The dataset contains the *.gif animations of the numerical results from the far-field modeling study of the 2010 Deepwater Horizon oil spill in the Gulf of Mexico. Oil concentrations are from the experiments that used the latest updated version of the oil application of the Connectivity Modeling System (CMS) or oil-CMS. The animations show time evolution of layer-averaged oil concentrations for the several layers spanning the entire water column, as follows: 0-1m, 1-20m, 20-400m, 400-1000m, 1000-1200m, and below 1200m. Additional visualization of the 3D structure of the plume could be viewed from the time lapse sequence of the three (3) isosurfaces of oil concentrations of 10, 100, and 1000 ppb, focused over the blowout location, overlaid by the surface oil concentrations above the plume. The oil concentrations shown are daily average values in units of ppb. CMS has a Lagrangian, particle-tracking framework, computing particle evolution and transport in the ocean interior. In this version of the oil-CMS, the specified hydrocarbon pseudo-components are in the same droplet. CMS simulation start date: April 20, 2010, 0000 UTC, and particles were tracked for 167 days. Oil particles release location: 28.736N, 88.365W, depth is 1222m or 300m above the oil well. 3000 particles were released every 2 hours, for 87 days, equivalent to total of 3132000 oil particles released during the simulation. Initial particle sizes were determined at random by the CMS in the range of 1-500 micron. Each particle contained three (3) pseudo-components accounting for the differential oil density as follows: 10% of light oil with the density of 800kg/m^3, 75% of the oil with 840 kg/m^3, and 15% of a heavy oil with 950 kg/m^3 density. The half-life decay rates of oil fractions were 30 days, 40 days, and 180 days, respectively. The surface evaporation half-life was set to 250 hours; horizontal diffusion was set to 10 m^2/s in the present case. Ocean hydrodynamic forcing for the CMS model was used from the HYbrid Coordinate Ocean Model (HYCOM) for the Gulf of Mexico region on a 0.04-deg. horizontal grid and 40 vertical levels from the surface to 5500m. It provided daily average 3-D momentum, temperature and salinity forcing fields to the CMS model. The surface wind drift parameterization used surface winds and wind stressed from the 0.5-degree Navy Operational Global Atmospheric Prediction System (NOGAPS). The transport and evolution of the oil particles were tracked by the oil-CMS model during the 167 days of the simulation, recording each particle’s horizontal position, depth, diameter, and density into the model output every 2 hours. Model data need to be post-processed to obtain oil concentrations estimates. The post-processing algorithm took into the account the total amount of oil spilled during the 87-day incident as estimated from the reports (730000 tons), and the assumptions about the oil particle size distribution at the time of the release as estimated in the prior studies. The current dataset assumes the oil was not treated with the chemical dispersants, and the modal peak in initial particle distribution is between 50-70 micron. Post-processed oil concentrations were used to create *.gif animations using Matlab software package, v. R2016b and v2017a. Surface or layer-average ocean currents for corresponding days were computed from the same dataset of HYCOM hydrodynamic data used in a CMS experiment. Oil concentration and oil mass data can be found in GRIIDC dataset R4.x267.000:0084 doi:10.7266/N7KD1WDB. Numerical simulations and post-processing were performed using a Pegasus supercomputer at the Center of Computational Science, University of Miami, in 2017.


Supplemental Information

Data visualization animations oil concentration (ppb) across the northern Gulf of Mexico and at depth (km) OilConc_DWHwinds_0_1m_UVsfc_untreated.gif: Vertical layers 0-1 m, Untreated oil + surface currents OilConc_DWHwinds_1_20m_UVav_untreated.gif: Vertical layers 1-20 m, Untreated oil + depth averaged currents OilConc_DWHwinds_2lays_UVav_larger.gif: Vertical layers 0-1 m and 1-20 m, Untreated oil + depth averaged currents OilConc_DWHwinds_4lays_UVav_4p.gif: Vertical layers 20-1200 m and below 1200 m, Untreated oil + depth averaged currents OilConc3D_DWHcontrol_3iso_sfc.gif: Deepwater horizon subsurface oil concentrations, 3D visualization |The *.gif animations are prepared using the Matlab software, using the data of the time-space distribution of the oil concentrations, obtained as follows. The output from the updated oil-CMS model contains the 3-D location of oil particles, their size and density. It is further processed in order to obtain the oil concentrations in the time-space. The information used for that purpose is the following i) the total oil released during the case study, estimated as 730000 tons of crude oil; ii) the total number of particles released, 3132000 particles; iii) adopted droplet size distribution (DSD) at the time of release, for the untreated oil with no dispersants added. Knowing the i) and ii), yields the amount of oil of 233kg of oil that each released particle represents under the assumption of uniform distribution from 1-500 micron. A single particle therefore represents different amount of oil mass in different modal distributions. Here for untreated oil, i.e. not treated with chemical dispersants, we used the DSD with a modal peak between 50-70 microns and a range of 1-500 micron, following Li et al. (2008). The DSD is approximated with a binned distribution and particles falling within each individual bin are assumed to represent the same amount of oil for that bin; this value would vary for each bin. The post-processing method of computing the daily average oil concentrations includes the following: 1) estimate the mass of oil represented by each bin of the modal distribution; 2) compute the scaling factor for each particle at the initial time depending on particle mass; 3) multiply the evolving particle mass by the initial scaling factor unique for each particle; 4) sum the mass of all the particles found in a given 3-D grid box at a given time (2h intervals); 5) determine the oil concentration from the mass of oil in the volume of an ocean grid box, take into the account the bathymetry for coastal areas; 6) Compute daily average oil concentrations from 2-h concentration estimates.|1. Matlab software version R2016a or R2017a was used for preparing the animations, for obtaining the oil concentrations from the oil-CMS model output, and for storing the data in a commonly used NetCDF format. 2. Numerical model used in experiments is the updated versions of the open-source Connectivity Modeling System (CMS v.2.0) and of the oil module (not open-source) where the multi-fraction algorithm represents all the hydrocarbon compounds within a single droplet. 3. All numerical work has been done using a Pegasus supercomputer at the Center of Computational Science, University of Miami. 4. The dataset files are in *.gif format. All the files have been archived in a *.zip file.|Time scale for the 3D oil concentrations: daily averages Horizontal grid: 0.02-degree spacing. Vertical grid: 0-2500m with 20-m increments, except the top two layers bounded as follows: 0-1m and 1-20m. Layer-average data: vertical layers as specified by the layer boundaries||References for the CMS model: Paris C.B., J. Helgers, E. van Sebille, and A. Srinivasan, 2013: Connectivity Modeling System: A probabilistic modeling tool for the multi-scale tracking of biotic and abiotic variability in the ocean. Environmental Modelling & Software, 42, 47-54. Reference for the previous version of oil-CMS model: Paris., C.B., M. Le Hénaff, Z.M. Aman, A. Subramaniam, J. Helgers, D.-P. Wang, V.H. Kourafalou, and A. Srinivasan, 2012: Evolution of the Macondo Well Blowout: Simulating the Effects of the Circulation and Synthetic Dispersants on the Subsea Oil Transport. Environ. Sci. Technol., 46, 13293−13302. http://dx.doi.org/10.1021/es303197h Reference for droplet size distribution (DSD) analysis study: Li, Z., K. Lee, T. King, M.C. Boufadel, A.D.Venosa, 2008: Oil droplet size distribution as a function of energy dissipation rate in an experimental wave tank. Conference: International Oil Spill Conference, DOI: 10.7901/2169-3358-2008-1-621.


To provide visualization of the oil plume and oil transport from the state-of-the-art modeling results of the far-field hindcast simulations of the 2010 Deepwater Horizon oil spill. To be used for demonstrational purposes, as well as for visual analysis of the oil transport, concentration values, and the areas affected. Overlaid vectors of surface or layer-averaged currents highlight major Gulf of Mexico circulation features that drive the oil particles transport.


oil spill visualization, oil transport, far-field oil modeling, Deepwater Horizon 2010 oil spill modeling, spatial and temporal oil distribution, deep sea oil distribution, Connectivity Modeling System, daily oil concentrations, subsurface hydrocarbon transport, Macondo Well




March 2018

Point of Contact


Natalie Perlin


University of Miami / Center for Computational Science


Claire B. Paris-Limouzy


University of Miami / Rosenstiel School of Marine and Atmospheric Science

Funding Source




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