Developing an Automated Medium-Range Flood Awareness System for Switzerland Based on Probabilistic Forecasts of Integrated Water Vapor Fluxes

Mahlstein, Irina; Bhend, Jonas; Spirig, Christoph; Martius, Olivia (2019). Developing an Automated Medium-Range Flood Awareness System for Switzerland Based on Probabilistic Forecasts of Integrated Water Vapor Fluxes. Weather and Forecasting, 34(6), pp. 1759-1776. American Meteorological Society 10.1175/WAF-D-18-0189.1

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Floods in the Alpine region can be destructive and cause large economic losses. Many rivers and lakes in Switzerland are regulated and flood damage can be mitigated through an optimal management of lake levels and runoff. This requires high-quality forecasts of atmospheric flood precursors extending beyond short-range (forecast days 1–5) predictions. In several places around the world atmospheric rivers or extreme integrated vapor transport (IVT) are causally related to flood events. Also in Switzerland, extreme IVT oriented perpendicular to the main orography heralds extreme flood events. This relationship is exploited in an operational flood warning system on the medium-range (here forecast days 6–10) time scale based on probabilistic medium-range forecasts of IVT and precipitation over Switzerland provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). This entails first a comprehensive probabilistic verification of the direction and magnitude of (extreme) IVT and second the development of compact visualizations for the operational use by hydrologists. Based on 20 years of probabilistic reforecasts, we show that both regular and extreme IVT has a better predictability than precipitation and IVT is predictable out to day 8. As the direction of IVT is of central importance for flood risk in Switzerland, we develop a visualization that summarizes probabilistic information on both the direction and magnitude of the IVT together with users of the product. The result is an operational flood warning system based solely on atmospheric flood precursors to extend flood warning information beyond the range of high-resolution deterministic weather forecasts.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Institute of Geography
10 Strategic Research Centers > Oeschger Centre for Climate Change Research (OCCR)
08 Faculty of Science > Institute of Geography > Physical Geography > Unit Impact
08 Faculty of Science > Institute of Geography > Physical Geography

UniBE Contributor:

Mahlstein, Irina and Romppainen-Martius, Olivia

Subjects:

900 History > 910 Geography & travel
500 Science > 550 Earth sciences & geology

ISSN:

0882-8156

Publisher:

American Meteorological Society

Language:

English

Submitter:

Hélène Christine Louise Barras

Date Deposited:

13 Feb 2020 09:39

Last Modified:

13 Feb 2020 09:39

Publisher DOI:

10.1175/WAF-D-18-0189.1

Uncontrolled Keywords:

Ensembles; Forecast verification/skill

BORIS DOI:

10.7892/boris.138766

URI:

https://boris.unibe.ch/id/eprint/138766

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