Efficient Extraction of Coastal Upwelling in the Northern South China Sea Based on Sea Surface Temperature Data and Research of Its Interannual Variations

Abstract

By applying of the spatial intuitionistic fuzzy c-means (SIFCM) method based on MODIS Terra Sea Surface Temperature (SST) data, we extract the significant coastal upwelling in the northern South China Sea (NSCS) efficiently, without the need for setting thresholds or regional connectivity processing. In this letter, the procedure is applied to the 8-day SST data from 2001 to 2021. Accordingly, the extraction data are effectively utilized to obtain long-term characteristics, based on which the interannual variations are quantitatively investigated and examined. The long-term characteristics data are analysed in combination with the Oceanic Niño Index (ONI), and the results indicate that the yearly average SST differences of summer coastal upwelling are positively correlated with the El Niño Southern Oscillation (ENSO).