Changes in the Southern Ocean (SO) have global consequences. The SO region is responsible for about half of the global annual uptake of anthropogenic carbon dioxide (CO2) from the atmosphere. As part of the atmospheric CO2 uptake is driven by phytoplankton primary production, a significant impact on the feedback of phytoplankton is expected under climate change. Indeed, changes in the atmospheric and ocean temperature, wind patterns and sea ice concentration have already been documented in the SO region. However, our understanding on how phytoplankton respond to ongoing and future environmental changes strongly depends on consistent large scale and long term observations. As a remote region, substantial time and costs are required to obtain a comprehensive dataset for the SO. The use of satellite remote sensing is a cost-effective alternative and has led to important insights into the current knowledge of phytoplankton dynamics in this region. However, this technique does not come without limitations. Ocean colour remote sensing at high latitudes has to deal with different issues as for example high cloudiness and the limited number of in situ observations for development and calibration/validation of algorithms. Consequently, there is a strong need to assess the performance of ocean colour derived-products in the SO. Ocean colour remote sensing can be used to estimate net primary production (NPP), abundance of phytoplankton functional types (PFT), as well as their spatial and temporal dynamic. Although accurate information on NPP is fundamental, large differences have been observed among models hitherto applied in the SO. Apart from that, different PFTs play specific roles in the oceanic biogeochemical cycle and this information is of key importance on quantifying oceanic NPP. Diatoms, for instance, are the main primary producers in the region. Furthermore, additional insights into their variability due to environmental changes can be gained by studying the phenology of diatom blooms. The underlying aim of this thesis is to shed light into the above mentioned topics with a focus on the SO. Four main objectives have been pursued: 1) to evaluate the satellite retrievals of euphotic depth (Zeu) and how they influence NPP satellite retrievals; 2) to evaluate and improve the satellite retrievals of diatom abundance; 3) to investigate the mean patterns and interannual variability of diatom bloom phenology and 4) to examine the potential of ocean colour products to access environmental changes in the SO. The first study analyses satellite retrievals of Zeu, which is the lower limit of the euphotic zone and where most of the primary production takes place. Although the Zeu is a key parameter in modelling oceanic NPP from satellite data, assessments of the uncertainties of satellite Zeu products are scarce. This study investigated existing approaches and sensors to evaluate how different Zeu products might affect the estimation of NPP in the SO. Zeu was derived from MODIS and SeaWiFS products of (i) surface chlorophyll-a (Zeu-Chla) and (ii) inherent optical properties (Zeu-IOP). After comparison with in situ measurements, both approaches have shown robust results of Zeu retrievals, but spatial differences were of up to 30% over specific regions. Differences between the sensors were less evident. It was also shown that differences larger than 30% are expected in NPP, depending on the method used to estimate Zeu. In the second study, focus is given to the major marine primary producer - the diatoms - and to the importance of the SO in developing a global algorithm for the retrieval of diatom abundance using the Abundance Based Approach (ABA). A large global in situ dataset of phytoplankton pigments was compiled, particularly with more samples collected in the SO. The ABA was revised to account for the penetration depth (Zpd) and to improve the relationship between diatoms and total chlorophyll-a (TChla). The results showed a distinct relationship between diatoms and TChla in the SO and a new global model (ABAZpd) was suggested to improve the estimation of diatoms abundance, which improved the uncertainties by 28% in the SO compared with the original ABA model. In addition, a regional model for the SO was developed which further improved the retrieval of diatoms by 17% compared with the global ABAZpd model. The main finding of this study is that diatom may be more abundant in the SO than previously thought. In the third study, the new regional model was used to examine the mean pattern and the interannual variability of the diatom bloom phenology from 1997 to 2012. Ten phenological indices were used to describe the timing, duration and magnitude of the diatom blooms. The results show that the mean spatial patterns are generally associated to the position of the Southern Antarctic Circumpolar Current Front and of the maximum sea ice extent. Furthermore, in several areas of the SO the interannual variability of the anomalies of the phenological indices is found to be correlated with the large scale climate oscillations El Niño Southern Oscillation (ENSO) and Southern Annular Mode (SAM). The composite maps of the anomalies revealed distinct spatial patterns and opposite events of ENSO and SAM have similar effects in the diatom phenology. For example, in the Ross Sea region, later start of the bloom and lower biomass were observed associated with El Niño and negative SAM events; likely influenced by an increase in sea ice concentration during these events. These results confirm that climate variability and diatom blooms in the SO are closely linked through environmental changes and these processes can be accessed using ocean colour remote sensing.