Ocean model fields are being routinely used for forecasting the spreading of pollutants, oil spills, and for biogeochemical transport. Recent observations and advances in our understanding of ocean processes indicate there is an explosion of flow instabilities in the submesoscale range. While submesoscale flows have a significant impact on transport at their own scales, they require much more extensive data sets and numerical computations. Therefore, transport carried out by submesoscale flows is quite challenging to approach deterministically. In this study, we put forward a hybrid approach by combining deterministic Lagrangian coherent structures (LCS) to compute transport over the mesoscale range with statistical Lagrangian subgridscale (LSGS) models for the underresolved submesoscale motions. We apply this approach to particle transport in the Gulf Stream region, which exhibits indications of submesoscale activity from both models and observations. We consider HYCOM solutions at two resolutions. In the 1/12° computation, mesoscale features are well resolved but submesoscales are not resolved, while the 1/48° computation captures some of the submesoscale flow instabilities as well. By using metrics of relative dispersion, we investigate three LSGS models and demonstrate that they can be useful in correcting the underestimation of submesoscale dispersion in the 1/12° solution, with respect to relative dispersion obtained from the 1/48° solution and an observational result.
- Lagrangian stochastic models
- Relative dispersion
ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Geotechnical Engineering and Engineering Geology
- Atmospheric Science