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IMPRINT: Improvement of sub-seasonal probabilistic forecasts of European high-impact weather events using machine learning techniques

  • 1 July, 2018
  • VU University Amsterdam, Institute for Environmental Studies (IVM)
  • Prof. Bart van den Hurk
  • Dr. Dim CoumouDr. Maurice SchmeitsDr Kirien Whan

Each year Europe is subject to drought, heatwaves and periods of persistent rainfall that could lead to the flooding of rivers. Although short-range weather forecasts have improved substantially over the last decennia, long-range weather forecasts have improved less. The goal of this project is to improve these long-term probabilistic forecasts of extreme weather. Warnings can then be given earlier and more reliably. Long meteorological datasets and newly developed statistical post-processing methods enable us to better integrate the relevant information, and correct shortcomings of operational ensemble prediction systems.

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Researcher

Chiem van Straaten

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