Lagrangian prediction and correlation analysis with Eulerian data

Abstract

A velocity field obtained from the ocean surface by high-frequency radar is used to test Lagrangian prediction algorithms designed to evaluate the position of a particle given its initial position and observations of several other simultaneously released particles. The problem is motivated by oceanographic applications such as search and rescue operations and spreading pollutants, especially in coastal regions. The prediction skill is essentially determined by temporal and spatial covariances of the underlying velocity field. For this reason correlation analysis of both Lagrangian and Eulerian velocities was carried out. Space covariance functions and spectra of the velocity field are also presented to better illustrate statistical environments for the predictability studies. The results show that the regression prediction algorithm performs quite well on scales comparable with and higher than the velocity correlation scales.