Predicting the movement of floating objects in our oceans is not just a scientific curiosity, it is a matter of environmental urgency. From tracking oil spills to forecasting the drift of sargassum algae and plastics, accurately modeling how particles travel through ocean currents can save both ecosystems and lives.

In a recent study published in the journal Marine Pollution Bulletin, AIAS-AUFF Fellow Christian Appendini and colleagues introduce a novel algorithm that incorporates the Objective Eulerian Coherent Structures (OECS) method to significantly enhance Lagrangian particle tracking. By incorporating the persistent features of ocean flow patterns, their novel approach refines predictions and reduces errors that have long challenged traditional models.

Understanding the challenge

Traditionally, forecasting the trajectory of floating particles has relied on Lagrangian models that follow particles as they move with ocean currents. However, the ocean’s velocity field is highly dynamic and sensitive where even minor changes can lead to dramatic differences in a particle’s path. This sensitivity is often amplified near marine areas of strong attraction or repulsion, which means that even state-of-the-art models struggle to accurately predict particle movements. In practical terms, when responding to an oil spill or search-and-rescue operation, these inaccuracies could mean delays or misdirected efforts. 

The OECS breakthrough in particle tracking

The new research introduces a fresh perspective by integrating OECS into particle tracking simulations. In essence, OECS are short-term flow features that pinpoint regions in the ocean where the forces of attraction and repulsion are strongest. By “reading” these structures from instantaneous snapshots of the ocean’s surface currents, the researchers were able to pinpoint where errors are most likely to occur in traditional trajectory forecasts.

The innovative algorithm they have developed uses a correction factor derived from these OECS. It adjusts both the direction and the speed of simulated particle movements based on the local flow patterns. The team conducted tests using real-world data from satellite-tracked drifters in the Caribbean Sea over a five-day period. These tests revealed that in 71% of cases, the corrected trajectories more closely matched the observed drifter paths. The traditional, uncorrected models saw median errors climbing to 60–70 km, while the new method kept these errors down to around 50 km or less, with significant improvements noted even in the most extreme cases.

More precise responses to marine emergencies

More accurate models mean faster, more precise responses to marine emergencies, such as containing an oil spill, mitigating the impact of invasive sargassum blooms or streamlining search-and-rescue operations. The improved predictions enabled by the novel OECS-based approach could transform operational strategies in marine environmental management. While the tests in the study focused on the Caribbean, the new methodology is designed to be broadly applicable across global waters. 

Looking ahead – integrating complexity

While the new method shows significant promise, the ocean’s inherent complexity means that challenges still lie ahead. Notably, in nearly 29% of the cases in the study, the correction algorithm produced slightly larger errors than the uncorrected trajectories. This observation underscores the need for ongoing refinement and calibration of the new approach.

Future research of the team of researchers will focus on integrating additional physical processes, such as inertial effects, more sophisticated representations of wind-driven surface drifts and Stokes drift to further reduce error margins and enhance forecasting precision. Christian Appendini and his colleagues also plan to extend their validation studies to include a wider array of drifter data, both drogued and undrogued, to ensure that the method developed performs robustly under various conditions.  

Bridging the gap between theoretical models and practical, real-time applications

Their goal is to bridge the gap between advanced theoretical models and practical, real-time applications. By combining the precision of OECS with the flexibility of Lagrangian tracking, the study is laying the groundwork for next generation forecasting tools that can be deployed in operational settings. Tools that not only advance scientific understanding but also have the potential to protect both human and marine life. 

Access the full scientific article

The study is the fruit of an international research collaboration - access the study here:
‘Enhancing Lagrangian Particle Tracking Using Objective Eulerian Coherent Structures’ by Quintana-Barranco et al in: Marine Pollution Bulletin, 13 March 2025. Access the article here.

Contact

Christian Appendini, AIAS-AUFF Fellow
E-mail: cma@aias.au.dk

Aarhus Institute of Advanced Studies, AIAS
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