Improved Surface Velocity and Trajectory Estimates in the Gulf of Mexico from Blended Satellite Altimetry and Drifter Data
AbstractThis study investigates the results of blending altimetry-based surface currents in the Gulf of Mexico with available drifter observations. Here, subsets of trajectories obtained from the near-simultaneous deployment of about 300 Coastal Ocean Dynamics Experiment (CODE) surface drifters provide both input and control data. The fidelity of surface velocity fields are measured in the Lagrangian frame by a skill score that compares the separation between observed and hindcast trajectories to the observed absolute dispersion. Trajectories estimated from altimetry-based velocities provide satisfactory average results (skill score > 0.4) in large (~100 km) open-ocean structures. However, the distribution of skill score values within these structures is quite variable. In the DeSoto Canyon and on the shelf where smaller-scale structures are present, the overall altimeter skill score is typically reduced to less than 0.2. After 3 days, the dataset-averaged distance between hindcast and drifter trajectories, , is about 45 km—only slightly less than the average dispersion of the observations, km. Blending information from a subset of drifters via a variational method leads to significant improvements in all dynamical regimes. Skill scores typically increase to 0.8 with reduced to less than half of . Blending available drifter information with altimetry data restores velocity field variability at scales not directly sampled by the altimeter and introduces ageostrophic components that cannot be described by simple Ekman superposition. The proposed method provides a means to improve the fidelity of near-real-time synoptic estimates of ocean surface velocity fields by combining altimetric data with modest numbers of in situ drifter observations.
Observed and Modeled Global Ocean Turbulence Regimes as Deduced from Surface Trajectory Data
