Articles | Volume 18, issue 4
https://doi.org/10.5194/os-18-915-2022
https://doi.org/10.5194/os-18-915-2022
Research article
 | 
04 Jul 2022
Research article |  | 04 Jul 2022

Clustering analysis of the Sargassum transport process: application to beaching prediction in the Lesser Antilles

Didier Bernard, Emmanuel Biabiany, Raphaël Cécé, Romual Chery, and Naoufal Sekkat

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Cited articles

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Anses: Expositions aux émanations d'algues sargasses en décomposition aux Antilles et en Guyane, Technical report, ANSES, Maisons-Alfort, France, 162 pp., available at: https://www.anses.fr/en/system/files/AIR2015SA0225Ra.pdf (last access: 20 October 2021), 2017. 
Arnault, S., Thiria, S., Crépon, M., and Kaly, F.: A tropical Atlantic dynamics analysis by combining machine learning and satellite data, Adv. Space Res., 68, 467–486, https://doi.org/10.1016/j.asr.2020.09.044 2021. 
Baklouti, M., Devenon, J.-L., Bourret, A., Froidefond, J.-M., Ternon, J.-F., and Fuda, J.-L.: New insights in the French Guiana continental shelf circulation and its relation to the North Brazil Current retroflection, J. Geophys. Res., 112, C02023, https://doi.org/10.1029/2006JC003520, 2007. 
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Short summary
The massive Sargassum algae beachings observed over the past decade are a new natural hazard currently impacting the island states of the Caribbean region. This study aims to improve the prediction of the surface current dynamic leading to beachings in the Lesser Antilles using clustering analysis methods. The present clustering analysis predictive system would help improve this risk management in the islands of the region.