Understanding and modelling sargassum life-cycle
The year to year re-emergence of the sargassum in the « Great Atlantic Sargassum Belt » is allowed by their persistence in boreal winter in the eastern north Tropical Atlantic, where warm and nutrient- rich waters provide optimal conditions for their survival (Berline et al, 2017; Skliris et al 2022). In a seasonal perspective, this region is also key for the performance of forecasts systems since the amount of sargassum in this region will feed the proliferation in the Caribbean several months ahead (Jouanno et al. 2023). Presently, observations in this region rely solely on daily products from polar orbiting satellites. However, frequent cloud cover and aerosols significantly hinder these observations, leading to limited data, which, in turn, constrains the sargassum life cycle analysis. Considering the broad coverage of the Atlantic basin provided by MTG-FCI, offering kilometre-scale spatial resolution and high temporal frequency, the products developed in WP1 will serve as additional data for a more comprehensive understanding of the sargassum life cycle and enhanced seasonal-scale predictions. These observations hold particular value in the eastern basin (off the coast of Sierra Leone/Gulf of Guinea) for improving the initial conditions and a better understanding of the dynamics of Sargassum. In the NEMO-Sarg model (Jouanno et al 2021), satellite data play a central role in improving the accuracy of initializations, particularly with regard to sargassum coverage. Currently, initialization is based on degraded MODIS sargassum coverage fields at 0.25° resolution, averaged over one month. This monthly average is necessary to guarantee a « cloud-free » map. However, this temporal average may not accurately capture dynamic changes, particularly in regions such as the western edge of the tropical Atlantic where sargassum movements can be prompt, or the cloudy eastern region where sargassum rafts develop rapidly. With the integration of geostationary data, it is possible to reduce the averaging window, resulting in improved « cloud-free » initial conditions. As a result, this adjustment can lead to more consistent initial sargassum conditions, closely aligned with initial physical conditions, such as dynamics constrained by eddies activity. With a resolution finer than 1/12°, it will also be possible to compare a coupled ocean-atmosphere model such as NEMO-Sarg with the Lagrangian model already in place for the short term.
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- Berline, L., Ody, A., Jouanno, J., Chevalier, C., André, J. M., Thibaut, T., & Ménard, F. (2020). Hindcasting the 2017 dispersal of Sargassum algae in the Tropical North Atlantic. Marine Pollution Bulletin. https://doi.org/10.1016/j.marpolbul.2020.111431
- Jouanno, J., Benshila, R., Berline, L., Soulié, A., Radenac, M. H., Morvan, G., & 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. https://doi.org/10.5194/gmd-14-4069-2021
- 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. https://doi.org/10.1029/2023GL105545
- Skliris, N., Marsh, R., Appeaning Addo, K., & Oxenford, H. (2022). Physical drivers of pelagic Sargassum bloom interannual variability in the Central West Atlantic over 2010–2020. OceanDynamics. https://doi.org/10.1007/s10236-022-01511-1