Abstract:

This dataset has been generated in order to investigate how particles (i.e. oil from a spill) behave on the surface when the ocean is dominated by convection. We found that there is a preferential concentration mechanism that dominates the surface signature. The dataset is submitted as a zip file with of pair of files for each figure. Each pair contains the data (in numpy-npz format) and a small python script to read the data.

Suggested Citation:

Tomas Chor. 2018. Preferential concentration of non-inertial buoyant particles in the ocean mixed-layer under free-convection. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N7VX0F2R

Publications:

Chor, T., Yang, D., Meneveau, C., & Chamecki, M. (2018). Preferential concentration of noninertial buoyant particles in the ocean mixed layer under free convection. Physical Review Fluids, 3(6). doi:10.1103/physrevfluids.3.064501

Purpose:

This dataset has been generated in order to investigate how particles (i.e. oil from a spill) behaves on the surface when the ocean is dominated by convection. We found that there is a preferential concentration mechanism that dominates the surface signature.

Data Parameters and Units:

1000m x 1000m x 120m ocean Large Eddy Simulation (LES) with a heat flux at the boundary being the only forcing. No Coriolis effect included. General variables for all figures: x - x-coordinate y - y-coordinate All variables here are non-dimensional, i.e. they were non-dimenionalized by their relevant scales: Deardorff convective velocity scale for velocities, depth of the mixed layer for distances and an arbitrary concentration scale for concentrations. fig1: div - horizontal divergence at the surface conc_surf - surface concentration of particles fig2: X - horizontal divergence at surface Y - divergent okubo-weiss parameter at the surface (2D strain rate minus vertical vorticity) JPDF - Joint probability density function of the hor. divergence and the okubo-weiss parameter fig3: z - z-coordinate (depth) of the domain xcoarse, ycoarse - the same as x and y (x and y coordinates of the simulation) xfine, yfine - interpolated x and y coordinates of the domain into a finer mesh Q3D - 3-dimensional strain rate minus 3-dimensional rotation rate Q_surf - divergent okubo-weiss parameter at the surface (2D strain rate minus vertical vorticity) fig4: note: nodes, saddles and spirals are types of regions at the surface conv_nodes - particle concentrations in convergent nodes conv_saddles - particle concentrations in convergent saddles conv_spirals - particle concentrations in convergent spirals div_nodes - particle concentrations in divergent nodes div_saddles - particle concentrations in divergent saddles div_spirals - particle concentrations in divergent spirals ndtimes - non-dimensional times total - total concentration at the surface fig5: conv/div nodes/saddles/spirals - the same as in fig4 but for steady-state beta - the rise velocity divided by the Deardorff convective velocity fig6: X and Y - same as in fig3 conc_maps - concentration at the surface conditioned to X, Y pairs fig7 and fig8: Q - divergent okubo-weiss parameter at the surface conc_surf - surface particle concentration zeta - vertical vorticity at the surface fig9: w2 - vertical velocity variance u2 - streamwise velocity variance v2 - crosswise velocity variance w3 - vertical velocity skewness wT - vertical turbulent heat flux z_uv_nodes - vertical coordinates at the centers of the discretization cube z_w_nodes - vertical coordinates at the faces of the discretization cube

Individual Files: