OceanTracker 0.5: Fast Adaptable Lagrangian Particle Tracking in Structured and Unstructured Grids

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Authors

Laurin Steidle , Ross Vennell, Malcolm Smeaton, Romain Chaput, Ben Knight

Abstract

Particle tracking is frequently used to compute particle movements within hydrodynamic ocean models; however,
modelling millions of particles is computationally challenging. OceanTracker is designed to minimise the time required to
obtain results from particle tracking. Firstly, by being computationally fast, it enables users to scale to large numbers of particles,
thus obtaining better statistics or exploring a wider range of cases within acceptable run times. Secondly, OceanTracker can calculate multiple
particle statistics during the computational run, eliminating the time needed to post-process large volumes of recorded particle
trajectories. The adaptability of OceanTracker's modular computational pipeline allows users to add and modify components
which govern particle physics, behaviour, and statistics. The computational pipeline is entirely assembled from user-provided parameters, supplied as a text file or built using helper methods. Coders can easily modify existing components through code inheritance. Currently, OceanTracker supports hydrodynamic model output for unstructured grids (SCHISM, FVCOM, DELFT3D-FM) and structured grids (ROMS, NEMO/GLORYS). Computing the trajectories for more than a million particles with OceanTracker on a single computer core is 35 times faster than the OpenDrift code and twice as fast as the Ocean Parcels code, despite treating structured grids as unstructured. As a result, on a basic laptop computers it can model one million particles for one month in less than one hour, or many more particles on better hardware. OceanTrackers design allows multiple variations of particle tracking to be configured to run in parallel.

DOI

https://doi.org/10.31223/X5WM6Z

Subjects

Numerical Analysis and Scientific Computing, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics

Keywords

Ocean transport, Lagrangian, Numerical Model, Particle tracking

Dates

Published: 2025-01-16 05:33

Last Updated: 2025-01-16 13:26

License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
None