We apply a regularized vector autoregressive clustering technique to identify recurrent and persistent states of atmospheric circulation patterns in theNorthAtlantic sector (110W-0E, 20N-90N) associated with the Atlantic Ridge (AR) and the North Atlantic Oscillation (NAO). The technique additionally provides the temporal behavior in terms of a time-dependent switching between the respective cluster states. Using the resulting cluster affiliations for each day, we set the switching sequence a priori to define a non-smooth linear delayed map that we use to analyze the dynamics associated with the resulting cluster-based model. We compute the time-dependent covariant Lyapunov vectors (CLVs) and their associated finite-time covariant Lyapunov exponents (FTCLEs), with a particular focus on indicators of transitions between the states. We find that the window chosen to compute the CLVs acts as a filter on the dynamics. For short windows, CLV alignment and changes in FTCLE growth rates are indicative of individual transitions between persistent states. For long windows, we observe an emergent annual signal manifest in the alignment of the CLVs characteristic of the observed seasonality in the respective NAO and AR indices. Analysis of the average finite-time dimension reveals the NAO- as the most unstable state relative to the NAO+, with persistent AR states largely stable.