A NEMO-based model of Sargassum distribution in the tropical Atlantic: description of the model and sensitivity analysis (NEMO-Sarg1.0)

The tropical Atlantic has been facing a massive proliferation of Sargassum since 2011, with severe environmental and socioeconomic impacts. The development of large-scale modeling of Sargassum transport and physiology is essential to clarify the link between Sargassum distribution and environmental...

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Bibliographic Details
Published in:Geoscientific Model Development 2021-07, Vol.14 (6), p.4069-4086
Main Authors: Jouanno, Julien, Benshila, Rachid, Berline, Léo, Soulié, Antonin, Radenac, Marie-Hélène, Morvan, Guillaume, Diaz, Frédéric, Sheinbaum, Julio, Chevalier, Cristele, Thibaut, Thierry, Changeux, Thomas, Menard, Frédéric, Berthet, Sarah, Aumont, Olivier, Ethé, Christian, Nabat, Pierre, Mallet, Marc
Format: Article
Language:English
Subjects:
Algae
Atmospheric models
Biogeochemistry
Biomass
Distribution
Earth Sciences
Environmental conditions
Large-scale models
Mathematical models
Mineral nutrients
Modelling
Nutrients
Ocean currents
Ocean models
Oceans
Physiology
Proliferation
Salinity
Sargassum
Satellite observation
Sciences of the Universe
Seasonal distribution
Seasonal forecasting
Seasonal variation
Sensitivity analysis
Socioeconomic factors
Stranding
Transport
Tropical climate
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Summary:The tropical Atlantic has been facing a massive proliferation of Sargassum since 2011, with severe environmental and socioeconomic impacts. The development of large-scale modeling of Sargassum transport and physiology is essential to clarify the link between Sargassum distribution and environmental conditions, and to lay the groundwork for a seasonal forecast at the scale of the tropical Atlantic basin. We developed a modeling framework based on the Nucleus for European Modelling of the Ocean (NEMO) ocean model, which integrates transport by currents and waves, and physiology of Sargassum with varying internal nutrients quota, and considers stranding at the coast. The model is initialized from basin-scale satellite observations, and performance was assessed over the year 2017. Model parameters are calibrated through the analysis of a large ensemble of simulations, and the sensitivity to forcing fields like riverine nutrient inputs, atmospheric deposition, and waves is discussed. Overall, results demonstrate the ability of the model to reproduce and forecast the seasonal cycle and large-scale distribution of Sargassum biomass.
ISSN:1991-9603
1991-959X
1991-962X
1991-9603
1991-962X
DOI:10.5194/gmd-14-4069-2021