Extratropical cyclones (ETCs) are major features of the weather in the mid- and high-latitudes and are often associated with hazardous conditions such as heavy precipitation, high winds, blizzard conditions, and flooding. Additionally, severe coastal damage and major local impacts, including inundation and erosion, can result from high waves and storm surge due to cyclone interaction with the ocean. Consequently, ETCs can have serious detrimental socio-economic impacts. The west and east coasts of North America are strongly influenced by ETC storm activity. These coastal regions are also host to many land-based, coastal, and maritime socio-economic sectors, all of which can experience strong adverse impacts from extratropical storm activity. Society would therefore benefit if variations in ETC storm activity could be predicted skilfully for the upcoming season. Skilful prediction would enable affected sectors to better anticipate, prepare for, manage, and respond to variations in storm activity and the associated risks. The overall objective of this dissertation is to determine the seasonal predictability of North American coastal extratropical storm activity during the cold months (3-month rolling seasons – OND, NDJ, DJF, JFM – during which storm activity is most frequent and intense) using Environment and Climate Change Canada’s Canadian Seasonal to Interannual Prediction System (CanSIPS). This dissertation describes research focused on three themes: 1.) reanalysis representation of North American coastal storm activity, 2.) potential predictability of storm activity and climate signal-storm activity relationships for the North American coastal regions, and 3.) seasonal prediction of storm activity in CanSIPS. Research Theme 1 evaluates six global reanalysis datasets to determine which best reproduces observed storm activity in the North American coastal regions, annually and seasonally, during the 1979-2010 time period using single-station surface pressure-based proxies; ERA-Interim is found to perform best overall. Research Theme 2, using ERA-Interim, investigates the potential predictability of extratropical storm activity (represented by mean sea level pressure [MSLP], absolute pressure tendency, and 10-m wind speed) during the 1979-2015 time period using analysis of variance. The detected potential predictability provides observation-based evidence showing that it may be possible to predict storm activity on the seasonal timescale. Additionally, using composite analysis, the El Niño-Southern Oscillation, Pacific Decadal Oscillation, and North Atlantic Oscillation are identified as possible sources of predictability in the North American coastal regions. Research Theme 2 provides a basis upon which seasonal forecasting of extratropical storm activity can be developed. Research Theme 3 investigates the seasonal prediction of North American coastal storm activity using the CanSIPS multi-model ensemble mean hindcasts (1981-2010). Quantitative deterministic, categorical deterministic, and categorical probabilistic forecasts are constructed using the three equiprobable category framework (below-, near-, and above-normal conditions) and the parametric Gaussian method for determining probabilities. These forecasts are then evaluated against ERA-Interim using the correlation skill score, percent correct score, and Brier skill score to determine forecast skill. Baseline forecast skill is found for the seasonal forecasts of all three storm activity proxies, with MSLP forecasts found to be most skilful and 10-m wind speed forecasts the least skilful. Skilful seasonal forecasting of North American coastal extratropical storm activity is, therefore, possible in CanSIPS. / Graduate