The Western Antarctic Peninsula is one of the most rapidly warming regions on earth. It is therefore important to analyze long-term trends and inter-annual patterns of change in major environmental parameters to understand the process underlying climate change in Western Antarctica. Since many polar long-term data series are fragmented and cannot be analysed with common time series analysis tools, we present statistical approaches that can deal with missing values. We applied U-statistics after Pettit and Buishand to detect abrupt changes, dynamic factor analysis to detect functional relationships, and additive modelling to detect patterns in time related to climatic cycles such as the Southern Annular Mode and El Niño Southern Oscillation in a long-term environmental data set from King George Island (WAP), covering 20 years. Our results not only reveal sudden changes for sea surface temperature and salinity, but also clear patterns in all investigated variables (sea surface temperature, salinity, suspended particulate matter and Chlorophyll a) that can directly be related to climatic cycles. Our results complement previous findings on climate related changes in the King George Island Region and provide insight into the environmental conditions and climatic drivers of system change in the study area. Hence, our statistical analyses may prove valuable for other polar environmental data sets and contribute to a better understanding of the regional variability of climate change and its impact on coastal systems.