Improving Arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the European project APPLICATE
The Arctic environment is changing, increasing the vulnerability of local communities and ecosystems, and impacting its socio-economic landscape. In this context, weather and climate prediction systems can be powerful tools to support strategic planning and decision-making at different time horizons...
Published in: | Bulletin of the American Meteorological Society |
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ftupcatalunyair:oai:upcommons.upc.edu:2117/373606 2024-09-15T17:50:36+00:00 Improving Arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the European project APPLICATE Ortega Montilla, Pablo Blockley, Edward W. Køltzow, Morten Massonnet, François Sandu, Irina Svensson, Gunilla Acosta Navarro, Juan Camilo Cruz García, Rubén Moreno Chamarro, Eduardo Pérez Montero, Sergio Universitat Politècnica de Catalunya. Departament de Física Barcelona Supercomputing Center 2022-10 11 p. application/pdf http://hdl.handle.net/2117/373606 https://doi.org/10.1175/BAMS-D-22-0083.1 eng eng https://journals.ametsoc.org/view/journals/bams/aop/BAMS-D-22-0083.1/BAMS-D-22-0083.1.xml info:eu-repo/grantAgreement/EC/H2020/727862/EU/Advanced Prediction in Polar regions and beyond: Modelling, observing system design and LInkages associated with ArctiC ClimATE change/APPLICATE Ortega Montilla, P. [et al.]. Improving Arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the European project APPLICATE. "Bulletin of the American Meteorological Society", Octubre 2022, vol. 103, núm. 10, p. E2203-E2213. 0003-0007 http://hdl.handle.net/2117/373606 doi:10.1175/BAMS-D-22-0083.1 Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ Open Access Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Enginyeria ambiental Climatology -- Forecasting Climatology -- Mathematical models Arctic weather Weather prediction Climate prediction H2020 project APPLICATE Climatologia -- Previsió Climatologia -- Models matemàtics Article 2022 ftupcatalunyair https://doi.org/10.1175/BAMS-D-22-0083.1 2024-07-25T10:54:53Z The Arctic environment is changing, increasing the vulnerability of local communities and ecosystems, and impacting its socio-economic landscape. In this context, weather and climate prediction systems can be powerful tools to support strategic planning and decision-making at different time horizons. This article presents several success stories from the H2020 project APPLICATE on how to advance Arctic weather and seasonal climate prediction, synthesizing the key lessons learned throughout the project and providing recommendations for future model and forecast system development. The results discussed in this article were supported by the project APPLICATE (727862), funded by the European Union's Horizon 2020 research and innovation programme. PO was additionally supported by the Spanish fellowship RYC-2017-22772. Peer Reviewed Article signat per 29 autors/es: Pablo Ortega (1), Edward W. Blockley (2), Morten Køltzow (3), François Massonnet (4), Irina Sandu (5), Gunilla Svensson (6), Juan C. Acosta Navarro (1), Gabriele Arduini (5), Lauriane Batté (7), Eric Bazile (7), Matthieu Chevallier (8), Rubén Cruz-García (1), Jonathan J. Day (5), Thierry Fichefet (4), Daniela Flocco (9), Mukesh Gupta (4), Kerstin Hartung (6,10), Ed Hawkins (9), Claudia Hinrichs (11), Linus Magnusson (5), Eduardo Moreno-Chamarro (1), Sergio Pérez-Montero (1), Leandro Ponsoni (4), Tido Semmler (11), Doug Smith (2), Jean Sterlin (4), Michael Tjernström (6), Ilona Välisuo (7,12), and Thomas Jung (11,13) // (1) Barcelona Supercomputing Center, Barcelona, Spain | (2) Met Office, Exeter, UK | (3) Norwegian Meteorological Institute, Oslo, Norway | (4) Université catholique de Louvain, Earth and Life Institute, Georges Lemaître Centre for Earth and Climate Research, Louvain-la-Neuve, Belgium | (5) European Centre for Medium-Range Weather Forecasts, Reading, UK | (6) Department of Meteorology, Stockholm University, Stockholm, Sweden | (7) CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France | (8) Météo-France, Toulouse, France | ... Article in Journal/Newspaper Arctic Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledge Bulletin of the American Meteorological Society |
institution |
Open Polar |
collection |
Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledge |
op_collection_id |
ftupcatalunyair |
language |
English |
topic |
Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Enginyeria ambiental Climatology -- Forecasting Climatology -- Mathematical models Arctic weather Weather prediction Climate prediction H2020 project APPLICATE Climatologia -- Previsió Climatologia -- Models matemàtics |
spellingShingle |
Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Enginyeria ambiental Climatology -- Forecasting Climatology -- Mathematical models Arctic weather Weather prediction Climate prediction H2020 project APPLICATE Climatologia -- Previsió Climatologia -- Models matemàtics Ortega Montilla, Pablo Blockley, Edward W. Køltzow, Morten Massonnet, François Sandu, Irina Svensson, Gunilla Acosta Navarro, Juan Camilo Cruz García, Rubén Moreno Chamarro, Eduardo Pérez Montero, Sergio Improving Arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the European project APPLICATE |
topic_facet |
Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Enginyeria ambiental Climatology -- Forecasting Climatology -- Mathematical models Arctic weather Weather prediction Climate prediction H2020 project APPLICATE Climatologia -- Previsió Climatologia -- Models matemàtics |
description |
The Arctic environment is changing, increasing the vulnerability of local communities and ecosystems, and impacting its socio-economic landscape. In this context, weather and climate prediction systems can be powerful tools to support strategic planning and decision-making at different time horizons. This article presents several success stories from the H2020 project APPLICATE on how to advance Arctic weather and seasonal climate prediction, synthesizing the key lessons learned throughout the project and providing recommendations for future model and forecast system development. The results discussed in this article were supported by the project APPLICATE (727862), funded by the European Union's Horizon 2020 research and innovation programme. PO was additionally supported by the Spanish fellowship RYC-2017-22772. Peer Reviewed Article signat per 29 autors/es: Pablo Ortega (1), Edward W. Blockley (2), Morten Køltzow (3), François Massonnet (4), Irina Sandu (5), Gunilla Svensson (6), Juan C. Acosta Navarro (1), Gabriele Arduini (5), Lauriane Batté (7), Eric Bazile (7), Matthieu Chevallier (8), Rubén Cruz-García (1), Jonathan J. Day (5), Thierry Fichefet (4), Daniela Flocco (9), Mukesh Gupta (4), Kerstin Hartung (6,10), Ed Hawkins (9), Claudia Hinrichs (11), Linus Magnusson (5), Eduardo Moreno-Chamarro (1), Sergio Pérez-Montero (1), Leandro Ponsoni (4), Tido Semmler (11), Doug Smith (2), Jean Sterlin (4), Michael Tjernström (6), Ilona Välisuo (7,12), and Thomas Jung (11,13) // (1) Barcelona Supercomputing Center, Barcelona, Spain | (2) Met Office, Exeter, UK | (3) Norwegian Meteorological Institute, Oslo, Norway | (4) Université catholique de Louvain, Earth and Life Institute, Georges Lemaître Centre for Earth and Climate Research, Louvain-la-Neuve, Belgium | (5) European Centre for Medium-Range Weather Forecasts, Reading, UK | (6) Department of Meteorology, Stockholm University, Stockholm, Sweden | (7) CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France | (8) Météo-France, Toulouse, France | ... |
author2 |
Universitat Politècnica de Catalunya. Departament de Física Barcelona Supercomputing Center |
format |
Article in Journal/Newspaper |
author |
Ortega Montilla, Pablo Blockley, Edward W. Køltzow, Morten Massonnet, François Sandu, Irina Svensson, Gunilla Acosta Navarro, Juan Camilo Cruz García, Rubén Moreno Chamarro, Eduardo Pérez Montero, Sergio |
author_facet |
Ortega Montilla, Pablo Blockley, Edward W. Køltzow, Morten Massonnet, François Sandu, Irina Svensson, Gunilla Acosta Navarro, Juan Camilo Cruz García, Rubén Moreno Chamarro, Eduardo Pérez Montero, Sergio |
author_sort |
Ortega Montilla, Pablo |
title |
Improving Arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the European project APPLICATE |
title_short |
Improving Arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the European project APPLICATE |
title_full |
Improving Arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the European project APPLICATE |
title_fullStr |
Improving Arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the European project APPLICATE |
title_full_unstemmed |
Improving Arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the European project APPLICATE |
title_sort |
improving arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the european project applicate |
publishDate |
2022 |
url |
http://hdl.handle.net/2117/373606 https://doi.org/10.1175/BAMS-D-22-0083.1 |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
https://journals.ametsoc.org/view/journals/bams/aop/BAMS-D-22-0083.1/BAMS-D-22-0083.1.xml info:eu-repo/grantAgreement/EC/H2020/727862/EU/Advanced Prediction in Polar regions and beyond: Modelling, observing system design and LInkages associated with ArctiC ClimATE change/APPLICATE Ortega Montilla, P. [et al.]. Improving Arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the European project APPLICATE. "Bulletin of the American Meteorological Society", Octubre 2022, vol. 103, núm. 10, p. E2203-E2213. 0003-0007 http://hdl.handle.net/2117/373606 doi:10.1175/BAMS-D-22-0083.1 |
op_rights |
Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ Open Access |
op_doi |
https://doi.org/10.1175/BAMS-D-22-0083.1 |
container_title |
Bulletin of the American Meteorological Society |
_version_ |
1810292413619503104 |