level:Acceso aberto
Palavra-chave:Seasonal prediction (Meteorology)
Seasonal climate forecast
Probability Ensemble Forecast
Weighted Multi-Model
Forecast Verification
Previsió del temps
Àrees temàtiques de la UPC::Energies
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spelling Multi-model skill assessment of seasonal temperature and precipitation forecasts over EuropeMishra, NitiProdhomme, ChloéGuemas, VirginieSeasonal prediction (Meteorology)Seasonal climate forecastProbability Ensemble ForecastWeighted Multi-ModelForecast VerificationPrevisió del tempsÀrees temàtiques de la UPC::EnergiesThere is now a wide range of forecasts and observations of seasonal climatic conditions that can be used across a range of application sectors, including hydrological risk forecasting, planning and management. As we rely more on seasonal climate forecasts, it becomes essential to also assess its quality to ensure its intended use. In this study, we provide the most comprehensive assessment of seasonal temperature and precipitation ensemble forecasts of the EUROSIP multi-model forecasting system over Europe. The forecasts from the four individual climate models within the EUROSIP are assessed using both deterministic and probabilistic approaches. One equally and two unequally Weighted Multi-Models (WMMs) are also constructed from the individual models, for both climate variables, and their respective forecasts are also assessed. Consistent with existing literature, we find limited seasonal climate prediction skill over Europe. A simple equally WMM system performs better than both unequally WMM combination systems. However, the equally WMM system does not always outperform the single best model within the EUROSIP multi-model. Based on the results, it is recommended to assess seasonal temperature and precipitation forecast of individual climate models as well as their multi-model mean for a comprehensive overview of the forecast skill.The authors thank Prof. Francisco J. Doblas Reyes, Alicia Sanchez Lorente, Veronica Torralba and Louis-Philippe Caron for discussions and suggestions during the forming of this paper. Thanks to Nicolau Manubens, whose incredible technical support allowed steady implementation of the experiments in this study. Thanks are also due to the anonymous reviewers and their critical reviews. Their comments and suggestions improved the content of this paper. The research leading to these results has received funding from the EU H2020 Framework Programme under grant agreement #641811 (IMPREX).Peer ReviewedSpringer Verlag20182018-08-3120182018-10-22journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/122724https://dx.doi.org/10.1007/s00382-018-4404-zreponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengEuropean Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 641811 IMproving PRedictions and management of hydrological EXtremesopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1227242026-05-27T15:37:01Z
dc.title.none.fl_str_mv Multi-model skill assessment of seasonal temperature and precipitation forecasts over Europe
title Multi-model skill assessment of seasonal temperature and precipitation forecasts over Europe
spellingShingle Multi-model skill assessment of seasonal temperature and precipitation forecasts over Europe
Mishra, Niti
Seasonal prediction (Meteorology)
Seasonal climate forecast
Probability Ensemble Forecast
Weighted Multi-Model
Forecast Verification
Previsió del temps
Àrees temàtiques de la UPC::Energies
title_short Multi-model skill assessment of seasonal temperature and precipitation forecasts over Europe
title_full Multi-model skill assessment of seasonal temperature and precipitation forecasts over Europe
title_fullStr Multi-model skill assessment of seasonal temperature and precipitation forecasts over Europe
title_full_unstemmed Multi-model skill assessment of seasonal temperature and precipitation forecasts over Europe
title_sort Multi-model skill assessment of seasonal temperature and precipitation forecasts over Europe
dc.creator.none.fl_str_mv Mishra, Niti
Prodhomme, Chloé
Guemas, Virginie
author Mishra, Niti
author_facet Mishra, Niti
Prodhomme, Chloé
Guemas, Virginie
author_role author
author2 Prodhomme, Chloé
Guemas, Virginie
author2_role author
author
dc.subject.none.fl_str_mv Seasonal prediction (Meteorology)
Seasonal climate forecast
Probability Ensemble Forecast
Weighted Multi-Model
Forecast Verification
Previsió del temps
Àrees temàtiques de la UPC::Energies
topic Seasonal prediction (Meteorology)
Seasonal climate forecast
Probability Ensemble Forecast
Weighted Multi-Model
Forecast Verification
Previsió del temps
Àrees temàtiques de la UPC::Energies
description There is now a wide range of forecasts and observations of seasonal climatic conditions that can be used across a range of application sectors, including hydrological risk forecasting, planning and management. As we rely more on seasonal climate forecasts, it becomes essential to also assess its quality to ensure its intended use. In this study, we provide the most comprehensive assessment of seasonal temperature and precipitation ensemble forecasts of the EUROSIP multi-model forecasting system over Europe. The forecasts from the four individual climate models within the EUROSIP are assessed using both deterministic and probabilistic approaches. One equally and two unequally Weighted Multi-Models (WMMs) are also constructed from the individual models, for both climate variables, and their respective forecasts are also assessed. Consistent with existing literature, we find limited seasonal climate prediction skill over Europe. A simple equally WMM system performs better than both unequally WMM combination systems. However, the equally WMM system does not always outperform the single best model within the EUROSIP multi-model. Based on the results, it is recommended to assess seasonal temperature and precipitation forecast of individual climate models as well as their multi-model mean for a comprehensive overview of the forecast skill.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-08-31
2018
2018-10-22
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/122724
https://dx.doi.org/10.1007/s00382-018-4404-z
url https://hdl.handle.net/2117/122724
https://dx.doi.org/10.1007/s00382-018-4404-z
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 641811 IMproving PRedictions and management of hydrological EXtremes
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
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
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer Verlag
publisher.none.fl_str_mv Springer Verlag
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301629

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