This thesis presents a detailed analysis of ice drift speeds, patterns in the Arctic Ocean and their forcing mechanisms using a combination of various datasets. The mean Arctic Ocean sea-ice motion consists of three well-known primary circulation regimes: the Beaufort Gyre (BG), transpolar drift (TPD), and a motion system from the Kara Sea (KS). Regression analyses of the ice drift speed anomalies show statistically significant positive drift speed trends in BG, TPD and KS. The first three modes of Empirical Orthogonal Functions were found to explain 30.2%, 13.5% and 8.7% of the spatial variance in the mean winter ice drift patterns and highlight the large variability in the ice drift patterns. Although the geophysical systems are often assumed to follow Gaussian probability density functions; however, deviations from Gaussian behaviour can shed light on the underlying dynamics. For the large-scale motion of the Arctic sea ice, such deviations have been interpreted as signatures of structure in dynamic flow fields. In this study, we use higher-order moments (skewness and kurtosis) to identify spatiotemporal changes in the Beaufort Gyre (BG) and the Transpolar Drift (TPD) sea-ice drift patterns. Higher-order moments of satellite-derived ice drift speeds are examined over the winter period of 2006–2017 to describe the persistence of features like the BG and TPD, and their variation over time. Index patterns indicate that the periphery of the BG can be identified by a combination of high positive skewness and high kurtosis in the ice drift time series on an annual basis. Furthermore, we examined the Arctic basin-wide sea ice drift speeds and patterns, and specifically focus on the response of ice drift to wind speeds.