Filtering Drifter Trajectories Sampled at Submesoscale Resolution

Author

Yaremchuk, Max ; Coelho, Emanuel F.

Author_Institution

Stennis Space Center, Naval Res. Lab., Washington, MS, USA

Volume

40

Issue

3

fYear

2015

fDate

Jul-15

Firstpage

497

Lastpage

505

Abstract

In this paper, a variational method for removing positioning errors (PEs) from drifter trajectories is proposed. The technique is based on the assumption of statistical independence of the PEs and drifter accelerations. The method provides a realistic approximation to the probability density function of the accelerations while keeping the difference between the filtered and observed trajectories within the error bars of the positioning noise. Performance of the method is demonstrated in application to real data acquired during the Grand Lagrangian Deployment (GLAD) experiment in the Northern Gulf of Mexico in 2012.

Keywords

approximation theory; data acquisition; oceanographic techniques; probability; statistical analysis; variational techniques; GLAD; Northern Gulf of Mexico; PE removal; approximation theory; data acquisition; filtering drifter trajectory; grand Lagrangian deployment; positioning error removal; probability density function; statistical independence; submesoscale resolution; variational method; Acceleration; Global Positioning System; Noise; Sea surface; Surface treatment; Trajectory; Computers and information processing/data processing; mathematics/filtering algorithms; optimization; smoothing methods;

fLanguage

English

Journal_Title

Oceanic Engineering, IEEE Journal of

Publisher

ieee

ISSN

0364-9059

Type

jour

DOI

10.1109/JOE.2014.2353472

Filename

6932495