Understanding coastal water flows
Ecological and biogeochemical conditions of coastal regions are significantly affected by the mechanisms responsible for horizontal transport and cross-shelf exchanges of water masses. They are controlled by processes such as eddies, fronts (the boundary between two water masses) or filaments (which are formed by turbulent stirring). These (sub) meso-scale features are in the order of 10 km or less and originate from instabilities in large-scale ocean currents. Understanding the impact of these processes through the use of techniques such as finite-size Lyapunov exponent (FSLE) is crucial for managing coastal ecological resources. The FSLEs are used to identify Lagrangian coherent structures (LCSs), which can provide direct information on transport and mixing patterns of a flow. The EU-funded project 'Lyapunov analysis in the coastal environment' (LACOSTE) investigated LCSs in the Gulf of Lion in the north-western Mediterranean. This was achieved using a combination of field measurements (including surface temperature and salinity), numerical model results and satellite observations. Results showed that although (sub) meso-scale processes are short-lived and localised, they are a key factor in regulating biological and ecological conditions in coastal regions. While in situ observations can provide detailed information on specific events, numerical modelling simulations and remote sensing help investigate their impact over a larger scale. Researchers also conducted an extended analysis of transport structures at the (sub) meso scale for the whole of the Gulf of Lion. This was achieved by applying the FSLE analysis to the numerical model results in order to identify and quantify transport patterns and associated fluxes using self-organising maps. LACOSTE results will enable identification of those areas of the Gulf of Lion most affected by transport patterns. This will make a vital contribution to the sustainable management of the area's ecological resources. The methods applied to numerical models will also contribute to regional and global climate studies.
