An Automated Approach to Detect Oceanic Eddies From Satellite Remotely Sensed Sea Surface Temperature Data

Cyclonic (anticyclonic) oceanic eddies drive local upwelling (downwelling), leaving footprints in the sea surface temperature (SST) field as local extremes. Satellite-measured SST images can therefore be used to obtain information of the characteristics of oceanic eddies. Remotely sensed measurements represent very large data sets, both spatially and temporally. Manual eddy detection and analysis are thus practically impossible. In this letter, an automated scheme for eddy detection from remote sensing SST data is presented. The method is based on the analysis of velocity fields derived from SST measurements (thermal-wind velocity field). Using the geometric features of the velocity field, we can identify positions of eddy centers and derive eddy size, intensity, path, and lifetime. The scheme is applied to a realistic remotely sensed SST data set in a strong eddy activity region: Kuroshio Extension region.