Type of dataset: monthly maps of mean sargassum surface cover

Digital Object Identifiers (DOIs): 

•  Sargassum Seasonal  Forecast : 10.24400/527896/a01-2025.002 - more metadata

Condition of access: This product is distributed by AVISO under standard AVISO+ license agreement.

Use: study the seasonal variability of the sargassum biomass in the Tropical Atlantic from Gulf of Guinea to Gulf of Mexico. Anticipate sargassum concentration and areas affected by Sargassum events in the coming months.

Description: The Seasonal Sargassum Forecast relies on the system described by Jouanno et al. (2023), currently operated by at the Laboratoire d’Etude en Géophysique et Océanographie Spatiale (LEGOS) and its first version has been developed within ANR FORESEA and TOSCA SAREDA projects. 
This system relies on a mechanistic model of Sargassum populations, the NEMO-Sarg 1.0 model (Jouanno et al. 2021,2023, 2025), which integrates both transport and a physiology model of the macroalgae. The model considers varying internal nutrient quotas (C, N, P). NEMO-Sarg is based on the Nucleus for European Modeling of the Ocean (NEMO) modeling system, allowing efficient parallelization and interfacing with physical–biogeochemical models. 
Sargassum growth is modeled as a function of internal reserves of nutrients (quotas), dissolved inorganic nutrients in seawater, irradiance, and sea temperature, while its decay depends on senescence and sea-state. Jouanno et al. (2021, 2023, 2025) describes the code and its evolution and illustrates the capacity of the model to represent the seasonal cycle of Sargassum and regime shift around 2011. The code and a set of forcing are freely available on Zenodo (https://www.zenodo.org/record/4275901). 

The ensemble version of the Sargassum model at 1/4° horizontal resolution has been implemented and allows for the production of 7-month forecasts every month, initialized from Sargassum areal coverage near-real time estimates from the Moderate Resolution Imaging Spectroradiometer MODIS (Berline & Descloitres, 2021). The forecast is the result of 25-member ensembles to account for uncertainties in the predictability of the coupled ocean-atmosphere system. For each member, the surface winds and the solar radiation are obtained from from a member randomly extracted among the 51 members of the fifth-generation seasonal forecast system SEAS5 of the European Centre for Medium-Range Weather Forecasts (ECMWF, Johnson et al., 2019). The surface currents, temperature and salinity are obtained from ensembles of 25 regional physical ocean forecasts based on NEMOv4.0 (Nucleus for European Modelling of the Ocean, Madec & The NEMO System Team, 2023) forced with meteorological fields from the SEAS5 members. A climatology based on the biogeochemical analysis and forecast system BIO4 from Mercator Ocean International is used for nutrients as there are no skillful biogeochemical seasonal forecasts available to the community. The 7-month limit of the Sargassum forecast is imposed by the length of the ECMWF's operational forecasts.| The forecasting performances for the period 2010-2022 are described in Jouanno et al. (2023).

Geographic coverage: Latitude -15.00 to 50.00, Longitude -100.00 to 15.00

Citation: Any use of this dataset must be verified in the AVISO+ license and must cite its DOI 10.24400/527896/a01-2025.002 as well as the following sentence: "The Sargassum Seasonal Forecast product has been produced by IRD with support from CNES, distributed by Aviso+ (DOI 10.24400/527896/a01-2025.002)"

Resources: 

• User manual
• The code and a set of forcing are freely available on Zenodo (https://www.zenodo.org/record/4275901).
• Jouanno, J., Morvan, G., Berline, L., Benshila, R., Aumont, O., Sheinbaum, J., & Ménard, F. (2023). Skillful seasonal forecast of Sargassum proliferation in the Tropical Atlantic. Geophysical Research Letters, 50, e2023GL105545. https://doi.org/10.1029/2023GL105545
• Berline, L., & Descloitres, J. (2021). Cartes de répartition des couvertures de Sargasses dérivées de MODIS sur l'Atlantique [Dataset]. AERIS/ ICARE - CNES/TOSCA. https://doi.org/10.12770/8fe1cdcb-f4ea-4c81-8543-50f0b39b4eca  
• Johnson, S. J., Stockdale, T. N., Ferranti, L., Balmaseda, M. A., Molteni, F., Magnusson, L., et al. (2019). SEAS5: The new ECMWF seasonal forecast system. Geoscientific Model Development, 12(3), 1087–1117. https://doi.org/10.5194/gmd-12-1087-2019  
• Jouanno, J., & Benshila, R. (2020). Sargassum distribution model based on the NEMO ocean modelling platform (0.0) [Software]. Zenodo. https://doi.org/10.5281/zenodo.4275901  
• Jouanno, J., Benshila, R., Berline, L., Soulié, A., Radenac, M. H., Morvan, G., et al. (2021a). A NEMO-based model of Sargassum distribution in the tropical Atlantic: Description of the model and sensitivity analysis (NEMO-Sarg1.0). Geoscientific Model Development, 14(6), 4069–4086. https://doi.org/10.5194/gmd-14-4069-2021
• Jouanno, J., S. Berthet, Muller-Karger, Aumont and Sheinbaum (2025). An extreme North Atlantic Oscillation event drove the pelagic Sargassum tipping point. Nature Communications Earth and Environment.
• Madec, G., & The NEMO System Team. (2023). NEMO ocean engine reference manual [Software]. Zenodo. https://doi.org/10.5281/zenodo.8167700