Advances in the subseasonal prediction of extreme events: relevant case studies across the globe
Extreme weather events have devastating impacts on human health, economic activities, ecosystems, and infrastructure. It is therefore crucial to anticipate extremes and their impacts to allow for preparedness and emergency measures. There is indeed potential for probabilistic subseasonal prediction...
| Autores: | , , , , , , , , |
|---|---|
| Formato: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/371614 |
| Acesso em linha: | https://hdl.handle.net/2117/371614 https://dx.doi.org/10.1175/BAMS-D-20-0221.1 |
| Access Level: | acceso abierto |
| Palavra-chave: | Extreme weather Climate change Heatwaves (Meteorology) Madden-Julian oscillation Severe storms Ensembles Forecast verification/skill Probability forecasts/models/distribution Flood events Simulació per ordinador Àrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia |
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oai:upcommons.upc.edu:2117/371614 |
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Advances in the subseasonal prediction of extreme events: relevant case studies across the globe Domeisen, Daniela I. V. White, Christopher J. Afargan Gerstman, Hilla Muñoz, Ángel G. Janiga, Matthew A. Lledó, Llorenç|||0000-0002-8628-6876 Manrique Suñén, Andrea Palma, Lluis Soret, Albert|||0000-0002-1962-2972 Extreme weather Climate change Heatwaves (Meteorology) Madden-Julian oscillation Severe storms Ensembles Forecast verification/skill Probability forecasts/models/distribution Flood events Simulació per ordinador Àrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia Extreme weather events have devastating impacts on human health, economic activities, ecosystems, and infrastructure. It is therefore crucial to anticipate extremes and their impacts to allow for preparedness and emergency measures. There is indeed potential for probabilistic subseasonal prediction on time scales of several weeks for many extreme events. Here we provide an overview of subseasonal predictability for case studies of some of the most prominent extreme events across the globe using the ECMWF S2S prediction system: heatwaves, cold spells, heavy precipitation events, and tropical and extratropical cyclones. The considered heatwaves exhibit predictability on time scales of 3–4 weeks, while this time scale is 2–3 weeks for cold spells. Precipitation extremes are the least predictable among the considered case studies. Tropical cyclones, on the other hand, can exhibit probabilistic predictability on time scales of up to 3 weeks, which in the presented cases was aided by remote precursors such as the Madden–Julian oscillation. For extratropical cyclones, lead times are found to be shorter. These case studies clearly illustrate the potential for event-dependent advance warnings for a wide range of extreme events. The subseasonal predictability of extreme events demonstrated here allows for an extension of warning horizons, provides advance information to impact modelers, and informs communities and stakeholders affected by the impacts of extreme weather events. Peer Reviewed "Article signat per 40 autors/es: Daniela I. V. Domeisen, Christopher J. White, Hilla Afargan-Gerstman, Ángel G. Muñoz, Matthew A. Janiga, Frédéric Vitart, C. Ole Wulff, Salomé Antoine, Constantin Ardilouze, Lauriane Batté, Hannah C. Bloomfield, David J. Brayshaw, Suzana J. Camargo, Andrew Charlton-Pérez, Dan Collins, Tim Cowan, Maria del Mar Chaves, Laura Ferranti, Rosario Gómez, Paula L. M. González, Carmen González Romero, Johnna M. Infanti, Stelios Karozis, Hera Kim, Erik W. Kolstad, Emerson LaJoie, Llorenç Lledó, Linus Magnusson, Piero Malguzzi, Andrea Manrique-Suñén, Daniele Mastrangelo, Stefano Materia, Hanoi Medina, Lluís Palma, Luis E. Pineda, Athanasios Sfetsos, Seok-Woo Son, Albert Soret, Sarah Strazzo, and Di Tian" American Meteorological Society https://hdl.handle.net/2117/371614 https://dx.doi.org/10.1175/BAMS-D-20-0221.1 |
| title |
Advances in the subseasonal prediction of extreme events: relevant case studies across the globe |
| spellingShingle |
Advances in the subseasonal prediction of extreme events: relevant case studies across the globe Domeisen, Daniela I. V. Extreme weather Climate change Heatwaves (Meteorology) Madden-Julian oscillation Severe storms Ensembles Forecast verification/skill Probability forecasts/models/distribution Flood events Simulació per ordinador Àrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia |
| title_short |
Advances in the subseasonal prediction of extreme events: relevant case studies across the globe |
| title_full |
Advances in the subseasonal prediction of extreme events: relevant case studies across the globe |
| title_fullStr |
Advances in the subseasonal prediction of extreme events: relevant case studies across the globe |
| title_full_unstemmed |
Advances in the subseasonal prediction of extreme events: relevant case studies across the globe |
| title_sort |
Advances in the subseasonal prediction of extreme events: relevant case studies across the globe |
| author |
Domeisen, Daniela I. V. |
| author_facet |
Domeisen, Daniela I. V. White, Christopher J. Afargan Gerstman, Hilla Muñoz, Ángel G. Janiga, Matthew A. Lledó, Llorenç|||0000-0002-8628-6876 Manrique Suñén, Andrea Palma, Lluis Soret, Albert|||0000-0002-1962-2972 |
| author_role |
author |
| author2 |
White, Christopher J. Afargan Gerstman, Hilla Muñoz, Ángel G. Janiga, Matthew A. Lledó, Llorenç|||0000-0002-8628-6876 Manrique Suñén, Andrea Palma, Lluis Soret, Albert|||0000-0002-1962-2972 |
| author2_role |
author author author author author author author author |
| topic |
Extreme weather Climate change Heatwaves (Meteorology) Madden-Julian oscillation Severe storms Ensembles Forecast verification/skill Probability forecasts/models/distribution Flood events Simulació per ordinador Àrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia |
| topic_facet |
Extreme weather Climate change Heatwaves (Meteorology) Madden-Julian oscillation Severe storms Ensembles Forecast verification/skill Probability forecasts/models/distribution Flood events Simulació per ordinador Àrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia |
| description |
Extreme weather events have devastating impacts on human health, economic activities, ecosystems, and infrastructure. It is therefore crucial to anticipate extremes and their impacts to allow for preparedness and emergency measures. There is indeed potential for probabilistic subseasonal prediction on time scales of several weeks for many extreme events. Here we provide an overview of subseasonal predictability for case studies of some of the most prominent extreme events across the globe using the ECMWF S2S prediction system: heatwaves, cold spells, heavy precipitation events, and tropical and extratropical cyclones. The considered heatwaves exhibit predictability on time scales of 3–4 weeks, while this time scale is 2–3 weeks for cold spells. Precipitation extremes are the least predictable among the considered case studies. Tropical cyclones, on the other hand, can exhibit probabilistic predictability on time scales of up to 3 weeks, which in the presented cases was aided by remote precursors such as the Madden–Julian oscillation. For extratropical cyclones, lead times are found to be shorter. These case studies clearly illustrate the potential for event-dependent advance warnings for a wide range of extreme events. The subseasonal predictability of extreme events demonstrated here allows for an extension of warning horizons, provides advance information to impact modelers, and informs communities and stakeholders affected by the impacts of extreme weather events. |
| publishDate |
2022 |
| format |
article |
| url |
https://hdl.handle.net/2117/371614 https://dx.doi.org/10.1175/BAMS-D-20-0221.1 |
| language |
eng |
| eu_rights_str_mv |
openAccess |
| publisher |
American Meteorological Society |
| institution |
Universitat Politècnica de Catalunya (UPC) |
| collection |
UPCommons. Portal del coneixement obert de la UPC |
| reponame_str |
UPCommons. Portal del coneixement obert de la UPC |
| instname_str |
Universitat Politècnica de Catalunya (UPC) |
| _version_ |
1878436904856190976 |
| publishDateSort |
2022 |
| author_browse |
Afargan Gerstman, Hilla Domeisen, Daniela I. V. Janiga, Matthew A. Lledó, Llorenç|||0000-0002-8628-6876 Manrique Suñén, Andrea Muñoz, Ángel G. Palma, Lluis Soret, Albert|||0000-0002-1962-2972 White, Christopher J. |
| publisherStr |
American Meteorological Society |
| score |
6,924472 |