Abstract:

This dataset reports the modelling of oil droplets transport in the upper ocean under the effect of eddy diffusivity by modelling. The transient position of droplets and the concentration of droplets were calculated and compared between uniform eddy diffusivity and K-profile parameterization (KPP) model. The results were also confirmed by using the Lagrangian particle tracking model NEMO3D. This dataset supports the publication: Boufadel, M., Liu, R., Zhao, L., Lu, Y., Özgökmen, T., Nedwed, T., & Lee, K. (2020). Transport of Oil Droplets in the Upper Ocean: Impact of the Eddy Diffusivity. Journal of Geophysical Research: Oceans, 125(2). doi:10.1029/2019jc015727

Suggested Citation:

Ruixue Liu. 2020. Dataset for: Transport of Oil Droplets in the Upper Ocean: Impact of the Eddy Diffusivity. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/YFNW5W7Q

Publications:

Boufadel, M., Liu, R., Zhao, L., Lu, Y., Özgökmen, T., Nedwed, T., & Lee, K. (2020). Transport of Oil Droplets in the Upper Ocean: Impact of the Eddy Diffusivity. Journal of Geophysical Research: Oceans, 125(2). doi:10.1029/2019jc015727

Purpose:

To describe the effect of vertical eddy parameterization on oil droplet size distribution and transport of droplets following an oil spill.

Data Parameters and Units:

The data contained in the associated journal article Boufadel et al., 2020 are contained in an Excel spreadsheet, with one worksheet devoted to each figure (Figures 4-11). Figure 4: Initial and steady state mass fraction at the surface as a function of droplet size, DS (Delvigne and Sweeney) correlation. Droplet diameter [m], droplet diameter [um], initial mass concentration [mg/L], steady state mass concentration [mg/L]. Figure 7: Vertical profiles of number concentration based on a uniform vertical eddy diffusivity at varying times, wind speeds, and analytical/numerical solution. Depth (z, [m]), number concentration (t=6 hours, [1/L]), number concentration (t=24 hours, [1/L]). Figure 8: Surface concentration normalized by the initial concentration as a function of time and at two wind speeds. (ratio of rise velocity to diffusivity, Wd/K, [1/m], ratio c/c0 [dimensionless]). Figure 9: Depth distribution of number concentration of 30-um droplets (wind speed = 0.5 m/s) for uniform diffusivity (analytical solution) and KPP (NEMO3D) at 6 hours and 24 hours. Depth (z, [m]), number concentration (t=6 hours, [1/L]), number concentration (t=24 hours, [1/L]). Figure 10. Depth distribution of number concentration of 30-um droplets (wind speed = 2 m/s) for uniform diffusivity (analytical solution) and KPP (NEMO3D) at 6 hours and 24 hours. Depth (z, [m]), number concentration (t=6 hours, [1/L]), number concentration (t=24 hours, [1/L]). Figure 11. Depth distribution of number concentration of 30-um droplets (wind speed = 5 m/s) for uniform diffusivity (analytical solution) and KPP (NEMO3D) at 6 hours and 24 hours. Depth (z, [m]), number concentration (t=6 hours, [1/L]), number concentration (t=24 hours, [1/L]).

Methods:

The transient droplets size distribution were obtained by solving the one-dimensional advection-diffusion equation for non-constant eddy diffusivity. Also, NEMO3D - a Lagrangian particle tracking model based on a random walk approach - was applied.

Provenance and Historical References:

Delvigne, G. A. L., & Sweeney, C. E. (1988). Natural dispersion of oil. Oil and Chemical Pollution, 4(4), 281–310. doi:10.1016/s0269-8579(88)80003-0

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