Abstract
Relative dispersion statistics and related Lagrangian parameters, not well observed in coastal regions, are obtained from in situ surface drifter observations and presented in the context of Lagrangian stochastic models. Clusters of GPS tracked surface drifters, with initial horizontal spacing of 5–10 m, were repetitively deployed in the Santa Barbara Channel from July 2004 to June 2005. The drifters sampled their position every 10 min for 1–2 days. Mean square pair separation distance, or relative dispersion, increases approximately exponentially in time during the first ∼5 h of sampling (e‐folding time of 0.9 h). Thereafter, the dispersion increase is approximately quadratic in time. Large error bars on the observed mean dispersion, and higher‐order Lagrangian statistics that are not clearly supportive of the aforementioned dispersion curves, indicate uncertainty. The mean square relative (separation) velocity shows near‐linear growth with pair separation distance, extending from 0.3 to 85 cm2 s−2over length scales from ∼8 m to 2.2 km. The observed length scale dependency in square relative velocity is investigated in a Lagrangian stochastic model (LSM) for a cloud of particles. Modeled dispersion agrees with observations only when the velocity scale for the sub‐grid scale random normal deviate in the LSM (typically a constant) is length scale dependent, and takes into consideration the observed scaling. Occasional large (>25 cm s−1) discrepancies in grid‐scale velocities between drifters and HF radar cause general disagreement in distributions of ending positions of LSM trajectories when compared with Lagrangian observations.
Key Points
Relative dispersion observations for the coastal ocean are presented
Mean square relative velocity grows linearly with separation distance
A scale‐dependent Lagrangian stochastic model form is presented
