Advances in the Subseasonal Prediction of Extreme Events

Domeisen, Daniela I. V. and White, Christopher J. and Afargan-Gerstman, Hilla and Munoz, Angel G. and Janiga, Matthew A. and Vitart, Frederic and Wulff, C. Ole and Antoine, Salome and Ardilouze, Constantin and Batte, Lauriane and Bloomfield, Hannah C. and Brayshaw, David J. and Camargo, Suzana J. and Charlton-Perez, Andrew and Collins, Dan and Cowan, Tim and del Mar Chaves, Maria and Ferranti, Laura and Gomez, Rosario and Gonzalez, Paula L. M. and Gonzalez Romero, Carmen and Infanti, Johnna M. and Karozis, Stelios and Kim, Hera and Kolstad, Erik W. and LaJoie, Emerson and Lledo, Llorenc and Magnusson, Linus and Malguzzi, Piero and Manrique-Sunen, Andrea and Mastrangelo, Daniele and Materia, Stefano and Medina, Hanoi and Palma, Lluis and Pineda, Luis E. and Sfetsos, Athanasios and Son, Seok-Woo and Soret, Albert and Strazzo, Sarah and Tian, Di (2022) Advances in the Subseasonal Prediction of Extreme Events. Bulletin of the American Meteorological Society, 103 (6). E1473-E1501. ISSN 0003-0007


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 proba-bilistic 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.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Files associated with this item cannot be displayed due to copyright restrictions.
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment - Centre for Applied Climate Sciences (1 Aug 2018 -)
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment - Centre for Applied Climate Sciences (1 Aug 2018 -)
Date Deposited: 27 Jun 2022 03:47
Last Modified: 02 Nov 2022 04:51
Uncontrolled Keywords: Madden-Julian oscillation; Severe storms; Ensembles; Forecast verification/skill; Probability; Forecasts/models/distribution; Flood event
Fields of Research (2020): 37 EARTH SCIENCES > 3701 Atmospheric sciences > 370101 Adverse weather events
37 EARTH SCIENCES > 3702 Climate change science > 370201 Climate change processes
37 EARTH SCIENCES > 3709 Physical geography and environmental geoscience > 370903 Natural hazards
37 EARTH SCIENCES > 3701 Atmospheric sciences > 370105 Atmospheric dynamics
37 EARTH SCIENCES > 3701 Atmospheric sciences > 370108 Meteorology
Socio-Economic Objectives (2020): 19 ENVIRONMENTAL POLICY, CLIMATE CHANGE AND NATURAL HAZARDS > 1904 Natural hazards > 190404 Hydrological hazards (e.g. avalanches and floods)
18 ENVIRONMENTAL MANAGEMENT > 1801 Air quality, atmosphere and weather > 180103 Atmospheric processes and dynamics
19 ENVIRONMENTAL POLICY, CLIMATE CHANGE AND NATURAL HAZARDS > 1904 Natural hazards > 190405 Meteorological hazards (e.g. cyclones and storms)
18 ENVIRONMENTAL MANAGEMENT > 1801 Air quality, atmosphere and weather > 180104 Weather
Identification Number or DOI: https://doi.org/10.1175/BAMS-D-20-0221.1
URI: http://eprints.usq.edu.au/id/eprint/49363

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