Bridging the gap between ensemble forecasting and end-user needs for decision-making on high-impact events
Matteo Ponzano
CORRESPONDING AUTHOR
Department of Meteorological Services, Météo-France, 42 avenue Gaspard Coriolis, 31057 Toulouse CEDEX 1, France
Bruno Joly
Department of Meteorological Services, Météo-France, 42 avenue Gaspard Coriolis, 31057 Toulouse CEDEX 1, France
Isabelle Beau
Department of Meteorological Services, Météo-France, 42 avenue Gaspard Coriolis, 31057 Toulouse CEDEX 1, France
Elvis Renard
Department of Meteorological Services, Météo-France, 42 avenue Gaspard Coriolis, 31057 Toulouse CEDEX 1, France
Gregory Fifre
Department of Meteorological Services, Météo-France, 42 avenue Gaspard Coriolis, 31057 Toulouse CEDEX 1, France
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Nat. Hazards Earth Syst. Sci., 20, 1369–1389, https://doi.org/10.5194/nhess-20-1369-2020, https://doi.org/10.5194/nhess-20-1369-2020, 2020
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We assess a methodology to evaluate and improve intense precipitation forecasting in the southeastern French region. This methodology is based on the use of a 30-year dataset of past forecasts which are analysed using a spatial verification approach. We found that precipitation forecasting is qualitatively driven by the deep-convection parametrization. Locally the model is able to reproduce the distribution of spatially integrated rainfall patterns of the most intense precipitation.
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We assess a methodology to evaluate and improve intense precipitation forecasting in the southeastern French region. This methodology is based on the use of a 30-year dataset of past forecasts which are analysed using a spatial verification approach. We found that precipitation forecasting is qualitatively driven by the deep-convection parametrization. Locally the model is able to reproduce the distribution of spatially integrated rainfall patterns of the most intense precipitation.
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Forecasting the height of new snow is crucial for avalanche hazard, road viability, ski resorts and tourism. The numerical models suffer from systematic and significant errors which are misleading for the final users. Here, we applied for the first time a state-of-the-art statistical method to correct ensemble numerical forecasts of the height of new snow from their statistical link with measurements in French Alps and Pyrenees. Thus the realism of automatic forecasts can be quickly improved.
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Short summary
Weather forecasts that include uncertainty can be difficult to interpret and apply to real decisions. This study presents simplified and user-friendly tools developed in collaboration with professionals to make probabilistic forecasts more accessible. Tested to heat stress during the Paris 2024 Olympic and Paralympic Games and late frost in vineyards, these tools help anticipate risks and support earlier, more informed, and more effective responses.
Weather forecasts that include uncertainty can be difficult to interpret and apply to real...