Quantifying Variability in Lagrangian Particle Dispersal in Ocean Ensemble Simulations

Scientists at Utrecht University have made a significant breakthrough in understanding the behavior of particle dispersal in ocean ensemble simulations. By using an information theory approach, the researchers were able to define and compare the variability in the ensemble with single-member simulations. The study found that release periods of 12 to 20 weeks and spatial releases with a 2.0° radius most effectively captured the full ensemble variability.

Key Takeaways:

• Ensemble Lagrangian simulations aim to capture the full range of possible outcomes for particle dispersal, but single-member Lagrangian simulations only provide a subset of the possible outcomes.
• The study explored how to generate variability in a single-member simulation to obtain comparable trajectory variability and dispersal to the full 50-member ensemble.
• The researchers used an information theory approach to define and compare the variability in the ensemble with single-member strategies, finding that release periods of 12 to 20 weeks most effectively captured the full ensemble variability.
• Spatial releases with a 2.0° radius resulted in the closest match at timescales shorter than 10 d.
• Adding Brownian motion diffusion captured the entropy aspects of the full ensemble variability well but led to an overestimation of connectivity.
• The study provides insights to improve the representation of variability in particle trajectories and define a framework for uncertainty quantification in Lagrangian ocean analysis.

Statistics:

• 50-member ensemble simulation was used to capture the full range of possible outcomes for particle dispersal.
• Release periods of 12 to 20 weeks most effectively captured the full ensemble variability.
• Spatial releases with a 2.0° radius resulted in the closest match at timescales shorter than 10 d.
• Brownian motion diffusion with a rate of * * K* * [ [* * h* * ] ] =1000 m[superscript]2 s[superscript]-1 was used in the study.

Sources:

• Quantifying variability in Lagrangian particle dispersal in ocean ensemble simulations: an information theory approach. Nonlinear Processes in Geophysics, 2025, 32: 411-438.
• Utrecht University, Princetonplein 5, 3584 CC Utrecht, Netherlands.
• Institute for Marine and Atmospheric Research, Utrecht University.
• Copernicus Publications.
• Nonlinear Processes in Geophysics - http://www.nonlinear-processes-in-geophysics.net/.
• DOI: 10.5194/npg-32-411-2025.