Clustering of Floating Tracer Due to Mesoscale Vortex and Submesoscale Fields

• Published in: Geophysical research letters 2020-02, Vol.47 (3), p.n/a
• Main Authors: Stepanov, Dmitry V., Ryzhov, Eugene A., Zagumennov, Alexei A., Berloff, Pavel, Koshel, Konstantin V.
• Format: Article
• Language: English
• Subjects: Aggregation; Clustering; Computer simulation; Diagnostic software; Diagnostic systems; Divergence; Ecological aggregations; Fields; Floating; General circulation models; Impurities; Kinematics; mesoscale eddies; Mesoscale phenomena; Mesoscale vortexes; Ocean surface; Oceanography; Oceans; Oil pollution; Oil spills; Plastic pollution; random velocity field; Seawater; submesoscale; Surface velocity; tracer clustering; Tracers; Velocity; Velocity distribution; Vortices; Water flow; Water pollution
• ISSN: 0094-8276; 1944-8007
• DOI: 10.1029/2019GL086504

Floating tracer clustering is studied in oceanic flows that combine both a field of coherent mesoscale vortices, as simulated by a regional, comprehensive, eddy‐resolving general circulation model, and kinematic random submesoscale velocity fields. Both fields have rotational and divergent velocity components, and depending on their relative contributions, as well as on the local characteristics of the mesoscale vortices, we identified different clustering scenarios. We found that the mesoscale vortices do not prevent clustering but significantly modify its rate and spatial pattern. We also demonstrated that even weak surface‐velocity divergence has to be taken into account to avoid significant errors in model predictions of the floating tracer patterns. Our approach combining dynamically constrained and random velocity fields, and the applied diagnostic methods, are proposed as standard tools for analyses and predictions of floating tracer distributions, in both observational data and general circulation models. Plain Language Summary The problem of dispersion and aggregation of various tracers in the ocean has recently attracted a lot of interest. These tracers can be natural ocean water characteristics, such as temperature and salinity, or various hazardous impurities, such as plastic pollution and oil spills. The latter tracers are also the floating ones, which means that their dynamics is different from the passive tracers. An important and interesting aspect of the floating tracers is their ability to form pronounced clusters, that is aggregations in isolated patches—understanding and predicting this phenomenon is one of the challenges in modern oceanography. In this study, we explore how floating‐tracer clustering depends on kinematic characteristics of the ocean surface velocity. Key Points Phenomenology of floating tracer clustering in the divergent submesoscale and mesoscale flow Exponential clustering process is analyzed depending on the submesoscale model characteristics It is argued that the 2D velocity field divergence is essential for studying tracer transport properties