Current state-of-the art procedures for studying modeled submesoscale oceanographic features have made a strong assumption of independence between features identified at different times. Therefore, all submesoscale eddies identified in a time series were studied in aggregate. Statistics from these methods are illuminating but oversample identified features and cannot determine the lifetime evolution of the transient submesoscale processes. To this end, the authors apply the Topological Feature Tracking (TFT) algorithm to the problem of identifying and tracking submesoscale eddies over time. TFT allows a user to identify submesoscale eddies as critical points on a set of time-ordered scalar fields and associate the points between consecutive timesteps. The procedure yields tracklets which represent spatio-temporal displacement of eddies. Thus the time-dependent behavior of submesoscale eddies can be studied. We analyze the submesoscale eddy dataset produced by TFT, which yields unique, time-varying statistics on this currently underexplored phenomenon.