Advances in the subseasonal prediction of extreme events: Relevant case studies across the globe

Daniela I.V. Domeisen , Christopher White , Hilla Afargan-Gerstman , Ángel Muñoz , Matthew Janiga , Frédéric Vitart , C. Ole Wulf , Salomé Antoine (1) , Constantin Ardilouze (1) , Lauriane Saunier Batté (1) , Hannah Bloomfield , David Brayshaw , Suzana Camargo , Andrew Charlton-Pérez , Dan Collins , Tim Cowan , Maria del Mar Chaves , Laura Ferranti , Rosario Gómez , Paula L.M. González , Carmen González Romero , Johnna Infanti , Stelios Karozis , Hera Kim , Erik Kolstad , Emerson Lajoie , Llorenç Lledó , Linus Magnusson , Piero Malguzzi , Andrea Manrique-Suñén , Daniele Mastrangelo , Stefano Materia , Hanoi Medina , Lluís Palma , Luis Pineda , Athanasios Sfetsos , Seok-Woo Son , Albert Soret , Sarah Strazzo , Di Tian

1 CNRM - Centre national de recherches météorologiques

Extreme weather events have devastating impacts on human health, economic activities, ecosys tems, 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 timescales 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 timescales of 3-4 weeks, while this timescale 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 timescales 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.

Domaines: Météorologie; Océan, Atmosphère

Daniela I.V. Domeisen, Christopher White, Hilla Afargan-Gerstman, Ángel Muñoz, Matthew Janiga, et al.. Advances in the subseasonal prediction of extreme events: Relevant case studies across the globe. Bulletin of the American Meteorological Society, 2022, ⟨10.1175/BAMS-D-20-0221.1⟩. ⟨hal-03601088⟩