Automatic detection of oceanic eddies in reanalyzed SST images and its application in the East China Sea

Abstract

Oceanic eddies may cause local sea surface temperature (SST), height, and salinity anomalies in remote sensing (RS) images. Remote sensed SST imagery has proven to be an effective technique in oceanic eddy detection, because of its high temporal and spatial resolution. Various techniques have been used to identify eddies from SST images. However, mainly owing to the strong morphological variation of oceanic eddies, there is arguably no uniquely correct eddy detection method. A scheme of algorithm based on quasi-contour tracing and clustering of eddy detection from SST dataset is presented. The method does not impose fixed restrictions or limitations during the course of “suspected” eddy detection, and any eddy-like structures can be detected as “suspected” eddies. Then, “true” eddies can be identified based on the combination of intensity and spatial/temporal scale criteria. This approach has been applied to detect eddies in the East China Sea by using Operational SST & Sea Ice Analysis (OSTIA) dataset. Experiments proved that oceanic eddies ranging in diameter from tens to hundreds of kilometers can be detected. Through investigation of the 2007–2011 OSTIA daily SST dataset from the Kuroshio region in the East China Sea, we found that the most active regions for oceanic eddies are those along the Kuroshio path, northeast of Taiwan Island, the Yangtze Estuary and the Ryukyu Islands. About 86% of the cyclonic eddies and 87% of the anticyclonic eddies have the size of 50–100 km in diameter. Only 25% of the anticyclonic eddy and 26% of the cyclonic eddy have the strength more than 0.4°C in the sea surface layer.