CFM 2019

Massive stranding of pelagic sargassum on French Antilles coasts: Analysis of observed situations with Operational Mercator global ocean analysis and forecast system
Didier-Clement Bernard  1@  , Naoufal Sekkat  1, *@  , Romual Chery  1, *@  , Emmanuel Biabiany  1, *@  , Raphaël Cécé  1, *@  
1 : Laboratoire de Recherche en Géosciences et Energies  (LARGE)
Université des Antilles (Pôle Guadeloupe) : EA4539
* : Auteur correspondant

The unprecedented influx of Sargassum that reached the French Antilles on several occasions, especially during 2015 to 2018 constitutes a major threat to the ecology, health and economy of these islands. These small islands can each receive an average of 150 000 m3 of seaweed during major stranding episodes. The predictability of these has not been investigated and is likely related with thermodynamic conditions that cause a build-up and ocean transport that brings the problem to east-facing beaches and bays, mainly since 2011. The increased volume of seaweed has closed some tourism resorts and made some beaches uninhabitable. A research effort becomes necessary to reduce these uncertainties and thereby apprehend future episodes of seaweed stranding.

We present here the results from a series of ocean models that examine surface transport, east of the Antilles, for several cases of massive stranding on the coasts of Guadeloupe and Martinique. The Operational Mercator global ocean analysis and forecast system at 1/12 degree was used and includes daily and monthly mean files of temperature, salinity, currents, sea level, and mixed layer depth. It also includes time-integrated fields for sea surface height, temperature and currents. The atmospheric fields forcing the ocean model are taken from the ECMWF (European Centre for Medium-Range Weather Forecasts) Integrated Forecast System. We will explore the dynamical and statistical relationships between surface currents and Sargassum cover observed by satellites in the Atlantic near these islands and on reaching the coastal areas.

 



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