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Coastal current convergence structures in the Bay of Biscay from optimized high-frequency radar and satellite data

Toxics 2024 3 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Stéphane Bertin, Anna Rubio, Ismael Hernández‐Carrasco, L. Solabarrieta, Irene Luque Ruiz, Alejandro Orfila, Alexei Sentchev

Summary

This study used high-frequency radar and satellite data optimized with drifting buoy fusion to identify coastal current convergence structures in the Bay of Biscay that drive marine litter accumulation. The optimization reduced Lagrangian tracking error by 50% and revealed how convergence zones control phytoplankton distribution and govern where floating marine debris concentrates along the coast.

Study Type Environmental

The southeastern Bay of Biscay has been described as a "dead end" for floating marine litter, often accumulating along small-scale linear streaks. Coastal Current Convergence Structures (CCS), often associated with vertical motions at river plume edges, estuarine fronts, or other physical processes, can be at the origin of the accumulation. Understanding the formation of CCS and their role in the transport of marine litter is essential to better quantify and to help mitigate marine litter pollution. The Lagrangian framework, used to estimate the absolute dispersion, and the finite-size Lyapunov exponents (FSLE), have proved very effective for identifying CCS in the current velocity field. However, the quality of CCS identification depends strongly on the Eulerian fields. Two surface current velocity data sets were used in the analysis: the remotely sensed velocities from the EuskOOS High-Frequency Radar (HFR) network and velocities from three-dimensional model outputs. They were complemented by drifting buoy velocity measurements. An optimization method, involving the fusion of drifting buoys and HFR velocities is proposed to better reconstruct the fine-scale structure of the current velocity field. Merging these two sources of velocity data reduced the mean Lagrangian error and the Root Mean Square Error (RMSE) by 50 % and 30 % respectively, significantly improving velocity reconstruction. FSLE ridgelines obtained from the Lagrangian analysis of optimized velocities were compared with remotely sensed concentrations of Chlorophyll-a. It was shown that ridgelines control the spatial distribution of phytoplankton. They fundamentally represent the CCS which can potentially affect marine litter aggregation. Analysis of the absolute dispersion revealed large stirring in the alongshore direction which was also confirmed by spatial distribution of FSLE ridgelines. The alignment between FSLE ridgelines and patterns of high Chlorophyll-a concentration was observed, often determining the limits of river plume expansion in the study area.

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