On Clustering of Floating Tracers in Random Velocity Fields

In this paper, we investigate the aggregation of a floating tracer into clusters. Motivated by observations dense patches buoyant material in real ocean (e.g., microplastic pollutants, plankton, and sargassum), develop an idealized model that can reproduce clustering process. A stochastic, kinematic 2D velocity field is chosen to represent turbulent oceanic surface currents, with weakly divergent component. Lagrangian particles are introduced track their concentrations. We differ from delta-correlated fields used previous studies including finite time correlations. Clustering these be compared traditional setting, through global measures cluster detection algorithms. The enhanced deformed using various interpolation methods. then sensitivity representation temporal/spatial structure inform future phenomenon. find coherency time-correlated velocities leads significantly faster rates clustering, causing larger number longer lived/more populated clusters form. likely relevant host biogeochemical processes urgent interest, such as phytoplankton blooms ecological risk pollutants. This work aims establish accurate basis for simulations, enable further exploration.