On clustering of floating tracers in random velocity fields
Author(s)
Meacham, Jamie
Berloff, Pavel
Type
Journal Article
Abstract
In this paper, we investigate the aggregation of a floating tracer into clusters. Motivated by observations of dense patches of buoyant material in the real ocean (e.g., microplastic pollutants, plankton, and sargassum), we develop an idealized model that can reproduce the clustering process. A stochastic, kinematic 2D velocity field is chosen to represent turbulent oceanic surface currents, with a weakly divergent component. Lagrangian particles are introduced and we track their concentrations. We differ from delta-correlated fields used in previous studies by including finite time correlations. Clustering in these fields can be compared to the traditional setting, through global measures and cluster detection algorithms. The enhanced velocity fields can be deformed using various interpolation methods. We can then investigate the sensitivity of clustering to the representation of temporal/spatial velocity structure to inform future studies of this phenomenon. We find coherency of time-correlated velocities leads to significantly faster rates of clustering, causing a larger number of longer lived/more populated clusters to form. Clustering is likely relevant to a host of biogeochemical processes of urgent interest, such as phytoplankton blooms and the ecological risk of microplastic pollutants. This work aims to establish an accurate basis for clustering simulations, to enable further exploration.
Date Issued
2023-05
Date Acceptance
2023-05-08
Citation
Journal of Advances in Modeling Earth Systems, 2023, 15 (5)
ISSN
1942-2466
Publisher
American Geophysical Union (AGU)
Journal / Book Title
Journal of Advances in Modeling Earth Systems
Volume
15
Issue
5
Copyright Statement
© 2023 The Authors. Journal of Advances in Modeling Earth Systems published by Wiley Periodicals LLC on behalf of American Geophysical Union.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
License URL
Identifier
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000993420300001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
Subjects
clustering
DEBRIS
fluids
kinematic
Lagrangian
MESOSCALE
Meteorology & Atmospheric Sciences
mixing
PARTICLES
Physical Sciences
Science & Technology
turbulence
Publication Status
Published
Article Number
e2022MS003484
Date Publish Online
2023-05-22