Preprints
https://doi.org/10.5194/gmd-2020-383
https://doi.org/10.5194/gmd-2020-383

Submitted as: model description paper 04 Dec 2020

Submitted as: model description paper | 04 Dec 2020

Review status: a revised version of this preprint was accepted for the journal GMD and is expected to appear here in due course.

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

Julien Jouanno1, Rachid Benshila1, Léo Berline2, Antonin Soulié1, Marie-Hélène Radenac1, Guillaume Morvan1, Frédéric Diaz2, Julio Sheinbaum3, Cristele Chevalier2, Thierry Thibaut2, Thomas Changeux2, Frédéric Menard2, Sarah Berthet4, Olivier Aumont5, Christian Ethé5, Pierre Nabat4, and Marc Mallet4 Julien Jouanno et al.
  • 1LEGOS, Université de Toulouse, IRD, CNRS, CNES, UPS, Toulouse, France
  • 2Aix-Marseille University, Université de Toulon, CNRS/INSU, IRD, MIO UM 110, Mediterranean Institute of Oceanography (MIO), Campus of Luminy, 13288 Marseille, France
  • 3CICESE, Ensenada, Mexico
  • 4CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
  • 5Laboratoire d’Océanographie et de Climatologie: Expérimentation et Approches Numériques, IRD-IPSL, 4 Place Jussieu, 75005 Paris, France

Abstract. The Tropical Atlantic is facing a massive proliferation of Sargassum since 2011, with severe environmental and socioeconomic impacts. The development of Sargassum modelling is essential to clarify the link between Sargassum distribution and environmental conditions, and to lay the groundwork for a seasonal forecast on the scale of the Tropical Atlantic basin. We developed a modelling framework based on the NEMO ocean model, which integrates transport by currents and waves, 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 Sargassum year 2017. Model parameters are calibrated through the analysis of a large ensemble of simulations, and the sensitivity to forcing fields like riverine nutrients 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.

Julien Jouanno et al.

 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Julien Jouanno et al.

Model code and software

NEMO-Sarg1.0 J. Jouanno and R. Benshila https://doi.org/10.5281/zenodo.4275901

Julien Jouanno et al.

Viewed

Total article views: 473 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
327 142 4 473 7 8
  • HTML: 327
  • PDF: 142
  • XML: 4
  • Total: 473
  • BibTeX: 7
  • EndNote: 8
Views and downloads (calculated since 04 Dec 2020)
Cumulative views and downloads (calculated since 04 Dec 2020)

Viewed (geographical distribution)

Total article views: 397 (including HTML, PDF, and XML) Thereof 396 with geography defined and 1 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 12 Jun 2021
Download
Short summary
The Tropical Atlantic is facing a massive proliferation of Sargassum since 2011, with severe environmental and socioeconomic impacts. We developed a modelling framework based on the NEMO ocean model, which integrates transport by currents and waves, physiology of Sargassum with varying internal nutrients quota, and considers stranding at the coast. Results demonstrate the ability of the model to reproduce and forecast the seasonal cycle and large-scale distribution of Sargassum biomass.