Abstract 192

Abstract ID: 192

Subseasonal-to-seasonal prediction case studies: extreme events and applications

Lead Author: Christopher J. White
Department of Civil and Environmental Engineering, University of Strathclyde, United Kingdom

Keywords: subseasonal-to-seasonal , prediction, extreme events, applications

Abstract: Extreme weather events have devastating impacts on human health, economic activities, ecosystems, and infrastructure. It is crucial to anticipate extremes and their impacts on multiple forecasting timescales to allow for preparedness and emergency measures and activities. There is potential for skilful probabilistic subseasonal-to-seasonal (S2S) prediction on timescales of several weeks for many extreme events. Decisions in various sectors are made in this forecast timescale, therefore there is a strong demand for a new generation of extreme events predictions.

Drawing on two recent S2S community-led papers in the Bulletin of the American Meteorological Society (BAMS), we provide an overview of S2S predictability using case studies of some of the most prominent extreme events across the globe, and then present recent progress in the applications of S2S extreme event forecasts.

The extreme events case studies use the ECMWF S2S prediction system for heatwaves, cold spells, heavy precipitation events, and tropical and extratropical cyclones. We use the case studies to illustrate the potential for event-dependent advance warnings for a wide range of extreme events. We then show how S2S forecasts are allowing for an extension of warning horizons using examples of applications case studies. Through these case studies, we demonstrate that S2S forecasts do not produce a ‘go/no go’ answer of how a user should respond to a potential extreme event; instead they provide additional, supplementary ‘situational awareness’ information that can be used to support decision-making on S2S timescales, providing advance information to impact modelers and informing communities and stakeholders affected by the impacts of extreme weather events.

While S2S forecasting is still a maturing discipline globally, these publications mark a significant step forward in demonstrating predictability of extreme events using S2S forecasts, and of the community moving from potential to actual S2S forecasting applications – a collective body of evidence demonstrating both skill and utility that places user needs and applications at the forefront of S2S extreme events forecast development.

The two papers are both available from BAMS as open access publications: https://doi.org/10.1175/BAMS-D-20-0224.1 and https://doi.org/10.1175/BAMS-D-20-0221.1

Daniela I.V. Domeisen (University of Lausanne and ETH Zürich, Switzerland)