Stochastic modeling of Lagrangian ocean surface drifter trajectories

We present a stochastic model that can describe the motion of ocean surface trajectories obtained from freely drifting satellite-tracked instruments. The model constitutes of three components: the first is for the turbulent background, the second is for inertial oscillations, and the third is for the tides. The aggregated model has nine parameters, and by fitting the stochastic model to observed Lagrangian trajectories, the estimated parameters provide useful summaries of structure. As examples, we can estimate the rate of horizontal diffusivity, the damping timescale of inertial oscillations, or the rate of decay of the Lagrangian spectral slope. By analysing multiple windows of observed trajectories, we can capture the spatial variability of these parameters across different regions. We do this by analysing the entire Global Drifter Program database of observations since 1979, constituting over 60 million data points. Our findings uncover interesting spatial patterns and develop general understanding of ocean circulation and ocean surface dynamics. Furthermore, these finding provide the first global estimates of the Lagrangian spectral slope.