Enhancing Lagrangian particle tracking using objective Eulerian coherent structures.

Area of Science:

• Oceanography
• Fluid Dynamics
• Computational Science

Background:

• Accurate forecasting of floating particle drift is vital for marine pollution control.
• Uncertainties in ocean surface velocity and particle initialization cause significant trajectory errors.

Purpose of the Study:

• To develop and test a correction algorithm using Objective Eulerian Coherent Structures (OECS) to improve Lagrangian particle-transport simulations.
• To reduce trajectory errors in forecasting the drift of floating particles in the ocean.

Main Methods:

• Integration of Objective Eulerian Coherent Structures (OECS) into Lagrangian particle-transport simulations.
• Development and testing of a correction algorithm incorporating attractive and repulsive OECS.
• Application of the algorithm to a dataset of drifters in the Caribbean Sea.

Main Results:

• The OECS-based correction algorithm significantly reduced trajectory errors compared to uncorrected simulations.
• Corrected median errors were below 50 km over five days, versus approximately 70 km for uncorrected trajectories.
• The algorithm demonstrated improved accuracy for larger outlier trajectories and showed potential for various marine management applications.

Conclusions:

• Incorporating OECS into Lagrangian simulations enhances particle tracking accuracy.
• This methodology offers a promising approach for marine debris management, oil spill tracking, and search and rescue operations.
• Reducing trajectory uncertainty is critical for addressing ecological challenges in ocean and coastal systems.