Observing and quantifying ocean flow properties using drifters with drogues at different depths

Author Posting. © American Meteorological Society, 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 51(8),(2021): 2463–2482, https://doi.org/10.1175/JPO-D-20-0291.1.
This paper presents analyses of drifters with drogues at different depths—1, 10, 30, and 50 m—that were deployed in the Mediterranean Sea to investigate frontal subduction and upwelling. Drifter trajectories were used to estimate divergence, vorticity, vertical velocity, and finite-size Lyapunov exponents (FTLEs) and to investigate the balance of terms in the vorticity equation. The divergence and vorticity are O(f) and change sign along trajectories. Vertical velocity is O(1 mm s−1), increases with depth, indicates predominant upwelling with isolated downwelling events, and sometimes changes sign between 1 and 50 m. Vortex stretching is one of the significant terms, but not the only one, in the vorticity balance. Two-dimensional FTLEs are 2 × 10−5 s−1 after 1 day, 2 times as large as in a 400-m-resolution numerical model. Three-dimensional FTLEs are 50% larger than 2D FTLEs and are dominated by the vertical shear of horizontal velocity. Bootstrapping suggests uncertainty levels of ~10% of the time-mean absolute values for divergence and vorticity. Analysis of simulated drifters in a model suggests that drifter-based estimates of divergence and vorticity are close to the Eulerian model estimates, except when drifters get aligned into long filaments. Drifter-based vertical velocity is close to the Eulerian model estimates at 1 m but differs at deeper depths. The errors in the vertical velocity are largely due to the lateral separation between drifters at different depths and are partially due to only measuring at four depths. Overall, this paper demonstrates how drifters, heretofore restricted to 2D near-surface observations, can be used to learn about 3D flow properties throughout the upper layer of the water column.
Authors Rypina and Pratt were supported by U.S. Office of Naval Research (ONR) Grant N000141812417. Author Getscher acknowledges support from the U.S. Navy Civilian Institution Office with the MIT–WHOI Joint Program. Author Mourre acknowledges support from ONR Grant N00014-16-1-3130. We also thank Eugenio Cutolo for the initial technical support in the implementation of the ultra-high-resolution WMOP simulation. CALYPSO is a Departmental Research Initiative funded by the ONR.
2022-01-16