Dataset Authors

Claire Paris
Natalie Perlin


The dataset contains the numerical results of the 2010 Deepwater Horizon oil spill incident at Macondo well in the Gulf of Mexico, as estimated from the simulations using the latest updated version of the oil application of the Connectivity Modeling System (CMS) or oil-CMS. This contains additional data that complements the dataset that is available at GRIIDC under Unique Dataset Identifier (UDI) R4.x267.000:0084 (DOI: 10.7266/N7KD1WDB). In this version of the oil-CMS model, the specified hydrocarbon pseudo-components are in the same droplet. The post-processing analysis yielded 4-D spatiotemporal data of the oil concentrations and oil mass on a regular horizontal and vertical grid. There are two sets of simulations that last 167 days and 100 days (a shorter sensitivity run). CMS has a Lagrangian, particle-tracking framework, computing particle evolution and transport in the ocean interior. CMS simulations start date: April 20, 2010, 0000 UTC, and particles were tracked for 167 days or 100 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 a 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, and are scaled during post-processing to represent the chosen droplet size distribution (DSD). Each particle contained three (3) pseudo-components accounting for the differential oil density as follows: 10% of light oil with a density of 800kg/m^3, 75% of the oil with 840 kg/m^3, and 15% of 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 main simulation (100 days for a sensitivity run), recording each particle’s horizontal position, depth, diameter, and density into the model output every 2 hours. Model data needed to be post-processed to obtain oil concentrations and oil mass estimates. The post-processing algorithm took into 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 contains post-processed gridded and non-gridded analyses for the cases of untreated oil and cases of oil treated with the chemical dispersants at the oil release location.


Supplemental Information

The main parameters included are - Time, Days after the initial blowout, (days), lat, latitude position of a grid cell center, (degrees north); lon, longitude position of a grid cell center, (degrees east); depth, bathymetry (depth) of a regular 2D grid, (meters); zlevs_bnd, vertical level bounds, (meters); zlevs, mid-depth of the vertical levels, (meters); oil_mass, the area-cumulative mass of crude oil in a vertical layer at a given time, (kg); Days after an initial blowout (days), oil_conc, oil concentration, (ppb, parts per billion). Non-gridded *.txt files with sedimented or beached oil mass – in kg. The naming convention of the files is as follow: 1) files with the string “DWHcontrol” or “untreated” are for the untreated oil; 2) files containing a string “treated” are for the cases assuming the chemical dispersant use. Note that the cases with “DWHcontrol” and “DWH_treated” are complementary for the GRIID-C dataset R4.x267.000.0084 (DOI: 10.7266/N7KD1WDB). In the “DWHcontrol” case the modal peak in the initial DSD is between 50-70 micron; in the “DWH_treated” case the modal peak is between 10-20 micron. In the suite of 100-day sensitivity simulations, “DWH_logDSD_untreated” and “DWH_logDSD2_untreated”, the initial DSD is scaled to log-normal, with the standard parameters mu=117 micron, and sigma=0.72, for the droplet range 1-500 micron. In the “DWH_logDSD_treated” and “DWH_logDSD2_treated”, the initial DSD is scaled to log-normal with the mu=69 micron, and sigma=0.82, for the droplet range 1-500 micron. The oil-CMS time step is the 1200s in “DWHcontrol”, “DWH_treated”, and in all “DWH_logDSD_” simulations; the time step is reduced to 120s in the simulations labeled “DWH_logDSD2”. The data for the oil concentrations (3-D oil mass) are daily average values in ppb units; the oil mass units are kg of crude oil. The horizontal 0.02-degree grid covers the entire Gulf of Mexico domain and beyond (18.0N-30.8N, 96.0W-77.0W), and the vertical grid extends from the surface to the depth of 2500m at 20m increments, except for the top two layers which are 0-1m and 1-20m. All the files containing surface concentrations (0-1m) cover a larger domain, extending westward to 98W; all the 3-D files for the “DWH_logDSD” cases cover the entire Gulf of Mexico domain as well and contain an additional bottom layer of concentrations below 2500m. Post-processed NetCDF files were created using Matlab software package, R2016b and R2017a. The data files were created using the compression capability of the NetCDF to keep the file size small; maximum compression or ‘DeflateLevel’ = 9 was used. Additional non-gridded files contain sedimented oil mass that reached the ocean floor/beach and no longer is transported by the oil-CMS model. The data are in .txt files for “DWH_logDSD” runs; the sedimented data for the “DHWcontrol” case is contained in the GRIID-C dataset R4.x267.000:0084 (DOI: 10.7266/N7KD1WDB). The data represents the scaled oil mass (in kg) for a given droplet. Note that the data are non-gridded and minimally post-processed, and presented in a particle-tracking framework. The format of the *landed.txt files is as follows: 1st column - time in seconds from the beginning of the run (i.e., onset of the blowout); 2nd column - depth where the particle landed/sedimented; 3rd column - latitude position of the landing site; 4th column - longitude position of the landing site; 5th column - oil mass in kg. In order to obtain a gridded data, or to find a summary of oil at any particular location and/or time frame, the sum of all particles that reach a given location or given time cell needs to be done, across all the output data entries (lines). Numerical simulations and post-processing were performed using a Pegasus supercomputer at the Center of Computational Science, University of Miami, in 2017-2019.|The website for the main CMS code could be found at The oil-CMS module is still under development. The numerical modeling output of the oil-CMS representing the trajectory, history, and attribute of individual oil droplets will be post-processed to compute the spatio-temporal evolution of mass-conserved oil concentrations. The oil concentrations shown are in daily average values in units of ppb, the daily oil mass is in kg. The time scale for the 3D oil concentrations and oil mass is in daily averages. Horizontal grid: 0.02-degree spacing. Vertical grid for 0-2500m has 20-m increments, except the top two layers bounded as follows: 0-1m and 1-20m; vertical grid in files indicating the lower boundary of 4500m contains an additional layer of oil concentrations below 2500m. Layer-average data: vertical layers as specified by 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 the 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. 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 Proceedings, 2008(1), 621–626. . Reference describing the control ("DWHcontrol" ) scenario, postprocessing approach, and different sensitivity studies: Perlin N., C.B. Paris, I.Berenshtein, A.C. Vaz, R. Faillettaz, Z.M. Aman, P.T. Schwing, I.C. Romero, M. Schlüter, A. Liese, N. Noirungsee, and S. Hackbusch, 2020: Far-Field Modeling of a Deep- Sea Blowout: Sensitivity Studies of Initial Conditions, Biodegradation, Sedimentation, and Subsurface Dispersant Injection on Surface Slicks and Oil Plume Concentrations. In: Murawski, S. et al. (eds.) Deep Oil Spills. Facts, Fate, and Effects. Springer, Cham,


This data was computed to provide a spatio-temporal 4-D simulation of the Deepwater Horizon oil spill in the form of spatially gridded daily oil concentrations and daily oil mass in each 3-D grid box. It provides state-of-the-art modeling data of the far-field hindcast simulations, serving as a base ("control") case for untreated oil simulation. To be used for comparative analysis with the observations, other validation techniques, as well as with other modeling efforts in sensitivity studies. To be used as spatiotemporal input data for ecosystem modeling applications.


Deepwater Horizon, Oil spill transport and fate, Oil spill Modeling, Hindcast, Oil concentrations, Connectivity Modeling System (CMS)




August 2022

Point of Contact


Claire B. Paris-Limouzy


University of Miami / Rosenstiel School of Marine and Atmospheric Science


Natalie Perlin


University of Miami / Center for Computational Science

Funding Source




Rights Information

Creative Commons License
This work is licensed under a Creative Commons Public Domain Dedication 1.0 License.