Skillful Seasonal Forecast of Sargassum Proliferation in the Tropical Atlantic

• Published in: Geophysical research letters Vol. 50; no. 21
• Main Authors: Jouanno, Julien, Morvan, Guillaume, Berline, Léo, Benshila, Rachid, Aumont, Olivier, Sheinbaum, Julio, Ménard, Frederic
• Format: Journal Article
• Language: English
• Published: Washington John Wiley & Sons, Inc 16.11.2023; American Geophysical Union; Wiley
• Subjects: Algae; Annual variations; Atlantic; Biogeochemistry; Coastal zone; Decision making; Environmental Sciences; Fishing; forecast; Forecasting; Mitigation; Nutrients; Pelagic fisheries; Radiation; Salinity; Sargassum; Satellites; Seasonal distribution; Seasonal forecasting; skill; Stranding; West Africa
• ISSN: 0094-8276; 1944-8007
• DOI: 10.1029/2023GL105545

The large‐scale proliferation of pelagic Sargassum in the Tropical Atlantic from 2011 has been the subject of increasing attention because of its negative consequences on the environment, fishing, and socioeconomic activities when stranding on coastal areas. This recurrent phenomenon presents strong seasonal and year to year variations. Anticipating the abundances and stranding on seasonal scale poses important challenges in terms of observations and modeling. We show that skillful seasonal forecast of Sargassum distribution can be achieved with up to 7 months in advance over the Tropical Atlantic, by integrating both transport and current knowledge on physiology of Sargassum. This forecast is designed to help marine stakeholders to develop mitigation and resilience strategies through anticipatory decision‐making. Plain Language Summary The Caribbean, Gulf of Mexico, and Tropical Atlantic are facing a massive and growing proliferation of floating brown algae (Sargassum) since 2011, whose environmental and socioeconomic impacts are immense. Observing, modeling, and forecasting the Sargassum proliferation and strandings are essential for designing effective integrated risk management strategies and is a strong and pressing demand from the civil society. The present study shows that a skillful forecast can be produced up to 7 months ahead of time by building on current knowledge on Sargassum physiology, mechanistic modeling, and remote sensing observations. Key Points A transport and physiology model of pelagic Sargassum has been developed Skillful seasonal forecast of Sargassum distribution can be achieved with up to 7 months in advance This forecast extends the current Sargassum observation and forecasting services