Data coverage in the Southern Ocean is a limiting factor for a full understanding of physical and biological processes: still little is known about their seasonality as well as their regional distribution. In these conditions remote sensing becomes a key tool, as high resolution is possible both in space and time.Focus of this study is the Scotia Sea, included between the Drake Passage and the South Sandwich Islands, the North and South Scotia Ridge. Satellite based measurements of chlorophyll-a show an enhanced biological productivity in the vicinity of the island ecosystems, which is then redistributed by complex circulation patterns. As for other High Nutrient Low Chlorophyll regions, the iron deficiency hypothesis is a well accepted explanation for these confined and intense spring and summer phytoplankton blooms. Several studies suggest that melting of sea-ice, ocean circulation patterns, grazing and the presence of confined land (the so called island mass effect), can regulate their occurrence and extent, although the relative importance of these factors is difficult to ascertain. Here, we address interannual and spatial variability of phytoplankton blooms in the Scotia Sea region; a combination of different datasets is used to describe and study their dynamics. Aqua-MODIS measurements of surface chlorophyll-a concentration and sea surface temperature (SST) were obtained from the NASA Goddard Distributed Active Archive Center. Analysis of regional monthly averaged data allows to track the history of each bloom, as well as to locate its starting point and extension.Fronts and water masses can be contoured by following horizontal temperature gradients. Available Argo float CTD profiles will also contribute with values for the mixed layer depth. Results show a significant inter-annual variability of the bloom starting point, intensity and extent, especially around the South Sandwich and South Georgia islands. However, the complexity of interactions between the phytoplankton communities and the surrounding environment, responsible for bottom-up and top-down control (i.e. micro-nutrient enrichment and grazing) implies the need for more dedicated surveys and high resolution coupled physical-biogeochemical models; the latter would provide further information regarding nutrient fluxes and physical processes, especially during the undersampled winter season.