Articles | Volume 25, issue 3
https://doi.org/10.5194/nhess-25-1139-2025
https://doi.org/10.5194/nhess-25-1139-2025
Research article
 | 
17 Mar 2025
Research article |  | 17 Mar 2025

Using random forests to forecast daily extreme sea level occurrences at the Baltic Coast

Kai Bellinghausen, Birgit Hünicke, and Eduardo Zorita

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Short summary
We designed a tool to predict the storm surges at the Baltic Sea coast with satisfactory predictability (80 % correct predictions), using lead times of a few days. The proportion of false warnings is typically as low as 10 % to 20 %. We were able to identify the relevant predictor regions and their patterns – such as low-pressure systems and strong winds. Due to its short computing time, the method can be used as a pre-warning system to trigger the application of more sophisticated algorithms.
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