Three-dimensional daily oil concentrations and oil mass estimates in the Gulf of Mexico from the modeling of the Deepwater Horizon 2010 oil spill using a Connectivity Modeling System

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. In this version, 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, as well as time evolution of the horizontally-cumulative oil mass, all of the data for the 167-day simulation period. CMS has a Lagrangian, particle-tracking framework, computing particle evolution and transport in the ocean interior. 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. The data for the oil concentrations are daily average values in ppb units; the oil mass units are kg of crude oil. Horizontal 0.02-degree grid covers the entire Gulf of Mexico domain and beyond (18.0N-30.8N, 96.0W-77.0W), and 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. Layer-averaged daily oil concentrations are also given for the following vertical layers: 0-1m, 1-20m, 0-20m, 20-400m, 400-1000m, 1000-1200m, and below 1200m. The data for horizontally-cumulative oil mass are in units of kg of crude oil, distributed in the water column on a vertical grid from the surface down to 2500m at 20m increments, and estimated bi-hourly corresponding to the oil-CMS model output interval. Post-processed NetCDF files were created using Matlab software package, v. R2016b. The data files with the 3-D data used compression capability of the NetCDF to keep file size small; maximum compression, or ‘DeflateLevel’ = 9 was used. Numerical simulations and post-processing were performed using a Pegasus supercomputer at the Center of Computational Science, University of Miami, in 2017.