We have assessed the use of satellite derived currents to calculate oceanic surface drift, as an alternative to using currents from ocean models. Predicted trajectories are compared to observed ...trajectories of two types of drifting buoys, which are subject to different degree of wind and wave forcing, in addition to the ocean surface current. This variable degree of ocean-, wind- and wave forcing is highly relevant for the practical problem of predicting the drift of e.g. oil to aid cleanup operations, and the drift of floating objects to aid search and rescue operations. The calculated trajectories are evaluated in terms of separation distance, and a calculated skill score. For the submerged drifters (CODE/DAVIS), we find that a high resolution non-assimilated ocean model gives the best results, whereas a coarser scale assimilated model performs similarly to satellite derived surface currents from the GlobCurrent project (geostrophic + Ekman components). For the wind-exposed drifters (iSphere), the wind-drift contribution is found to be dominating, and there is only a small impact of using any of the available information about ocean currents. The wind drift contribution to the iSphere drift is estimated to be 3% of the wind if Stokes drift is included in the calculations, and 4% if the Stokes drift is not included. Including Stokes drift in the calculations gives improvement for the submerged drifters, but shows no improvement for the wind exposed drifters.
•Satellite derived currents are found to be useful for ocean trajectory forecasting.•Ocean currents represent the largest uncertainty in ocean trajectory forecasting.•Ocean surface drift may be fairly well predicted from wind only.
In oil spill models, vertical mixing due to turbulence is commonly modelled by random walk. If the eddy diffusivity varies with depth, failing to take the derivative of the diffusivity into account ...in the random walk scheme will lead to incorrect results. Depending on the diffusivity profile, the result may be either over- or underprediction of the amount of surfaced oil. The importance of using consistent random walk schemes has been known for decades in, e.g., the plankton modelling community. However, it appears not to be common knowledge in the oil spill community, with inconsistent random walk schemes appearing even in recent publications. We demonstrate and quantify the error due to inconsistent random walk, using a simplified oil spill model, and two different diffusivity profiles. In the two cases considered, a commonly used inconsistent scheme predicts respectively 58% and 176% the amount of surface oil, compared to a consistent scheme.
•For variable diffusivity, inconsistent random walk schemes cause systematic errors.•We provide a complete and detailed description of a simplified 1D oil spill model.•We show that an inconsistent scheme gives large errors in surfaced oil mass.
Drift in the uppermost part of the ocean Röhrs, Johannes; Christensen, Kai H.
Geophysical research letters,
16 December 2015, Letnik:
42, Številka:
23
Journal Article
Recenzirano
Odprti dostop
Lagrangian drift velocities within the uppermost meter of the ocean mostly depend on the local wind forcing, turbulent mixing, and waves. While the interior part of the Ekman layer has been ...extensively studied using drogued drifters, the drift at—or very close to—the surface is less investigated. The wind response of surface currents on time scales from 1 h to 10 days is analyzed using two types of satellite‐tracked drifters: (i) spherical floats on the surface and (ii) drifters with a drogue centered at 70 cm depth. The response of drifting objects to wind and wave forcing is highly dependent on the vertical position, even within the upper meter of the ocean. The surface drifters are wind coherent for both cyclonic and anticyclonic subinertial frequencies. In contrast, the subsurface drift responds primarily to anticyclonic forcing that resonates with the intrinsic ocean dynamics.
Key Points
Drifters at the surface respond similarly to cyclonic and anticyclonic forcing
Subsurface drifters respond primarily to forcing that resonates with the ocean
The wind coherence is very low between the inertial frequency and 1 cph
Lagrangian particle models are used for many applications in the ocean sciences, including transport modelling of oil spills, fish eggs and larvae, plastics, and sediment particles. In the context of ...oil spill modelling, there are numerous papers discussing entrainment of surface oil by breaking waves. However, for the opposite process, i.e., droplets reaching the surface and joining the surface slick, we have found no discussion in the literature of the exact steps involved. Given the wide use of particle-based models in oil spill modelling, it is important to establish a consistent recipe for treating the surface boundary.
We investigate a Lagrangian particle model for the vertical transport, surfacing and resuspension of buoyant material in the water column. By modifying the behaviour at the surface boundary, the model can be applied to materials such as oil droplets, that form a surface slick, and hence see the surface as an absorbing boundary, and to particles that do not form a surface slick, such as fish eggs and microplastics. For slick-forming materials, we also consider resuspension from the surface slick, (e.g., entrainment of surface oil by breaking waves). While we restrict our attention to positively buoyant materials, the model is equally applicable to the settling of negatively buoyant particles, such as sediment grains and marine snow.
We consider three case studies, each designed to allow a detailed and direct comparison of the Lagrangian model to an Eulerian model based on numerical solution of the advection–diffusion–reaction equation. We demonstrate that the two models give the same results when the boundary at the surface is treated correctly.
•We analyse a Lagrangian particle model for vertical mixing, surfacing and resuspension of buoyant particles.•We formulate an equivalent Eulerian model based on direct numerical solution of the advection–diffusion equation.•The treatment of the boundary at the surface is discussed in particular detail for both models.•We demonstrate the equivalence of the two models for cases representing fish eggs, oil droplets, and oil with resuspension.
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.
Plastic litter is accumulating on pristine northern European beaches, including the European Arctic, and questions remain about the exact origins and sources. Here we investigate plausible fishery ...and consumer-related sources of beach littering, using a combination of information from expert stakeholder discussions, litter observations and a quantitative tool - a drift model - for forecasting and backtracking likely pathways of pollution. The numerical experiments were co-designed together with practice experts. The drift model itself was forced by operational ocean current, wave and weather forecasts. The model results were compared to a database of marine litter on beaches, collected every year according to the standardized monitoring program of the Oslo/Paris Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR). By comparing the heterogeneous beach observations to the model simulations, we are able to highlight probable sources. Two types of plastic are considered in the simulations: floating plastic litter and submerged, buoyant microplastics. We find that the model simulations are plausible in terms of the potential sources and the observed plastic litter. Our analysis results in identifiable sources of plastic waste found on each beach, providing a basis for stakeholder actions.
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•By using oceanic backtracking simulations, potential sources of observed litter at OSPAR beaches are identified.•Simulated sources of marine plastic fit well with the classification of observed plastic litter types.•It is highly probable that most of the litter observed on the Arctic OSPAR beaches originates from regional fishing areas.•Marine plastic originating in central Europe takes more than a year to reach the Arctic by oceanic drift.•Marine (macroscopic) litter is transported faster than microplastics, and in more diverse directions.
An operational ocean Ensemble Prediction System (EPS) for the coastal seas off Northern Norway is evaluated by comparing with high-frequency radar current speed estimates. The EPS is composed of 24 ...members for which the ocean current is not perturbed nor constrained but forced with an atmosphere ensemble. The ocean ensemble spread stems from (i) accumulated differences in wind-forcing history and (ii) constraints of sea surface temperature by data assimilation. The intention of the ensemble is to reflect the actual uncertainty in initial conditions, which are largely unknown in terms of mesoscale circulation. We find a low but pronounced predictive skill in surface currents along with a good statistic skill. Additionally, current speeds show deterioration of the validation metrics over the forecast range. Further, high-resolution wind forcing seems to provide better forecast skill in currents compared to lower resolution forcing. In general, the ensemble exhibits the ability to predict forecast uncertainty.
Knowledge of upper ocean currents is needed for trajectory forecasts and is essential for search and rescue operations and oil spill mitigation. This paper addresses effects of surface waves on ocean ...currents and drifter trajectories using in situ observations. The data set includes colocated measurements of directional wave spectra from a wave rider buoy, ocean currents measured by acoustic Doppler current profilers (ADCPs), as well as data from two types of tracking buoys that sample the currents at two different depths. The ADCP measures the Eulerian current at one point, as modelled by an ocean general circulation model, while the tracking buoys are advected by the Lagrangian current that includes the wave-induced Stokes drift. Based on our observations, we assess the importance of two different wave effects: (a) forcing of the ocean current by wave-induced surface fluxes and the Coriolis–Stokes force, and (b) advection of surface drifters by wave motion, that is the Stokes drift. Recent theoretical developments provide a framework for including these wave effects in ocean model systems. The order of magnitude of the Stokes drift is the same as the Eulerian current judging from the available data. The wave-induced momentum and turbulent kinetic energy fluxes are estimated and shown to be significant. Similarly, the wave-induced Coriolis–Stokes force is significant over time scales related to the inertial period. Surface drifter trajectories were analysed and could be reproduced using the observations of currents, waves and wind. Waves were found to have a significant contribution to the trajectories, and we conclude that adding wave effects in ocean model systems is likely to increase predictability of surface drifter trajectories. The relative importance of the Stokes drift was twice as large as the direct wind drag for the used surface drifter.
Geophysical models are cornerstone pieces in marine forecasting of floating objects and pollution, such as marine surface oil slicks. Trajectory forecasts of oil spills inherit the uncertainties from ...the underlying geophysical forcing. In this work we compare the forecast capabilities of an ocean ensemble prediction system (EPS) to those from a higher resolution deterministic model on the representation of oil slick drift. As reference, we use produced water (PW) slicks detected and delineated from 41 C–band Sentinel-1A/B satellite synthetic aperture radar images between April and December, 2021. We found that the EPS provided at least equivalent member-wise results relative to simulations forced with the deterministic model. Ensemble verification through rank histograms and spread-error relationship showed that including the ocean fields is necessary to address model uncertainties. Whether considering the ocean field or not, the modeled slicks were counterclockwise rotated between 20° and 30° relative to the ones observed in the satellite images, and these were deflected about 45° to the right of the observed wind direction.
The transport of pelagic plankton by wind-driven ocean currents and surface gravity waves is investigated for the example of Northeast Arctic cod eggs and larvae on the coast of northern Norway. ...Previous studies indicate that the wave-induced drift (i.e., Stokes drift) is relevant for the transport of particles in the upper ocean. We use an ocean general circulation model together with a numerical wave prediction model and a Lagrangian particle tracking model to calculate trajectories of fish eggs and larvae. Waves are considered not only for particle drift but also for the air–sea momentum flux, its contribution to the Coriolis force, and vertical mixing. The sample species provides the advantage that many of its physical and behavioral properties are well known (e.g., egg buoyancy), allowing investigation of vertical particle displacement by turbulent mixing in response to wind forcing and wave breaking. The approach accounting for particle mixing by breaking waves enhances agreement between observed and modeled egg profiles. Results also show a general shoreward transport of particles by the Stokes drift. This wave drift exhibits a more constant direction than the Eulerian current and hence stabilizes particle diffusion to favor a dominant direction. For the case of Northeast Arctic cod, waves concentrated model eggs and larvae on average 1.5 km closer to shore, which is 20% of their total distance to the coast. This increases the residence time of first-feeding larvae close to the spawning areas compared to earlier models.
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