4.6 Article

Submesoscale Dynamics in the Northern Gulf of Mexico. Part III: Lagrangian Implications

期刊

JOURNAL OF PHYSICAL OCEANOGRAPHY
卷 47, 期 9, 页码 2361-2376

出版社

AMER METEOROLOGICAL SOC
DOI: 10.1175/JPO-D-17-0036.1

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资金

  1. Gulf of Mexico Research Initiative through CARTHE Consortium
  2. ONR [N000141410626]
  3. Extreme Science and Engineering Discovery Environment (XSEDE)

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Four numerical simulations are used to characterize the impact of submesoscale circulations on surface Lagrangian statistics in the northern Gulf of Mexico over 2 months, February and August, representative of winter and summer. The role of resolution and riverine forcing is explored focusing on surface waters in regions where the water column is deeper than 50 m. Whenever submesoscale circulations are present, the probability density functions (PDFs) of dynamical quantities such as vorticity and horizontal velocity divergence for Eulerian and Lagrangian fields differ, with particles preferentially mapping areas of elevated negative divergence and positive vorticity. The stronger the submesoscale circulations are, the more skewed the Lagrangian distributions become, with greater differences between Eulerian and Lagrangian PDFs. In winter, Lagrangian distributions are modestly impacted by the presence of the riverine outflow, while increasing the model resolution from submesoscale permitting to submesoscale resolving has a more profound impact. In summer, the presence of riverine-induced buoyancy gradients is the key to the development of submesoscale circulations and different Eulerian and Lagrangian PDFs. Finite-size Lyapunov exponents (FSLEs) are used to characterize lateral mixing rates. Whenever submesoscale circulations are resolved and riverine outflow is included, FSLEs slopes are broadly consistent with local stirring. Simulated slopes are close to -0.5 and support a velocity field where the ageostrophic and frontogenetic components contribute stirring at scales between about 5 and 7 times the model resolution and 100 km. The robustness of Lagrangian statistics is further discussed in terms of their spatial and temporal variability and of the number of particles available.

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