Publications des scientifiques de l'IRD

Jouanno Julien, Benshila R., Berline L., Soulie A., Radenac Marie-Hélène, Morvan Guillaume, Diaz F., Sheinbaum J., Chevalier Cristèle, Thibaut T., Changeux Thomas, Ménard Frédéric, Berthet S., Aumont Olivier, Ethe C., Nabat P., Mallet M. (2021). 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), p. 4069-4086. ISSN 1991-959X.

Titre du document
A NEMO-based model of Sargassum distribution in the tropical Atlantic : description of the model and sensitivity analysis (NEMO-Sarg1.0)
Année de publication
2021
Type de document
Article référencé dans le Web of Science WOS:000670319500001
Auteurs
Jouanno Julien, Benshila R., Berline L., Soulie A., Radenac Marie-Hélène, Morvan Guillaume, Diaz F., Sheinbaum J., Chevalier Cristèle, Thibaut T., Changeux Thomas, Ménard Frédéric, Berthet S., Aumont Olivier, Ethe C., Nabat P., Mallet M.
Source
Geoscientific Model Development, 2021, 14 (6), p. 4069-4086 ISSN 1991-959X
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.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Limnologie biologique / Océanographie biologique [034] ; Ecologie, systèmes aquatiques [036]
Description Géographique
ATLANTIQUE
Localisation
Fonds IRD [F B010082279]
Identifiant IRD
fdi:010082279
Contact