Linking Horizontal and Vertical Submesoscale Lagrangian Dynamics South of the Ibiza Channel
Sara Cloux, Ismael Hernandez-Carrasco, Alejandro Orfila, Emilio Hernandez-Garcia, Cristobal Lopez
Abstract
Fronts, eddies, jets, and meanders populate the ocean surface and play a key role in organizing transport and mixing across a wide range of scales. From a Lagrangian perspective, frontal structures are conveniently detected as surface filaments that act as barriers to horizontal transport. However, the degree to which these structures maintain coherence below the surface and the relationship between horizontal and vertical motions in their vicinity remain poorly understood. Here we analyze two such filaments in the western Mediterranean Sea, south of the Ibiza Channel, using a high-resolution ocean simulation and Lagrangian diagnostics specifically designed to characterize submesoscale transport. Backward Finite-Size Lyapunov Exponents (FSLE) computed at successive depths reveal nearly vertical, curtain-like structures extending several tens of meters into the water column, with intensity decreasing with depth. Vertical-velocity sections across the filaments show coherent downward motion aligned with the filament cores, while Lagrangian trajectories indicate rapid horizontal convergence of fluid particles accompanied by sustained downward displacement. The barrier effect of Lagrangian Coherent Structures (LCSs) is commonly associated with persistent dynamical features of large-scale flows. Here, however, we demonstrate that FSLE filaments generated by rapidly fluctuating submesoscale dynamics can also act as effective transport barriers. The results demonstrate that the surface signatures of Lagrangian filaments identified through FSLE techniques correspond to three-dimensional transport structures that regulate both lateral aggregation and vertical connectivity in the upper ocean.
Create a lesson
Related papers
Cumulus parameterization controls simulated rainfall more than microphysics, but not at heavy thresholds: a 3 * 2 factorial WRF study over the Western Himalaya
Satyam Kumar, Akshay Sunil, Devesh Sheoran
Extreme events and statistics in an AI emulator of a global storm-resolving model
Anna Kwa, W. Andre Perkins, Troy Arcomano et al.
The hypervariational method: a general, automated technique based on innovations to tune the parameters of the Hybrid covariance matrix
Francesco Sardelli, Craig H. Bishop
Statistical Downscaling of Daily Precipitation from ERA5 Atmospheric Fields to IMERG over West Africa
David Sagna, Redouane Lguensat, Samo Diatta
Forecasting carbon-risk hotspots ahead of the extreme 2026 El Niño
Xiaomeng Du, Runda Jiang, Philippe Ciais et al.
Identifying Arctic states vulnerable to rapid ice loss with a convolutional neural network
Matthew Patterson, Ioana Colfescu, Nathan Kirk et al.