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

Cited 40 time in Web of Science Cited 37 time in Scopus
Authors

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.; Romero, Carmen González; 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

Issue Date
2022-06
Publisher
American Meteorological Society
Citation
Bulletin of the American Meteorological Society, Vol.103 No.6, pp.E1473-E1501
Abstract
© 2022 American Meteorological Society. All rights reserved.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.
ISSN
0003-0007
URI
https://hdl.handle.net/10371/205464
DOI
https://doi.org/10.1175/BAMS-D-20-0221.1
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  • College of Natural Sciences
  • Department of Earth and Environmental Sciences
Research Area Climate Change, Polar Environmental, Severe Weather, 극지환경, 기후과학, 위험기상

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