Articles | Volume 21, issue 4
https://doi.org/10.5194/os-21-1813-2025
https://doi.org/10.5194/os-21-1813-2025
Research article
 | 
26 Aug 2025
Research article |  | 26 Aug 2025

Drivers of high-frequency extreme sea levels around northern Europe – synergies between recurrent neural networks and random forest

Céline Heuzé, Linn Carlstedt, Lea Poropat, and Heather Reese

Model code and software

cheuze/SeaLevel_RF_LSTM_EGU_OS_2025: Paper accepted (v1.0) C. L. Heuzé https://doi.org/10.5281/zenodo.15754554

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Short summary
Extreme sea levels will worsen under climate change. In northern Europe, what drives these extreme events will not change, so determining these drivers is of use for planning coastal defences. Here, using two machine learning methods on hourly tide gauge and weather data at nine locations around the North and Baltic seas, we determine that the drivers of prolonged periods of high sea level are westerly winds, whereas the drivers of the most extreme peaks depend on the coastline geometry.
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