Constructing and Assessing Ocean Frontal Indexes from Satellite SST Observations
Lekouara, Mounir1; Robinson, Ian S.2; Bouvet, Marc1

It is becoming increasingly evident that ocean surface density fronts are associated with intense sub-mesoscale vertical mixing which can trigger local blooms of primary productivity. Satellite observations of Sea Surface Temperature (SST) are an important way of understanding these processes. The potential for measuring fronts on satellite single-sensor SST data sets is limited by the presence of clouds on Infrared measurements and by the low resolution of Microwave instruments. A lot of effort is being given to producing new level-4 analysis products which merge SST measurements from various satellite and in-situ sensors. This work explores the capacity of these new high temporal and spatial frequency global datasets to reveal ocean mesoscale and sub-mesoscale frontal variability. The application of front detection algorithms produces daily maps of fronts and their local spatial and temporal statistics. An attempt is made to infer dynamical properties of fronts from their signature on the SST in order to produce indexes which characterize fronts accordingly to their dynamical significance. This frontal analysis approach is being applied with a view to quantify up-welling associated with frontal sub-mesoscale processes which appear to be necessary to close the new production budget in the subtropical gyres. The spatial and temporal variability of the ocean fronts is also explored in order to determine their sensitivity to climatic signals. This study demonstrates the power of high-resolution SST datasets for resolving oceanographic small scale activity variability on a climatic and global scale. It provides new tools for oceanographers to apply on regional studies.