Advances in the Subseasonal Prediction of Extreme Events: Relevant Case Studies across the Globe

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Version: Final published version
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Serval ID
serval:BIB_7B0EB2716AEE
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Advances in the Subseasonal Prediction of Extreme Events: Relevant Case Studies across the Globe
Journal
Bulletin of the American Meteorological Society
Author(s)
Domeisen Daniela I. V., White Christopher J., Afargan-Gerstman Hilla, Muñoz Ángel G., Janiga Matthew A., Vitart Frédéric, Wulff C. Ole, Antoine Salomé, Ardilouze Constantin, Batté Lauriane, Bloomfield Hannah C., Brayshaw David J., Camargo Suzana J., Charlton-Pérez Andrew, Collins Dan, Cowan Tim, del Mar Chaves Maria, Ferranti Laura, Gómez Rosario, González Paula L. M., González Romero Carmen, Infanti Johnna M., Karozis Stelios, Kim Hera, Kolstad Erik W., LaJoie Emerson, Lledó Llorenç, Magnusson Linus, Malguzzi Piero, Manrique-Suñén Andrea, Mastrangelo Daniele, Materia Stefano, Medina Hanoi, Palma Lluís, Pineda Luis E., Sfetsos Athanasios, Son Seok-Woo, Soret Albert, Strazzo Sarah, Tian Di
ISSN
0003-0007
1520-0477
Publication state
Published
Issued date
06/2022
Peer-reviewed
Oui
Volume
103
Number
6
Pages
E1473-E1501
Language
english
Abstract
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.
Keywords
Atmospheric Science
Web of science
Create date
07/10/2022 17:21
Last modification date
20/01/2023 6:53
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