Ocean processes underlying surface clustering

Abstract

Ageostrophic ocean processes such as frontogenesis, submesoscale mixed‐layer instabilities, shelf break fronts, and topographic interactions on the continental shelf produce surface‐divergent flows that affect buoyant material over time. This study examines the ocean processes leading to clustering, i.e., the increase of material density over time, on the ocean surface. The time series of divergence along a material trajectory, the Lagrangian divergence (LD), is the flow property driving clustering. To understand the impacts of various ocean processes on LD, numerical ocean model simulations at different resolutions are analyzed. Although the relevant processes differ, patterns in clustering evolution from the deep ocean and the continental shelf bear similarities. Smaller‐scale ocean features are associated with stronger surface divergence, and the surface material clustering is initially dominated by these features. Over time, the effect of these small‐scale features becomes bounded, as material traverses small‐scale regions of both positive and negative divergence. Lower‐frequency flow phenomena, however, continue the clustering. As a result, clustering evolves from initial small‐scale to larger‐scale patterns.

Clusters, deformation, and dilation: Diagnostics for material accumulation regions

“…These aspects are addressed by Jacobs et al [2015]. In fact, its strength of reflecting cumulative effects, which is critical for a diagnostic, makes the identification of these challenging.…”

Submesoscale evolution of surface drifter triads in the Gulf of Mexico

“…In the present study, triplet shape metrics from in situ drifters are analyzed to further quantify tracer patch evolution, complementing prior numerical investigations on surface clustering [ Zhong and Bracco , ; Kalda et al , ; Huntley et al , ; Jacobs et al , ] and ultimately informing oil spill mitigation efforts. LaCasce and Ohlmann [] and LaCasce [] investigated triangle evolution from 30 chance triplets of drifters initially separated by ≈1 km in the Gulf of Mexico.…”

Impact of data assimilation on Eulerian versus Lagrangian estimates of upper ocean transport

“…One likely cause for these differences is the fact that the more pronounced stratification in ANA enables a stronger near‐surface amplitude of wind‐forced currents, as discussed in Röhrs and Christensen []. Our analysis does not reveal why the Lagrangian energy levels are higher in the reanalysis, but there are two possible explanations: (i) the differences in the upper ocean dynamics leads to more clustering, and convergence of numerical drifters in regions of strong divergence [ Jacobs et al ., ], and/or (ii) the increase in periodic flow features (cf. the increase in the superinertial frequency band) leads to an increase in the residual drift currents [ Longuet‐Higgins , ; Wei et al ., ].…”