Ocean surface circulation within the bay of biscay, on the basis of remote sensing data

Resumen

The accidental discharge of fuel into the ocean generates oil slicks that tend to drift horizontally, with the surface currents. The recovery of oil slicks, in the sea, reduces the harmful effect of the contaminant on the marine environment. The knowledge and the forecasting of the surface ocean circulation and, hence, of the trajectory of the oil slicks drifting with the surface currents, facilitates the recovery tasks. This is one of the main conclusions derived after a crisis, which occurred within the Bay of Biscay, a sub-basin located in the eastern North Atlantic, following the sinking of the oil tanker Prestige offshore of the Galician coasts. Certain commercial fish species drift within the surface currents, during the first stages of their life cycle. In the case of the Bay of Biscay anchovy populations (Engraulis encrasicolus), the knowledge and the forecasting of the surface ocean circulation, will assist in the development of a better understanding of the life cycle of this species. This information, together with the scientific management of this fishery, may help in a sustainable fishing of this species. The above are two examples for which the knowledge of the surface water circulation is essential. However, there are different methods to estimate the surface circulation. The instrumental methods are the most precise, since they are based upon current measurements and not in estimations. Nevertheless, despite the suitability of the instrumental measurements for local studies, the deployment of multiple instruments, to study the surface circulation on a synoptic scale, is not viable; this is due to the logistical complexity and cost that will be encountered. Another way to analyse the surface circulation is the use of numerical models. These models are suitable for synoptic studies, but instead of measurements, they provide estimations of the surface currents; therefore, such estimations incorporate a certain degree of error.