Understanding and Predicting Sargassum Blooms: A Coupled Modeling and Remote Sensing Approach

The proliferation of pelagic Sargassum in the tropical Atlantic since 2011 has become a significant environmental and socioeconomic issue. To better understand and predict this phenomenon, a combination of remote sensing observations and numerical modeling has been employed. By integrating satellite data with a biophysical model (NEMO-Sarg), we have investigated the factors driving Sargassum blooms, their seasonal variability, and their potential impact on coastal regions. Our findings highlight the role of the North Atlantic Oscillation in initiating the regime shift in 2010 and the nutrient fluxes sustaining subsequent blooms. Additionally, we demonstrate the feasibility of seasonal Sargassum forecasts with up to 7-month of anticipation, providing valuable insights for coastal communities to mitigate the adverse effects of Sargassum inundation. By quantifying the amount of Sargassum accumulating on coastlines and developing vulnerability indices, we identify regions most at risk and inform targeted management strategies. These advancements in our understanding and predictive capabilities are crucial for addressing the challenges posed by Sargassum blooms and safeguarding coastal ecosystems.