Articles | Volume 6, issue 2
https://doi.org/10.5194/wcd-6-571-2025
https://doi.org/10.5194/wcd-6-571-2025
Research article
 | 
21 May 2025
Research article |  | 21 May 2025

Weather type reconstruction using machine learning approaches

Lucas Pfister, Lena Wilhelm, Yuri Brugnara, Noemi Imfeld, and Stefan Brönnimann

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Short summary
Our work compares different machine learning approaches for creating long-term classifications of daily atmospheric circulation patterns using input data from surface meteorological observations. Our comparison reveals that a feedforward neural network performs best at this task. Using this model, we present a daily reconstruction of a commonly used weather type classification for central Europe that dates back to 1728.
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