Articles | Volume 6, issue 6
https://doi.org/10.5194/gmd-6-1851-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-6-1851-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
MEDSLIK-II, a Lagrangian marine surface oil spill model for short-term forecasting – Part 1: Theory
M. De Dominicis
Istituto Nazionale di Geofisica e Vulcanologia, Bologna, Italy
N. Pinardi
Corso di Scienze Ambientali, University of Bologna, Ravenna, Italy
G. Zodiatis
Oceanography Centre, University of Cyprus, Nicosia, Cyprus
R. Lardner
Oceanography Centre, University of Cyprus, Nicosia, Cyprus
Related authors
No articles found.
Seimur Shirinov, Ivan Federico, Simone Bonamano, Salvatore Causio, Nicolás Biocca, Viviana Piermattei, Daniele Piazzolla, Jacopo Alessandri, Lorenzo Mentaschi, Giovanni Coppini, Marco Marcelli, and Nadia Pinardi
Nat. Hazards Earth Syst. Sci., 25, 3737–3758, https://doi.org/10.5194/nhess-25-3737-2025, https://doi.org/10.5194/nhess-25-3737-2025, 2025
Short summary
Short summary
This research investigates how seagrass meadows attenuate coastal waves. Our methodology integrates site measurements with numerical simulations, revealing that plant flexibility and seasonal growth cycles are crucial factors that enhance model fidelity for predicting wave damping. These insights aid ecosystem-based coastal protection and conservation of these vital habitats. Future work should address current–sediment–vegetation interactions for a more complete hydrodynamic understanding.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
EGUsphere, https://doi.org/10.5194/egusphere-2025-3795, https://doi.org/10.5194/egusphere-2025-3795, 2025
Short summary
Short summary
The parameters that control a model's behavior determine its ability to represent a system. In this work, multiple cases test how to estimate the parameters of a model with components corresponding to both the physics and the chemical and biological processes (i.e. the biogeochemistry) of the ocean. While demonstrating how to approach this problem type, the results show estimating both sets of parameters simultaneously is better than estimating the physics then the biogeochemistry separately.
Mahmud Hasan Ghani, Nadia Pinardi, Antonio Navarra, Lorenzo Mentaschi, Silvia Bianconcini, Francesco Maicu, and Francesco Trotta
EGUsphere, https://doi.org/10.5194/egusphere-2025-2867, https://doi.org/10.5194/egusphere-2025-2867, 2025
Short summary
Short summary
Using the same SST and the same bulk formula, but different atmospheric reanalysis and analysis surface variable datasets, we show that higher resolution (ECMWF) dataset is crucial for evaluating the heat budget closure hypothesis in the Mediterranean Sea. For the first time, we investigate the impact of extreme heat loss events in the Mediterranean Sea in the long-term mean basin-averaged heat budget.
Paolo Oddo, Mario Adani, Francesco Carere, Andrea Cipollone, Anna Chiara Goglio, Eric Jansen, Ali Aydogdu, Francesca Mele, Italo Epicoco, Jenny Pistoia, Emanuela Clementi, Nadia Pinardi, and Simona Masina
EGUsphere, https://doi.org/10.5194/egusphere-2025-1553, https://doi.org/10.5194/egusphere-2025-1553, 2025
Short summary
Short summary
This study present a data assimilation scheme that combines ocean observational data with ocean model results to better understand the ocean and predict its future state. The method uses a variational approach focusing on the physical relationships between all the state vector variables errors. Testing in the Mediterranean Sea showed that a complex sea level operator based on a barotropic model works best.
Rita Lecci, Robyn Gwee, Kun Yan, Sanne Muis, Nadia Pinardi, Jun She, Martin Verlaan, Simona Masina, Wenshan Li, Hui Wang, Salvatore Causio, Antonio Novellino, Marco Alba, Etiënne Kras, Sandra Gaytan Aguilar, and Jan-Bart Calewaert
EGUsphere, https://doi.org/10.5194/egusphere-2025-1763, https://doi.org/10.5194/egusphere-2025-1763, 2025
Short summary
Short summary
This study explored how sea level is changing along the China-Europe Sea Route. By combining satellite and in-situ observations with advanced modeling, the research identified ongoing sea level rise and an increasing frequency of extreme water level events in some regions. These findings underscore the importance of continued monitoring and provide useful knowledge to support long-term planning, coastal resilience, and informed decision-making.
Italo R. Lopes, Ivan Federico, Michalis Vousdoukas, Luisa Perini, Salvatore Causio, Giovanni Coppini, Maurilio Milella, Nadia Pinardi, and Lorenzo Mentaschi
EGUsphere, https://doi.org/10.5194/egusphere-2025-1695, https://doi.org/10.5194/egusphere-2025-1695, 2025
Short summary
Short summary
We improved a computer model to simulate coastal flooding by including temporary barriers like sand dunes. We tested it where sand dunes are built seasonally to protect the shoreline for two real storms: one that broke through the dunes and another where dunes held strong. Our model showed how important it is to design these defenses carefully since even if a small part of a dune fails, a major flooding can happen. Overall, our work helps create better tools to manage and protect coastal areas.
José A. Jiménez, Gundula Winter, Antonio Bonaduce, Michael Depuydt, Giulia Galluccio, Bart van den Hurk, H. E. Markus Meier, Nadia Pinardi, Lavinia G. Pomarico, and Natalia Vazquez Riveiros
State Planet, 3-slre1, 3, https://doi.org/10.5194/sp-3-slre1-3-2024, https://doi.org/10.5194/sp-3-slre1-3-2024, 2024
Short summary
Short summary
The Knowledge Hub on Sea Level Rise (SLR) has done a scoping study involving stakeholders from government and academia to identify gaps and needs in SLR information, impacts, and policies across Europe. Gaps in regional SLR projections and uncertainties were found, while concerns were raised about shoreline erosion and emerging problems like saltwater intrusion and ineffective adaptation plans. The need for improved communication to make better decisions on SLR adaptation was highlighted.
Nadia Pinardi, Bart van den Hurk, Michael Depuydt, Thorsten Kiefer, Petra Manderscheid, Lavinia Giulia Pomarico, and Kanika Singh
State Planet, 3-slre1, 2, https://doi.org/10.5194/sp-3-slre1-2-2024, https://doi.org/10.5194/sp-3-slre1-2-2024, 2024
Short summary
Short summary
The Knowledge Hub on Sea Level Rise (KH-SLR), a joint effort between JPI Climate and JPI Oceans, addresses the critical need for science-based information on sea level changes in Europe. The KH-SLR actively involves stakeholders through a co-design process discussing the impacts, adaptation planning, and policy requirements related to SLR in Europe. Its primary output is the KH Assessment Report (KH-AR), which is described in this volume.
Bart van den Hurk, Nadia Pinardi, Alexander Bisaro, Giulia Galluccio, José A. Jiménez, Kate Larkin, Angélique Melet, Lavinia Giulia Pomarico, Kristin Richter, Kanika Singh, Roderik van de Wal, and Gundula Winter
State Planet, 3-slre1, 1, https://doi.org/10.5194/sp-3-slre1-1-2024, https://doi.org/10.5194/sp-3-slre1-1-2024, 2024
Short summary
Short summary
The Summary for Policymakers compiles findings from “Sea Level Rise in Europe: 1st Assessment Report of the Knowledge Hub on Sea Level Rise”. It covers knowledge gaps, observations, projections, impacts, adaptation measures, decision-making principles, and governance challenges. It provides information for each European basin (Mediterranean, Black Sea, North Sea, Baltic Sea, Atlantic, and Arctic) and aims to assist policymakers in enhancing the preparedness of European coasts for sea level rise.
Bethany McDonagh, Emanuela Clementi, Anna Chiara Goglio, and Nadia Pinardi
Ocean Sci., 20, 1051–1066, https://doi.org/10.5194/os-20-1051-2024, https://doi.org/10.5194/os-20-1051-2024, 2024
Short summary
Short summary
Tides in the Mediterranean Sea are typically of low amplitude, but twin experiments with and without tides demonstrate that tides affect the circulation directly at scales away from those of the tides. Analysis of the energy changes due to tides shows that they enhance existing oscillations, and internal tides interact with other internal waves. Tides also increase the mixed layer depth and enhance deep water formation in key regions. Internal tides are widespread in the Mediterranean Sea.
Roberta Benincasa, Giovanni Liguori, Nadia Pinardi, and Hans von Storch
Ocean Sci., 20, 1003–1012, https://doi.org/10.5194/os-20-1003-2024, https://doi.org/10.5194/os-20-1003-2024, 2024
Short summary
Short summary
Ocean dynamics result from the interplay of internal processes and external inputs, primarily from the atmosphere. It is crucial to discern between these factors to gauge the ocean's intrinsic predictability and to be able to attribute a signal under study to either external factors or internal variability. Employing a simple analysis, we successfully characterized this variability in the Mediterranean Sea and compared it with the oceanic response induced by atmospheric conditions.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev., 17, 621–649, https://doi.org/10.5194/gmd-17-621-2024, https://doi.org/10.5194/gmd-17-621-2024, 2024
Short summary
Short summary
Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Giovanni Coppini, Emanuela Clementi, Gianpiero Cossarini, Stefano Salon, Gerasimos Korres, Michalis Ravdas, Rita Lecci, Jenny Pistoia, Anna Chiara Goglio, Massimiliano Drudi, Alessandro Grandi, Ali Aydogdu, Romain Escudier, Andrea Cipollone, Vladyslav Lyubartsev, Antonio Mariani, Sergio Cretì, Francesco Palermo, Matteo Scuro, Simona Masina, Nadia Pinardi, Antonio Navarra, Damiano Delrosso, Anna Teruzzi, Valeria Di Biagio, Giorgio Bolzon, Laura Feudale, Gianluca Coidessa, Carolina Amadio, Alberto Brosich, Arnau Miró, Eva Alvarez, Paolo Lazzari, Cosimo Solidoro, Charikleia Oikonomou, and Anna Zacharioudaki
Ocean Sci., 19, 1483–1516, https://doi.org/10.5194/os-19-1483-2023, https://doi.org/10.5194/os-19-1483-2023, 2023
Short summary
Short summary
The paper presents the Mediterranean Forecasting System evolution and performance developed in the framework of the Copernicus Marine Service.
Umesh Pranavam Ayyappan Pillai, Nadia Pinardi, Ivan Federico, Salvatore Causio, Francesco Trotta, Silvia Unguendoli, and Andrea Valentini
Nat. Hazards Earth Syst. Sci., 22, 3413–3433, https://doi.org/10.5194/nhess-22-3413-2022, https://doi.org/10.5194/nhess-22-3413-2022, 2022
Short summary
Short summary
The study presents the application of high-resolution coastal modelling for wave hindcasting on the Emilia-Romagna coastal belt. The generated coastal databases which provide an understanding of the prevailing wind-wave characteristics can aid in predicting coastal impacts.
Giorgio Micaletto, Ivano Barletta, Silvia Mocavero, Ivan Federico, Italo Epicoco, Giorgia Verri, Giovanni Coppini, Pasquale Schiano, Giovanni Aloisio, and Nadia Pinardi
Geosci. Model Dev., 15, 6025–6046, https://doi.org/10.5194/gmd-15-6025-2022, https://doi.org/10.5194/gmd-15-6025-2022, 2022
Short summary
Short summary
The full exploitation of supercomputing architectures requires a deep revision of the current climate models. This paper presents the parallelization of the three-dimensional hydrodynamic model SHYFEM (System of HydrodYnamic Finite Element Modules). Optimized numerical libraries were used to partition the model domain and solve the sparse linear system of equations in parallel. The performance assessment demonstrates a good level of scalability with a realistic configuration used as a benchmark.
Begoña Pérez Gómez, Ivica Vilibić, Jadranka Šepić, Iva Međugorac, Matjaž Ličer, Laurent Testut, Claire Fraboul, Marta Marcos, Hassen Abdellaoui, Enrique Álvarez Fanjul, Darko Barbalić, Benjamín Casas, Antonio Castaño-Tierno, Srđan Čupić, Aldo Drago, María Angeles Fraile, Daniele A. Galliano, Adam Gauci, Branislav Gloginja, Víctor Martín Guijarro, Maja Jeromel, Marcos Larrad Revuelto, Ayah Lazar, Ibrahim Haktan Keskin, Igor Medvedev, Abdelkader Menassri, Mohamed Aïssa Meslem, Hrvoje Mihanović, Sara Morucci, Dragos Niculescu, José Manuel Quijano de Benito, Josep Pascual, Atanas Palazov, Marco Picone, Fabio Raicich, Mohamed Said, Jordi Salat, Erdinc Sezen, Mehmet Simav, Georgios Sylaios, Elena Tel, Joaquín Tintoré, Klodian Zaimi, and George Zodiatis
Ocean Sci., 18, 997–1053, https://doi.org/10.5194/os-18-997-2022, https://doi.org/10.5194/os-18-997-2022, 2022
Short summary
Short summary
This description and mapping of coastal sea level monitoring networks in the Mediterranean and Black seas reveals the existence of 240 presently operational tide gauges. Information is provided about the type of sensor, time sampling, data availability, and ancillary measurements. An assessment of the fit-for-purpose status of the network is also included, along with recommendations to mitigate existing bottlenecks and improve the network, in a context of sea level rise and increasing extremes.
Katherine M. Smith, Skyler Kern, Peter E. Hamlington, Marco Zavatarelli, Nadia Pinardi, Emily F. Klee, and Kyle E. Niemeyer
Geosci. Model Dev., 14, 2419–2442, https://doi.org/10.5194/gmd-14-2419-2021, https://doi.org/10.5194/gmd-14-2419-2021, 2021
Short summary
Short summary
We present a newly developed reduced-order biogeochemical flux model that is complex and flexible enough to capture open-ocean ecosystem dynamics but reduced enough to incorporate into highly resolved numerical simulations with limited additional computational cost. The model provides improved correlations between model output and field data, indicating that significant improvements in the reproduction of real-world data can be achieved with a small number of variables.
Cited articles
Al-Rabeh, A. H., Lardner, R. W., and Gunay, N.: Gulfspill Version 2.0: a software package for oil spills in the Arabian Gulf, Environ. Modell. Softw., 15, 425–442, 2000.
Ambjörn, C.: Seatrack Web, Forecasts of Oil Spills, a New Version, Environ. Res. Eng. Manage., 3, 60–66, 2007.
ASA: OILMAP for Windows (technical manual), Narrangansett, Rhode Island: ASA Inc, 1997.
ASCE: State-of-the-Art Review of Modeling Transport and Fate of Oil Spills, J. Hydraulic Eng., 122, 594–609, 1996.
Berry, A., Dabrowski, T., and Lyons, K.: The oil spill model OILTRANS and its application to the Celtic Sea, Mar. Pollut. Bull., 64, 2489–2501, 2012.
Butenschön, M. and Zavatarelli, M., and Vichi, M.: Sensitivity of a marine coupled physical biogeochemical model to time resolution, integration scheme and time splitting method, Ocean Model., 52, 36–53, 2012.
Carracedo, P., Torres-López, S., Barreiro, M., Montero, P., Balseiro, C., Penabad, E., Leitao, P., and Pérez-Muñuzuri, V.: Improvement of pollutant drift forecast system applied to the Prestige oil spills in Galicia Coast (NW of Spain): Development of an operational system, Mar. Pollut. Bull., 53, 350–360, 2006.
Castanedo, S., Medina, R., Losada, I. J., Vidal, C., Mendez, F. J., Osorio, A., Juanes, J. A., and Puente, A.: The Prestige oil spill in Cantabria Bay of Biscay). Part I: Operational forecasting system for quick response, risk assessment, and protection of natural resources, J. Coast. Res., 22, 1474–1489, 2006.
Coppini, G., De Dominicis, M., Zodiatis, G., Lardner, R., Pinardi, N., Santoleri, R., Colella, S., Bignami, F., Hayes, D. R., Soloviev, D., Georgiou, G., and Kallos, G.: Hindcast of oil-spill pollution during the Lebanon crisis in the Eastern Mediterranean, July–August 2006, Mar. Pollut. Bullet., 62, 140–153, 2011.
Daniel, P., Marty, F., Josse, P., Skandrani, C., and Benshila, R.: Improvement of drift calculation in Mothy operational oil spill prediction system, in: International Oil Spill Conference (Vancouver, Canadian Coast Guard and Environment Canada), vol. 6, 2003.
De Dominicis, M., Leuzzi, G., Monti, P., Pinardi, N., and Poulain, P.: Eddy diffusivity derived from drifter data for dispersion model applications, Ocean Dynam., 62, 1381–1398, https://doi.org/10.1007/s10236-012-0564-2, 2012.
De Dominicis, M., Pinardi, N., Zodiatis, G., and Archetti, R.: MEDSLIK-II, a Lagrangian marine surface oil spill model for short-term forecasting – Part 2: Numerical simulations and validations, Geosci. Model Dev., 6, 1871–1888, https://doi.org/10.5194/gmd-6-1871-2013, 2013.
Griffa, A.: Applications of stochastic particle models to oceanographic problems, in: Stochastic modelling in physical oceanography, Progress in Probability, 39, 113–140, 1996.
Gurney, K., Law, R., Denning, A., Rayner, P., Baker, D., Bousquet, P., Bruhwiler, L., Chen, Y. H., Ciais, P., Fan, S., Fung, I. Y., Gloor, M., Heimann, M., Higuchi, K., John, J., Maki, T., Maksyutov, S., Masarie, K., Peylin, P., Prather, M., Pak, B. C., Randerson, J., Sarmiento, J., Taguchi, S., Takahashi, T., and Yuen, C.-W.: Towards robust regional estimates of CO2 sources and sinks using atmospheric transport models, Nature, 415, 626–630, 2002.
Gurney, K., Law, R., Denning, A., Rayner, P., Pak, B., Baker, D., Bousquet, P., Bruhwiler, L., Chen, Y., Ciais, P., Fung, I. Y., Heimann, M., John, J., Maki, T., Maksyutov, S., Peylin, P., Prather, M., and Taguchi, S.: Transcom 3 inversion intercomparison: Model mean results for the estimation of seasonal carbon sources and sinks, Global Biogeochem. Cy., 18, GB1010, https://doi.org/10.1029/2003GB002111, 2004.
Hackett, B., Breivik, Ø., and Wettre, C.: Forecasting the Drift of Objects and Substances in the Ocean, Ocean Weather Forecasting, Springer, Netherlands, 507–523, 2006.
Haidvogel, D. B. and Beckmann, A.: Numerical ocean circulation modeling, Imperial College Pr, 318 pp., ISBN 9781860941146, 1999.
Hasselmann, K., Barnett, T., Bouws, E., Carlson, H., Cartwright, D., Enke, K., Ewing, J., Gienapp, H., Hasselmann, D., Kruseman, P., Meerburg, A., Mller, P., Olbers, D., Richter, K., Sell, W., and Walden, H.: Measurements of wind-wave growth and swell decay during the Joint North Sea Wave Project (JONSWAP), Ergänzungsheft zur Deutschen Hydrographischen Zeitschrift Reihe, A8–12, 1973.
Huntley, H. S., Lipphardt, B. L., and Kirwan, A. D.: Surface drift predictions of the Deepwater Horizon spill: The Lagrangian perspective, in: Monitoring and Modeling the Deepwater Horizon Oil Spill: A Record-Breaking Enterprise, Geophys. Monogr. Ser., 195, 179–195, 2011
Lardner, R., Zodiatis, G., Loizides, L., and Demetropoulos, A.: An operational oil spill model for the Levantine Basin (Eastern Mediterranean Sea), in: International Symposium on Marine Pollution, 1998.
Lardner, R., Zodiatis, G., Hayes, D., and Pinardi, N.: Application of the MEDSLIK Oil Spill Model to the Lebanese Spill of July 2006, European Group of Experts on Satellite Monitoring of Sea Based Oil Pollution, European Communities, 2006.
Lehr, W., Jones, R., Evans, M., Simecek-Beatty, D., and Overstreet, R.: Revisions of the ADIOS oil spill model, Environ. Modell. Softw., 17, 189–197, 2002.
Lenn, Y. D. and Chereskin, T. K.: Observations of Ekman currents in the Southern Ocean, J. Phys. Oceanogr., 39, 768–779, 2009.
Liu, Y., MacFadyen, A., Ji, Z.-G., and Weisberg, R. H.: Introduction to Monitoring and Modeling the Deepwater Horizon Oil Spill, in: Monitoring and Modeling the Deepwater Horizon Oil Spill: A Record-Breaking Enterprise, Geophys. Monogr. Ser., 195, 1–7, 2011a.
Liu, Y., Weisberg, R. H., Hu, C., and Zheng, L.: Trajectory forecast as a rapid response to the Deepwater Horizon oil spill, in: Monitoring and Modeling the Deepwater Horizon Oil Spill: A Record-Breaking Enterprise, Geophys. Monogr. Ser., 195, 153–165, 2011b.
Lorimer, G.: The kernel method for air quality modelling– I, Mathematical foundation, Atmos. Environ. (1967), 20, 1447–1452, 1986.
Mackay, D., Buist, I., Mascarenhas, R., and Paterson, S.: Oil spill processes and models. Report to Research and Development Division, Environment Emergency Branch, Environmental Impact Control Directorate, Environmental Protection Service, Environment Canada, Ottawa, 1979.
Mackay, D., Paterson, S., and Trudel, B.: A mathematical model of oil spill behaviour, Report to Research and Development Division, Environment Emergency Branch, Environmental Impact Control Directorate, Environmental Protection Service, Environment Canada, Ottawa, 1980.
Nittis, K., Perivoliotis, L., Korres, G., Tziavos, C., and Thanos, I.: Operational monitoring and forecasting for marine environmental applications in the Aegean Sea, Environ. Modell. Softw., 21, 243–257, 2006.
Noye, J.: Numerical methods for solving the transport equation, Num. Model. Application Mar. Syst., 145, 195–229, 1987.
Pedlosky, J.: The buoyancy and wind-driven ventilated thermocline, J. Phys. Oceanogr., 16, 1077–1087, 1986.
Pinardi, N. and Coppini, G.: Preface "Operational oceanography in the Mediterranean Sea: the second stage of development", Ocean Sci., 6, 263–267, https://doi.org/10.5194/os-6-263-2010, 2010.
Pinardi, N., Allen, I., Demirov, E., De Mey, P., Korres, G., Lascaratos, A., Le Traon, P.-Y., Maillard, C., Manzella, G., and Tziavos, C.: The Mediterranean ocean forecasting system: first phase of implementation (1998–2001), Ann. Geophys., 21, 3–20, https://doi.org/10.5194/angeo-21-3-2003, 2003.
Pollani, A., Triantafyllou, G., Petihakis, G., Nittis, K., Dounas, C., and Christoforos, K.: The Poseidon operational tool for the prediction of floating pollutant transport, Mar. Pollut. Bull., 43, 270–278, 2001.
Price, J. F., Weller, R. A., and Schudlich, R. R.: Wind-driven ocean currents and Ekman transport, Science, 238, 1534–1538, 1987.
Pugliese Carratelli, E., Dentale F., and Reale F.: On the effects of wave-induced drift and dispersion in the Deepwater Horizon oil spill, in: Monitoring and Modeling the Deepwater Horizon Oil Spill: A Record-Breaking Enterprise, Geophys. Monogr. Ser., 195, 197–204, 2011.
Reed, M., Gundlach, E., and Kana, T.: A coastal zone oil spill model: development and sensitivity studies, Oil Chem. Pollut., 5, 411–449, 1989.
Reed, M., Aamo, O. M., and Daling, P. S.: Quantitative analysis of alternate oil spill response strategies using OSCAR, Spill Sci. Technol. Bull., 2, 67–74, 1995.
Reed, M., Johansen, Ø., Brandvik, P. J., Daling, P., Lewis, A., Fiocco, R., Mackay, D., and Prentki, R.: Oil Spill Modeling towards the Close of the 20th Century: Overview of the State of the Art, Spill Sci. Technol. Bull., 5, 3–16, 1999.
Risken, H.: The Fokker-Planck equation, Springer, 475 pp., ISBN 354061530X, 9783540615309, 1989.
Röhrs, J., Christensen, K. H., Hole, L. R., Broström, G., Drivdal, M., and Sundby, S.: Observation-based evaluation of surface wave effects on currents and trajectory forecasts, Ocean Dynamics, 62, 10-12, 1519–1533, 2012.
Schreurs, P., Mewis, J., and Havens, J.: Numerical aspects of a Lagrangian particle model for atmospheric dispersion of heavy gases, J. Hazardous Materials, 17, 61–80, https://doi.org/10.1016/0304-3894(87)85042-2, 1987.
Shen, H. T., Yapa, P. D., and Petroski, M. E.: A Simulation Model for Oil Slick Transport in Lakes, Water Resour. Res., 23, 1949–1957, 1987.
Sibert, J. R., Hampton, J., Fournier, D. A., and Bills, P. J.: An advection-diffusion-reaction model for the estimation of fish movement parameters from tagging data, with application to skipjack tuna (Katsuwonus pelamis), Canadian J. Fish. Aquatic Sci., 56, 925–938, 1999.
Sobey, R. J. and Barker, C. H.: Wave-driven transport of surface oil, J. Coastal Res., 13, 490–496, 1997.
Sotillo, M., Alvarez Fanjul, E., Castanedo, S., Abascal, A., Menendez, J., Emelianov, M., Olivella, R., García-Ladona, E., Ruiz-Villarreal, M., Conde, J., G\'\oomez, M., Conde, P., Gutierrez, A., and Medina, R.: Towards an operational system for oil-spill forecast over Spanish waters: Initial developments and implementation test, Mar. Pollut. Bull., 56, 686–703, 2008.
Spaulding, M., Kolluru, V., Anderson, E., and Howlett, E.: Application of three-dimensional oil spill model (WOSM/OILMAP) to hindcast the Braer spill, Spill Sci. Technol. Bull., 1, 23–35, 1994.
Stohl, A.: Computation, accuracy and applications of trajectories – A review and bibliography, Atmos. Environ., 32, 947–966, https://doi.org/10.1016/S1352-2310(97)00457-3, 1998.
Stokes, G.: On the theory of oscillatory waves, Transactions of the Cambridge Philosophical Society, 8, 441–473, 1847.
Tompson, A. and Gelhar, L.: Numerical Simulation of Solute Transport in Three-Dimensional, Randomly Heterogeneous Porous Media, Water Resour. Res., 26, 2541–2562, 1990.
Wang, J. and Shen, Y.: Development of an integrated model system to simulate transport and fate of oil spills in seas, Sci. China Technol. Sci., 53, 2423–2434, 2010.
Wang, S., Shen, Y., Guo, Y., and Tang, J.: Three-dimensional numerical simulation for transport of oil spills in seas, Ocean Eng., 35, 503–510, 2008.
Woods, J.: Primitive equation modelling of plankton ecosystems, Ocean F}orecasting, Conceptual Basis and Applications, edited by: Pinardi, N. and Woods, J., Springer-Verlag {Berlin Heidelberg, 2002.
Wunsch, C.: The work done by the wind on the oceanic general circulation, J. Phys. Oceanogr., 28, 2332–2340, 1998.
Zelenke, B., O'Connor, C., Barker, C., Beegle-Krause, C. J., and Eclipse, L. (Eds.): General NOAA Operational Modeling Environment (GNOME) Technical Documentation, US Dept. of Commerce, NOAA Technical Memorandum NOS OR&R 40. Seattle, WA: Emergency Response Division, NOAA, 105 pp., available at: http://response.restoration.noaa.gov/gnome_manual, 2012.
Zodiatis, G., Lardner, R., Hayes, D., Georgiou, G., Pinardi, N., De Dominicis, M., and Panayidou, X.: The Mediterranean oil spill and trajectory prediction model in assisting the EU response agencie, in: Congreso Nacional de Salvamento en la Mar, Cadiz, 2–4 October, libro de actas, 535–547, 2008a.
Zodiatis, G., Lardner, R., Hayes, D. R., Georgiou, G., Sofianos, S., Skliris, N., and Lascaratos, A.: Operational ocean forecasting in the Eastern Mediterranean: implementation and evaluation, Ocean Sci., 4, 31–47, https://doi.org/10.5194/os-4-31-2008, 2008b.
Zodiatis, G., Lardner, R., Solovyov, D., Panayidou, X., and De Dominicis, M.: Predictions for oil slicks detected from satellite images using MyOcean forecasting data, Ocean Sci., 8, 1105–1115, https://doi.org/10.5194/os-8-1105-2012, 2012.