MEDSLIK-II, a Lagrangian marine surface oil spill model for short-term forecasting – Part 1: Theory

Dominicis, Michela De; Pinardi, Nadia; Zodiatis, George; Lardner, R. W.

doi:10.5194/gmd-6-1851-2013

Cited by 166 publications

(114 citation statements)

References 50 publications

(46 reference statements)

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“…An extrapolation procedure (De Dominicis et al, 2013) is used to prevent the presence of missing values interpolating the oceanic fields over the new higher-resolution grid. Two experiments are used: the first (SANIFS-v0) considers the nested model initialized only with temperature and salinity fields from MFS.…”

Section: Initialization Procedures and Spin-up Timementioning

confidence: 99%

Coastal ocean forecasting with an unstructured grid model in the southern Adriatic and northern Ionian seas

Federico

Pinardi

Coppini

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. SANIFS (Southern Adriatic Northern Ionian coastal Forecasting System) is a coastal-ocean operational system based on the unstructured grid finite-element threedimensional hydrodynamic SHYFEM model, providing short-term forecasts. The operational chain is based on a downscaling approach starting from the large-scale system for the entire Mediterranean Basin (MFS, Mediterranean Forecasting System), which provides initial and boundary condition fields to the nested system.The model is configured to provide hydrodynamics and active tracer forecasts both in open ocean and coastal waters of southeastern Italy using a variable horizontal resolution from the open sea (3-4 km) to coastal areas (50-500 m).Given that the coastal fields are driven by a combination of both local (also known as coastal) and deep-ocean forcings propagating along the shelf, the performance of SAN-IFS was verified both in forecast and simulation mode, first (i) on the large and shelf-coastal scales by comparing with a large-scale survey CTD (conductivity-temperature-depth) in the Gulf of Taranto and then (ii) on the coastal-harbour scale (Mar Grande of Taranto) by comparison with CTD, ADCP (acoustic doppler current profiler) and tide gauge data.Sensitivity tests were performed on initialization conditions (mainly focused on spin-up procedures) and on surface boundary conditions by assessing the reliability of two alternative datasets at different horizontal resolution (12.5 and 6.5 km).The SANIFS forecasts at a lead time of 1 day were compared with the MFS forecasts, highlighting that SANIFS is able to retain the large-scale dynamics of MFS. The largescale dynamics of MFS are correctly propagated to the shelfcoastal scale, improving the forecast accuracy (+17 % for temperature and +6 % for salinity compared to MFS). Moreover, the added value of SANIFS was assessed on the coastalharbour scale, which is not covered by the coarse resolution of MFS, where the fields forecasted by SANIFS reproduced the observations well (temperature RMSE equal to 0.11 • C).Furthermore, SANIFS simulations were compared with hourly time series of temperature, sea level and velocity measured on the coastal-harbour scale, showing a good agreement. Simulations in the Gulf of Taranto described a circulation mainly characterized by an anticyclonic gyre with the presence of cyclonic vortexes in shelf-coastal areas. A surface water inflow from the open sea to Mar Grande characterizes the coastal-harbour scale.

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Section: Initialization Procedures and Spin-up Timementioning

confidence: 99%

Coastal ocean forecasting with an unstructured grid model in the southern Adriatic and northern Ionian seas

Federico

Pinardi

Coppini

et al. 2017

Nat. Hazards Earth Syst. Sci.

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“…MEDSLIK-II is also able to take into account adsorption of oil by the coast should the slick reach it. The full description of the model formulation can be found in De Dominicis et al (2013a).…”

Section: The Oil Spill and Trajectory Model: Medslik-iimentioning

confidence: 99%

“…These models can vary from simple point source particle-tracking models, such as TESEO-PICHI (Castanedo et al 2006;Sotillo et al 2008), to complex models that attempt to comprehensively simulate the three-dimensional advectiondiffusion-transformations processes that oil undergoes (Wang et al 2008;Wang and Shen 2010). Some of the most sophisticated Lagrangian operational models are COZOIL (Reed et al 1989), SINTEF OSCAR 2000 (Reed et al 1995), OILMAP (Spaulding et al 1994;ASA 1997), GULFSPILL (Al-Rabeh et al 2000), ADIOS (Lehr et al 2002), MOTHY (Daniel et al 2003), MOHID (Carracedo et al 2006), the POSEIDON OSM (Pollani et al 2001Nittis et al 2006, OD3D (Hackett et al 2006), the Seatrack Web SMHI model (Ambjørn 2007), MEDSLIK (Lardner et al 1998, GNOME (Zelenke et al 2012), OILTRANS (Berry et al 2012), and MEDSLIK-II (De Dominicis et al 2013a). Which type of model to use depends on the model availability in the area of interest and final objectives: from short-term forecasting to longterm impact assessment.…”

Section: Introductionmentioning

confidence: 99%

“…Which type of model to use depends on the model availability in the area of interest and final objectives: from short-term forecasting to longterm impact assessment. The oil spill model used in this work is MEDSLIK-II (De Dominicis et al 2013a) that is able to simulate the transport of surface drifters or the transport, diffusion, and transformations of a surface oil slick. It has been used extensively in the past to simulate oil spill accidents (Coppini et al 2011) and/or drifter trajectories (De Dominicis et al 2013b), and it proved to be reliable in short-term forecasting.…”

Section: Introductionmentioning

confidence: 99%

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A relocatable ocean model in support of environmental emergencies

et al. 2014

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During the Costa Concordia emergency case, regional, subregional, and relocatable ocean models have been used together with the oil spill model, MEDSLIK-II, to provide ocean currents forecasts, possible oil spill scenarios, and drifters trajectories simulations. The models results together with the evaluation of their performances are presented in this paper. In particular, we focused this work on the implementation of the Interactive RElo- Concordia emergency and on its validation using drifters released in the area of the accident. It is shown that thanks to the capability of improving easily and quickly its configuration, the IRENOM results are of greater accuracy than the results achieved using regional or subregional model products. The model topography, the initialization procedures, and the horizontal resolution are the key model settings to be configured. Furthermore, the IRENOM currents and the MEDSLIK-II simulated trajectories showed to be sensitive to the spatial resolution of the meteorological fields used, providing higher prediction skills with higher resolution wind forcing.

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“…wind speed and integrated wave parameters, as presented by Ardhuin et al (2009). In some oil drift forecast models, such as SeaTrackWeb (STW; Liungman and Mattson 2011) and MEDSLIK (De Dominicis et al 2013), the wave information estimate is based only on the fetch and the wind speed-an approach that is generally limited in accuracy. It has been shown, e.g.…”

Section: Introductionmentioning

confidence: 99%

Surface Stokes drift in the Baltic Sea based on modelled wave spectra

et al. 2017

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The Stokes drift is an important component in the surface drift. We used the wave model WAM to evaluate the mean values and exceedance probabilities of the surface Stokes drift in the Baltic Sea. As there is no direct way to verify the accuracy of the modelled Stokes drift, we compared the bulk parameters calculated by the wave model against buoy measurements to ensure the quality of the wave hindcast. ) and underestimate the larger values of the Stokes drift compared to the values calculated by the wave model. The modelled surface Stokes drift direction mostly followed the forcing wind direction. This was the case even in the Gulf of Finland, where the direction of the wind and the waves can differ considerably.

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MEDSLIK-II, a Lagrangian marine surface oil spill model for short-term forecasting – Part 1: Theory

Cited by 166 publications

References 50 publications

Coastal ocean forecasting with an unstructured grid model in the southern Adriatic and northern Ionian seas

Coastal ocean forecasting with an unstructured grid model in the southern Adriatic and northern Ionian seas

A relocatable ocean model in support of environmental emergencies

Surface Stokes drift in the Baltic Sea based on modelled wave spectra

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