Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-4069-2021
https://doi.org/10.5194/gmd-14-4069-2021
Model description paper
 | 
01 Jul 2021
Model description paper |  | 01 Jul 2021

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

Julien Jouanno, Rachid Benshila, Léo Berline, Antonin Soulié, Marie-Hélène Radenac, Guillaume Morvan, Frédéric Diaz, Julio Sheinbaum, Cristele Chevalier, Thierry Thibaut, Thomas Changeux, Frédéric Menard, Sarah Berthet, Olivier Aumont, Christian Ethé, Pierre Nabat, and Marc Mallet

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Cited articles

Aumont, O. and Bopp, L.: Globalizing results from ocean in- situ iron fertilization experiments, Global Biogeochem. Cy., 20, GB2017, https://doi.org/10.1029/2005GB002591, 2006. 
Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. 
Axell, L. B.: Wind-driven internal waves and Langmuir circulations in a numerical ocean model of the southern Baltic Sea, J. Geophys. Res.-Oceans, 107, 3204, https://doi.org/10.1029/2001JC000922, 2002. 
Awo F. M., Alory, G., Da-Allada, C., Delcroix, T., Jouanno, J., and Baloïtch, E.: Sea Surface Salinity signature of the tropical Atlantic interannual climatic modes, J. Geophys. Res., 123, 7420–7437, https://doi.org/10.1029/2018JC013837, 2018. 
Baker, P., Minzlaff, U., Schoenle, A., Schwabe, E., Hohlfeld, M., Jeuck, A, Brenke, N., Prausse, D., Rothenbeck, M., Brix, S., Frutos, I., Jörger, K. M., Neusser, T. P., Koppelmann, R., Devey, C., Brandt, A., and Arndt, H.: Potential contribution of surface-dwelling Sargassum algae to deep-sea ecosystems in the southern North Atlantic, Deep-Sea Res. Pt. II, 148, 21–34, 2018. 
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Short summary
The tropical Atlantic has been facing a massive proliferation of Sargassum since 2011, with severe environmental and socioeconomic impacts. We developed a modeling framework based on the NEMO ocean model, which integrates transport by currents and waves, and physiology of Sargassum with varying internal nutrient 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.