Ocean surface flows at meso and submesoscales exhibit strong spatial heterogeneity and intense convergence associated with fronts and filaments. These structures play a key role in vertical exchanges of heat, nutrients and tracers, and strongly impact surface transport. In particular, Lagrangian particle clustering provides a useful framework to investigate how fine-scale dynamics shape tracer accumulation and dispersion.

In this study, we investigate the characteristics of particle clustering in energetic submesoscale regimes using high-resolution numerical simulations (LLC4320) and Lagrangian particle tracking. We focus on the relationship between clustering and dynamical properties of the flow, with special attention to frontal regions where strong convergence and ageostrophic motions occur.

Clustering is characterized through a set of Lagrangian and Eulerian diagnostics in order to identify flow structures leading to particle accumulation and to quantify characteristic clustering timescales. We further explore the sensitivity of particle clustering to the dynamical components of the flow (in particular frontal scales) by comparing advection by full or geostrophic velocity fields. This approach aims to clarify the contribution of small-scale and ageostrophic processes to clustering intensity and timescales.

This work provides a framework for quantifying Lagrangian clustering in submesoscale fronts and for assessing how unresolved scales and dynamical balances influence surface tracer distributions. It contributes to a better understanding of fine-scale transport processes relevant to oceanic heat exchange and pollutant dispersion.