Articles | Volume 20, issue 2
https://doi.org/10.5194/os-20-417-2024
https://doi.org/10.5194/os-20-417-2024
Research article
 | 
22 Mar 2024
Research article |  | 22 Mar 2024

Machine learning methods to predict sea surface temperature and marine heatwave occurrence: a case study of the Mediterranean Sea

Giulia Bonino, Giuliano Galimberti, Simona Masina, Ronan McAdam, and Emanuela Clementi

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Latest update: 20 May 2024
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Short summary
This study employs machine learning to predict marine heatwaves (MHWs) in the Mediterranean Sea. MHWs have far-reaching impacts on society and ecosystems. Using data from ESA and ECMWF, the research develops accurate prediction models for sea surface temperature (SST) and MHWs across the region. Notably, machine learning methods outperform existing forecasting systems, showing promise in early MHW predictions. The study also highlights the importance of solar radiation as a predictor of SST.