The DeepWater Horizon Oil Slick: High Resolution Model Simulations of River Front Effects, Initialized and Verified by Satellite Observations

The effect of river fronts on oil slick transport has been demonstrated using high resolution forcing models and a fully fledged oil drift model, OpenOil. The model system is used to simulate the 2010 DeepWater Horizon oil spill. Metocean forcing data are taken from the GoM-HYCOM 1/50° ocean model with realistic river input and ECMWF global forecast products of wind and wave parameters with 1/8° resolution. The simulations are initialized from satellite observations of the surface oil patch. OpenOil includes most of the relevant processes, such as emulsification, evaporation, wave entrainment, stranding and droplet formation. The model takes account of the actual oil type and properties, using the ADIOS oil weathering database of NOAA. The effect of using a newly developed parameterization for oil droplet size distribution is studied and compared to a traditional algorithm. Although the algorithms provide different distributions for a single wave breaking event, it is found that the net difference after long simulations is negligible, indicating that the outcome is robust regarding the choice of parameterization. That indicates that the wave entrainment, vertical mixing and re-surfacing mechanisms that are part of OpenOil are more important for determining the final droplet size spectrum than the spectrum prescribed for individual wave breaking events. In both cases, the size of the droplets controls how much oil is present at the surface and hence are subject to wind and Stokes drift. The effect of removing river outflow in the ocean model is investigated in order to showcase effects of river induced fronts on oil spreading. A consistent effect on the amount and location of stranded oil is found, and considerable impact of river induced fronts is seen on the location of the surface oil patch. During a case with large river outflow (May 20-27, 2010), the total amount of stranded oil is reduced by about 50% in the simulation with no river input. The results compares well with satellite observations of the surface oil patch.

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The DeepWater Horizon Oil Slick: Simulations of River Front Effects and Oil Droplet Size Distribution

Journal of Marine Science and Engineering ◽

10.3390/jmse7100329 ◽

2019 ◽

Vol 7 (10) ◽

pp. 329 ◽

Cited By ~ 2

Author(s):

Lars Robert Hole ◽

Knut-Frode Dagestad ◽

Johannes Röhrs ◽

Cecilie Wettre ◽

Vassiliki H. Kourafalou ◽

...

Keyword(s):

Size Distribution ◽

Droplet Size ◽

Droplet Size Distribution ◽

Deepwater Horizon ◽

Satellite Observations ◽

Oil Droplet ◽

River Input ◽

Oil Slick ◽

River Outflow ◽

Oil Droplet Size

The effect of river fronts on oil slick transport has been shown using high resolution forcing models and a fully fledged oil drift model, OpenOil. The model was used to simulate two periods of the 2010 DeepWater Horizon oil spill. Metocean forcing data were taken from the data-assimilative GoM-HYCOM 1/50 ∘ ocean model with realistic daily river input and global forecast products of wind and wave parameters from ECMWF. The simulations were initialized from satellite observations of the surface oil patch. The effect of using a newly developed parameterization for oil droplet size distribution was studied and compared to a traditional algorithm. Although the algorithms provide different distributions for a single wave breaking event, it was found that the net difference after long simulations is negligible, indicating that the outcome is robust regarding the choice of parameterization. The effect of removing the river outflow was investigated to showcase effects of river induced fronts on oil spreading. A consistent effect on the amount and location of stranded oil and a considerable impact on the location of the surface oil patch were found. During a period with large river outflow (20–27 May 2010), the total amount of stranded oil is reduced by about 50% in the simulation with no river input. The results compare well with satellite observations of the surface oil patch after simulating the surface oil patch drift for 7–8 days.

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Revisiting the DeepWater Horizon spill: High resolution model simulations of effects of oil droplet size distribution and river fronts

10.5194/os-2018-130 ◽

2018 ◽

Cited By ~ 1

Author(s):

Lars R. Hole ◽

Knut-Frode Dagestad ◽

Johannes Röhrs ◽

Cecilie Wettre ◽

Vassiliki H. Kourafalou ◽

...

Keyword(s):

Size Distribution ◽

Droplet Size ◽

Droplet Size Distribution ◽

Deepwater Horizon ◽

Ocean Model ◽

Stokes Drift ◽

Single Wave ◽

Oil Droplet ◽

Resolution Model ◽

Oil Droplet Size

Abstract. An open source ocean trajectory framework, OpenDrift, is used to simulate the 2010 DeepWater Horizon oil spill. Metocean forcing data are taken from the GoM-HYCOM 1/50° ocean model with realistic river input and ECMWF global forecasts of wind and wave parameters with 1/8° resolution. OpenDrift includes the integrated oil drift module OpenOil, which includes a number of relevant processes, such as emulsification, wave entrainment, and droplet formation. This takes account of the actual oil type/properties, using the ADIOS oil weathering database of NOAA. We investigate the effect of using a newly developed parameterization for oil droplet size distribution, compared to a traditional algorithm. Although the algorithms provide different distributions for a single wave breaking event, we find that the net difference after long time simulations is negligible, indicating that the outcome is robust regarding the choice of parameterization. In both cases, the size of the droplets controls how much oil is present at the surface and hence are subject to wind and Stokes drift. The oil droplet sizes are also relevant for the biological impact. Next, the effect of removing river outflow in the ocean model is investigated in order to showcase effects of river induced fronts on oil spreading. A consistent effect on the amount and location of stranded oil is found, and considerable impact is seen on the location of the surface oil patch.

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EnOI-Based Data Assimilation Technology for Satellite Observations and ARGO Float Measurements in a High Resolution Global Ocean Model Using the CMF Platform

Communications in Computer and Information Science - Supercomputing ◽

10.1007/978-3-319-55669-7_5 ◽

2016 ◽

pp. 57-66 ◽

Cited By ~ 4

Author(s):

Maxim Kaurkin ◽

Rashit Ibrayev ◽

Alexandr Koromyslov

Keyword(s):

High Resolution ◽

Data Assimilation ◽

Ocean Model ◽

Satellite Observations ◽

Global Ocean ◽

Argo Float

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Review of "Revisiting the DeepWater Horizon spill: High resolution model simulations of effects of oil droplet size distribution and river fronts"

10.5194/os-2018-130-rc3 ◽

2019 ◽

Author(s):

Anonymous

Keyword(s):

High Resolution ◽

Size Distribution ◽

Droplet Size ◽

Droplet Size Distribution ◽

Deepwater Horizon ◽

Oil Droplet ◽

Model Simulations ◽

Resolution Model ◽

High Resolution Model ◽

Oil Droplet Size

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A Comparison of Ocean Model Results with Satellite Observations during the Development of the strong 1997–98 El Niño

10.5194/os-2019-86 ◽

2019 ◽

Author(s):

David J. Webb ◽

Andrew C. Coward ◽

Helen M. Snaith

Keyword(s):

High Resolution ◽

Rossby Wave ◽

El Niño ◽

El Nino ◽

Ocean Model ◽

Equatorial Pacific ◽

Satellite Observations ◽

Sea Surface ◽

Instability Waves ◽

Tropical Instability Waves

Abstract. Satellite data from the equatorial Pacific is compared with results from a high resolution ocean model during a period including the strong El Niño of 1997–98. The results show that the ocean model realistically captures the changes in sea surface temperature and the propagation of the annual Rossby wave although it may overestimate the reduced energy of tropical instability waves during development of an El Niño. The results provide additional confidence in the oceanic mechanisms which model analysis implicated as being responsible for the development of both the 1982–83 and the 1997–98 El Niños.

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Matchup Characteristics of Sea Surface Salinity Using a High-Resolution Ocean Model

Remote Sensing ◽

10.3390/rs13152995 ◽

2021 ◽

Vol 13 (15) ◽

pp. 2995

Author(s):

Frederick M. Bingham ◽

Severine Fournier ◽

Susannah Brodnitz ◽

Karly Ulfsax ◽

Hong Zhang

Keyword(s):

High Resolution ◽

Time Window ◽

Single Point ◽

Ocean Model ◽

Sea Surface ◽

Sea Surface Salinity ◽

Surface Salinity ◽

Argo Floats ◽

Statistical Measures ◽

Salinity Difference

Sea surface salinity (SSS) satellite measurements are validated using in situ observations usually made by surfacing Argo floats. Validation statistics are computed using matched values of SSS from satellites and floats. This study explores how the matchup process is done using a high-resolution numerical ocean model, the MITgcm. One year of model output is sampled as if the Aquarius and Soil Moisture Active Passive (SMAP) satellites flew over it and Argo floats popped up into it. Statistical measures of mismatch between satellite and float are computed, RMS difference (RMSD) and bias. The bias is small, less than 0.002 in absolute value, but negative with float values being greater than satellites. RMSD is computed using an “all salinity difference” method that averages level 2 satellite observations within a given time and space window for comparison with Argo floats. RMSD values range from 0.08 to 0.18 depending on the space–time window and the satellite. This range gives an estimate of the representation error inherent in comparing single point Argo floats to area-average satellite values. The study has implications for future SSS satellite missions and the need to specify how errors are computed to gauge the total accuracy of retrieved SSS values.

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