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

By applying 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 eight-day SST data from 2001 to 2021. Accordingly, the extraction data are effectively used to obtain long-term characteristics, based on which the interannual variations are quantitatively investigated and examined. The long-term characteristics data are analyzed in combination with the oceanic Ni no index (ONI), and the results indicate that the yearly average SST differences in summer coastal upwelling are positively correlated with the El Ni no southern oscillation (ENSO).