Articles | Volume 20, issue 2
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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Forecasting the Mediterranean Sea Marine Heatwave of summer 2022
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The role of air-sea heat fluxes for marine heatwaves in the Mediterranean Sea
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Cited articles

Alvarez Fanjul, E., Ciliberti, S. A., and Bahurel, P.: Implementing Operational Ocean Monitoring and Forecasting Systems, IOC-UNESCO, 376 pp.,, 2022. a
Anding, D. and Kauth, R.: Estimation of sea surface temperature from space, Remote Sens. Environ., 1, 217–220, 1970. a
Bonino, G., Galimberti, G., Masina, S., McAdam, R., and Clementi, E.: Machine learning methods to predict Sea Surface Temperature and Marine Heatwave occurrence: a case study of the Mediterranean Sea, Zenodo [code],, 2023a. a
Bonino, G., Masina, S., Galimberti, G., and Moretti, M.: Southern Europe and western Asian marine heatwaves (SEWA-MHWs): a dataset based on macroevents, Earth Syst. Sci. Data, 15, 1269–1285,, 2023b. a
Boukabara, S.-A., Krasnopolsky, V., Stewart, J. Q., Maddy, E. S., Shahroudi, N., and Hoffman, R. N.: Leveraging modern artificial intelligence for remote sensing and NWP: Benefits and challenges, B. Am. Meteorol. Soc., 100, ES473–ES491, 2019. a, b, c
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.