Floating tracer clustering in divergent random flows modulated by an unsteady mesoscale ocean field

• Published in: Geophysical & Astrophysical Fluid Dynamics
• Main Authors: Stepanov, D, Ryzhov, EA, Berloff, P, Koshel, K
• Other Authors: Natural Environment Research Council (NERC), The Leverhulme Trust
• Format: Article in Journal/Newspaper
• Language: English
• Published: Taylor and Francis 2020
• Subjects: Science & Technology; Physical Sciences; Technology; Astronomy & Astrophysics; Geochemistry & Geophysics; Mechanics; Mesoscale; submesoscale; steady and unsteady flows; tracer clustering; tracer mixing; STATISTICAL TOPOGRAPHY; ELLIPSOIDAL VORTEX; PASSIVE TRACERS; SEA-ICE; TRANSPORT; DEFORMATION; DIFFUSION; VORTICES; DYNAMICS; ACCUMULATION; CIRCULATION; DISPERSION; Fluids & Plasmas; Sea ice
• Online Access: http://hdl.handle.net/10044/1/81454; https://doi.org/10.1080/03091929.2020.1786551

Clustering of tracers floating on the ocean surface and evolving due to combined velocity fields consisting of a deterministic mesoscale component and a kinematic random component is analysed. The random component represents the influence of submesoscale motions. A theory of exponential clustering in random velocity fields is applied to characterise the obtained clustering scenarios in both steady and unsteady time-dependent mesoscale flows, as simulated by a comprehensive realistic, eddy-resolving, general circulation model for the Japan/East Sea. The mesoscale flow field abounds in transient eddy-like patterns modulating and branching the main currents, and the underlying time-mean flow component features closed recirculation zones that can entrap the tracer. The submesoscale flow component is modelled kinematically, as a divergent random velocity field with a prescribed correlation radius and variance. The combined flow induces tracer clustering, that is, the exponential growth of tracer density in patches with vanishing areas. The statistical topography methodology, which provides integral characteristics to quantify the emerging clusters, uncovers drastic dependence of the clustering rates on whether the mesoscale flow component is taken to be steady or time-dependent. The former situation favours robust exponential clustering, similar to the theoretically understood case of purely divergent and zero-mean random velocity. The latter situation, on the contrary, hinders exponential clustering due to significant advection of the tracer out of the nearly enclosed eddies, at the rate faster than the clustering rate.