Articles | Volume 24, issue 8
https://doi.org/10.5194/nhess-24-2793-2024
https://doi.org/10.5194/nhess-24-2793-2024
Research article
 | 
22 Aug 2024
Research article |  | 22 Aug 2024

Probabilistic short-range forecasts of high-precipitation events: optimal decision thresholds and predictability limits

François Bouttier and Hugo Marchal

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Cited articles

Addor, N., Jaun, S., Fundel, F., and Zappa, M.: An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios, Hydrol. Earth Syst. Sci., 15, 2327–2347, https://doi.org/10.5194/hess-15-2327-2011, 2011. a
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Amengual, A., Hermoso, A., Carrió, D. S., and Homar, V.: The sequence of heavy precipitation and flash flooding of 12 and 13 September 2019 in eastern Spain. Part II: A hydro-meteorological predictability analysis based on convection-permitting ensemble strategies, J. Hydrometeorol., 22, 2153–2177, https://doi.org/10.1175/jhm-d-20-0181.1, 2021. a, b
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Short summary
Weather prediction uncertainties can be described as sets of possible scenarios – a technique called ensemble prediction. Our machine learning technique translates them into more easily interpretable scenarios for various users, balancing the detection of high precipitation with false alarms. Key parameters are precipitation intensity and space and time scales of interest. We show that the approach can be used to facilitate warnings of extreme precipitation.
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