The Movement of Oil Spills

Schwartzberg, Henry G.

doi:10.7901/2169-3358-1971-1-489

Cited by 26 publications

(10 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The empirical surface wind drift factor of 2% was strictly necessary to reproduce the observations because the easternmost part of the observed E80 surface slick moved eastward faster than the model could reproduce using drifter currents and Stokes drift alone. The resulting eastward surface drift, corresponding to about 3.5% of the wind speed (including Stokes drift of about 1.5% of the wind speed), is in good agreement with both empirical observations of Schwartzberg [] and the observed trajectories of the iSphere drifters (Figure ), which are designed to drift like surface oil. Whereas the Stokes drift is both well understood and well modeled, the physical mechanism behind this additional direct wind drift is not clear.…”

Section: Model Fit To Slick Evolutionsupporting

confidence: 87%

“…The isolated effect of this process on the larger spatial and temporal scales considered here is not well known, and cannot easily be distinguished from the overall effect of other turbulent processes (e.g., Langmuir turbulence), making the problem very complicated. Considering in addition that Schwartzberg [] found no dependence of the wind drift factor on oil properties, we find it reasonable to use the same constant wind drift factor for both oil types. For the plant oil, the surface windage did not make a significant difference in any case because the oil particles spent much more time entrained than at the surface.…”

Section: Model Fit To Slick Evolutionmentioning

confidence: 74%

“…The horizontal movement of the elements is the sum of three contributions: elements follow (1) the ambient current, (2) wave‐induced Stokes drift, and (3) elements at the ocean surface (“slick”) are subject to an additional direct wind drag that is a fraction of the surface wind, normally set at 2%. The latter “windage” adds to the surface Stokes drift, typically 1.5% of the wind speed [ Kenyon , ; Ardhuin et al ., ], to match the empirical finding that surface oil slicks drift with ∼3.5% of the wind speed [e.g., Schwartzberg , ]. Note that this windage is in addition to the Ekman drift and tidal motion, which are included in the ambient current.…”

Section: Openoil Drift Modelmentioning

confidence: 91%

See 2 more Smart Citations

Measurement and modeling of oil slick transport

et al. 2016

View full text Add to dashboard Cite

Transport characteristics of oil slicks are reported from a controlled release experiment conducted in the North Sea in June 2015, during which mineral oil emulsions of different volumetric oil fractions and a look‐alike biogenic oil were released and allowed to develop naturally. The experiment used the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) to track slick location, size, and shape for ∼8 h following release. Wind conditions during the exercise were at the high end of the range considered suitable for radar‐based slick detection, but the slicks were easily detectable in all images acquired by the low noise, L‐band imaging radar. The measurements are used to constrain the entrainment length and representative droplet radii for oil elements in simulations generated using the OpenOil advanced oil drift model. Simultaneously released drifters provide near‐surface current estimates for the single biogenic release and one emulsion release, and are used to test model sensitivity to upper ocean currents and mixing. Results of the modeling reveal a distinct difference between the transport of the biogenic oil and the mineral oil emulsion, in particular in the vertical direction, with faster and deeper entrainment of significantly smaller droplets of the biogenic oil. The difference in depth profiles for the two types of oils is substantial, with most of the biogenic oil residing below depths of 10 m, compared to the majority of the emulsion remaining above 10 m depth. This difference was key to fitting the observed evolution of the two different types of slicks.

show abstract

Section: Model Fit To Slick Evolutionsupporting

confidence: 87%

Section: Model Fit To Slick Evolutionmentioning

confidence: 74%

Section: Openoil Drift Modelmentioning

confidence: 91%

See 1 more Smart Citation

Measurement and modeling of oil slick transport

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Together with the Stokes drift (typically 1.5% of the wind at the surface), this sums up to the commonly found empirical value of 3.5% of the wind (Schwartzberg, 1971). …”

supporting

confidence: 66%

OpenDrift v1.0: a generic framework for trajectory modeling

Dagestad¹,

Röhrs²,

Breivik³

et al. 2017

Preprint

View full text Add to dashboard Cite

Abstract.OpenDrift is an open-source Python-based framework for Lagrangian particle modeling under development at the Norwegian Meteorological Institute with contributions from the wider scientific community. The framework is highly generic and modular, and is designed to be used for any type of drift calculations in the ocean or atmosphere. A specific module within the OpenDrift framework corresponds to a Lagrangian particle model in the traditional sense. A number of modules 5 have already been developed, including an oil drift model, a stochastic search and rescue model, a pelagic egg model, and a basic module for atmospheric drift. The framework allows for the ingestion of an unspecified number of forcing fields (scalar and vectorial) from various sources, including Eulerian ocean, atmosphere and wave models, but also measurements or subjective estimates of the same variables. A basic backtracking mechanism is inherent, using sign reversal of the total 10 displacement vector and negative time stepping. OpenDrift is fast and simple to set up and use on Linux, Mac and Windows environments, and can be used with minimal or no Python experience.It is designed for flexibility, and researchers may easily adapt or write modules for their specific purpose. OpenDrift is also designed for performance, and simulations with millions of particles may be performed on a laptop. Further, OpenDrift is designed for robustness, and is in daily operational 15 use for emergency preparedness modeling (oil drift, search and rescue and drifting ships) at the Norwegian Meteorological Institute.

show abstract

“…Lagrangian tools fall in two broad categories: either the trajectories are computed along with the velocity fields as part of the ocean or atmospheric circulation model, e.g. socalled floats in the regional ocean modelling system (ROMS) (Shchepetkin and McWilliams, 2005). This is known as "online" trajectory computations and has the advantage that no separate model is needed.…”

Section: Introductionmentioning

confidence: 99%

OpenDrift v1.0: a generic framework for trajectory modelling

et al. 2018

View full text Add to dashboard Cite

Abstract. OpenDrift is an open-source Python-based framework for Lagrangian particle modelling under development at the Norwegian Meteorological Institute with contributions from the wider scientific community. The framework is highly generic and modular, and is designed to be used for any type of drift calculations in the ocean or atmosphere. A specific module within the OpenDrift framework corresponds to a Lagrangian particle model in the traditional sense. A number of modules have already been developed, including an oil drift module, a stochastic search-and-rescue module, a pelagic egg module, and a basic module for atmospheric drift. The framework allows for the ingestion of an unspecified number of forcing fields (scalar and vectorial) from various sources, including Eulerian ocean, atmosphere and wave models, but also measurements or a priori values for the same variables. A basic backtracking mechanism is inherent, using sign reversal of the total displacement vector and negative time stepping. OpenDrift is fast and simple to set up and use on Linux, Mac and Windows environments, and can be used with minimal or no Python experience. It is designed for flexibility, and researchers may easily adapt or write modules for their specific purpose. OpenDrift is also designed for performance, and simulations with millions of particles may be performed on a laptop. Further, OpenDrift is designed for robustness and is in daily operational use for emergency preparedness modelling (oil drift, search and rescue, and drifting ships) at the Norwegian Meteorological Institute.

show abstract

The Movement of Oil Spills

Cited by 26 publications

References 0 publications

Measurement and modeling of oil slick transport

Measurement and modeling of oil slick transport

OpenDrift v1.0: a generic framework for trajectory modeling

OpenDrift v1.0: a generic framework for trajectory modelling

Contact Info

Product

Resources

About