Forecasting seasonal sargassum events across the tropical Atlantic: overview and challenges

Abstract

Proliferation of sargassum across the tropical Atlantic since 2011 has motivated a range of forecasting methods. Statistical methods based on basin-scale satellite data are used to address seasonal timescales. Other methods involve explicit Lagrangian calculations of trajectories for particles that are representative of drifting sargassum over days-months. This computed sargassum drift is attributed to the combined action of surface currents, winds and waves, individually or in various combinations. Such calculations are undertaken with both observed surface drift and simulated currents, each involving strengths and weaknesses. Observed drift implicitly includes the action on sargassum of winds and waves, assumed equivalent between drifters and sargassum mats. Simulated currents provide large gridded datasets that facilitate computation of ensembles, enabling some quantification of the uncertainty inherent in an eddy-rich ocean, further subject to interannual variability. A more limited number of forecasts account for in situ growth or loss of sargassum biomass, subject to considerable uncertainty. Forecasts provide either non-dimensional indices or quantities of sargassum, accumulated in specified areas or counted across specified transects over a given time interval. Proliferation of different forecast methodologies may reduce uncertainty, if predictions for given seasons are consistent in broad terms, but there is scope to coordinate different approaches with common geographical foci and predicted variables, to facilitate direct inter-comparisons. In an example of forecasting westward sargassum flux into the Caribbean during the first half of 2022, challenges and opportunities are highlighted. In conclusion, prospects for closer alignment of complementary forecasting methods, and implications for sargassum management, are identified.

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