Articles | Volume 6, issue 6
https://doi.org/10.5194/gmd-6-1871-2013
© 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-6-1871-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model evaluation paper
| 
01 Nov 2013
Model evaluation paper |
| 01 Nov 2013
MEDSLIK-II, a Lagrangian marine surface oil spill model for short-term forecasting – Part 2: Numerical simulations and validations
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. Archetti
DICAM, Dipartimento di Ingegneria Civile, Chimica Ambientale e dei Materiali, University of Bologna, Bologna, Italy
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
Abascal, A., Castanedo, S., Mendez, F., Medina, R., and Losada, I.: Calibration of a Lagrangian transport model using drifting buoys deployed during the Prestige oil spill, J. Coast. Res., 25, https://doi.org/10.2112/07-0849.1, 80–90, 2009.
Al-Rabeh, A.: Estimating surface oil spill transport due to wind in the Arabian Gulf, Ocean Eng., 21, 461–465, 1994.
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. Model. Softw., 15, 425–442, 2000.
Archetti, R.: Design of surface drifter for the oil spill monitoring, in: Revue Paralia, Conférence Méditerranéenne Côtière et Maritime (Coastal and Maritime Mediterranean Conference), Hammamet, Tunisi, 1, 231–234, 2009.
ASCE: State-of-the-Art Review of Modeling Transport and Fate of Oil Spills, J. Hydraulic Eng., 122, 594–609, 1996.
Barron, C. N., Smedstad, L. F., Dastugue, J. M., and Smedstad, O. M.: Evaluation of ocean models using observed and simulated drifter trajectories: Impact of sea surface height on synthetic profiles for data assimilation, J. Geophys. Res., 112, C07019, https://doi.org/10.1029/2006JC003982, 2007.
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, https://doi.org/10.1016/j.marpolbul.2012.07.036, 2012.
Brekke, C. and Solberg, A.: Oil spill detection by satellite remote sensing, Remote Sens. Environ., 95, 1–13, 2005.
Brostrom, G., Carrasco, A., Daniel, P., Hackett, B., Lardner, R., Panayidou, X., Paradis, D., and Zodiatis, G.: Comparison of different oil drift models and different ocean forcing with observed drifter trajectory in the Mediterranean, in: Coastal to Global Operational Oceanography: Achievements and challenges, 5th EuroGoos Conference proceedings, Sandy Park, Exeter, UK, 20–22 May 2008.
Caballero, A., Espino, M., Sagarminaga, Y., Ferrer, L., Uriarte, A., and González, M.: Simulating the migration of drifters deployed in the Bay of Biscay, during the Prestige crisis, Mar. Pollut. Bullet., 56, 475–482, 2008.
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. Bullet., 53, 350–360, 2006.
CEDRE: Aerial observation of oil pollution at sea, Operational guides, ISBN 978-2-87893-083-5, 2004.
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.
Cucco, A., Sinerchia, M., Ribotti, A., Olita, A., Fazioli, L., Perilli, A., Sorgente, B., Borghini, M., Schroeder, K., and Sorgente, R.: A high-resolution real-time forecasting system for predicting the fate of oil spills in the Strait of Bonifacio (western Mediterranean Sea), Mar. Pollut. Bullet., 64, 1186–1200, https://doi.org/10.1016/j.marpolbul.2012.03.019, 2012.
Davis, R. E.: Drifter observations of coastal surface currents during CODE: The method and descriptive view, J. Geophys. Res., 90, 4741–4755, 1985.
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 Lardner, R.: MEDSLIK-II, a Lagrangian marine surface oil spill model for short-term forecasting – Part 1: Theory, Geosci. Model Dev., 6, 1851–1869, https://doi.org/10.5194/gmd-6-1851-2013, 2013.
Dobricic, S. and Pinardi, N.: An oceanographic three-dimensional variational data assimilation scheme, Ocean Model., 22, 3, 89–105, 2008.
Fabbroni, N.: Numerical simulations of passive tracers dispersion in the sea, Ph.D. thesis, University of Bologna, Italy, 2009.
Fiscella, B., Giancaspro, A., Nirchio, F., Pavese, P., and Trivero, P.: Oil spill detection using marine SAR images, Int. J. Remote Sens., 21, 3561–3566, 2000.
Guarnieri, A., Pinardi, N., Oddo, P., Bortoluzzi, G., and Ravaioli, M.: Modelling baroclinic circulation with tidal components in the Adriatic Sea, J. Geophys. Res. – Oceans, 118, 166–183, https://doi.org/10.1029/2012JC007921, 2013.
Haidvogel, D. B. and Beckmann, A.: Numerical ocean circulation modeling, Imperial College Pr, 318 pp., ISBN 9781860941146, 1999.
Hoult, D.: Oil spreading on the sea, Ann. Rev. Fluid Mech., 4, 341–368, 1972.
Hu, C., Muller-Karger, F., Taylor, C., Myhre, D., Murch, B., Odriozola, A., and Godoy, G.: MODIS detects oil spills in Lake Maracaibo, Venezuela, EOS T. Am. Geophys. Un., 84, 313–319, 2003.
Hu, C., Li, X., Pichel, W., and Muller-Karger, F.: Detection of natural oil slicks in the NW Gulf of Mexico using MODIS imagery, Geophys. Res. Lett, 36, L01604, https://doi.org/10.1029/2008GL036119, 2009.
Huntley, H. S., Lipphardt Jr., B. L., and Kirwan Jr., A. D.: Lagrangian predictability assessed in the East China Sea, Ocean Model., 36, 163–178, 2011.
Ivichev, I., Hole, L. R., Karlin, L., Wettre, C., and Röhrs, J.: Comparison of Operational Oil Spill Trajectory Forecasts with Surface Drifter Trajectories in the Barents Sea, J. Geol. Geosci., 1, 105, https://doi.org/10.4172/jgg.1000105, 2012.
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. and Weisberg, R. H.: Evaluation of trajectory modeling in different dynamic regions using normalized cumulative Lagrangian separation, J. Geophys. Res., 116, C09013, https://doi.org/10.1029/2010JC006837, 2011b.
Liu, Y., Weisberg, R. H., Hu, C., and Zheng, L.: Tracking the Deepwater Horizon oil spill: A modeling perspective, EOS T. Am. Geoophys. Un., 92, 45–46, 2011c.
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, 2011d.
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, K.: 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.
Mariano, A., Kourafalou, V., Srinivasan, A., Kang, H., Halliwell, G., Ryan, E., and Roffer, M.: On the modeling of the 2010 Gulf of Mexico Oil Spil, Dynam. Atmos. Oceans, 52, 322–340, https://doi.org/10.1016/j.dynatmoce.2011.06.001, 2011.
Nirchio, F., Sorgente, M., Giancaspro, A., Biamino, W., Parisato, E., Ravera, R., and Trivero, P.: Automatic detection of oil spills from SAR images, Int. J. Remote Sens., 26, 1157–1174, 2005.
Nirchio, F., Marzo, C., Trivero, P., Biamino, W., Di Tomaso, S., and Escalada, A.: A generalised algorithm for oil spill detection on ERS and ENVISAT SAR images, in: Proceedings of Envisat Symposium 2007, 11, 12–40, 2007.
Nirchio, F., Pandiscia, G., Ruggieri, G., Santoleri, R., Pinardi, N., Trivero, P., Castellani, C., Tataranni, F., Masini, A., Adamo, M., Archetti, R., Biamino, W., Bignami, F., Bohm, E., Borasi, M., Nardelli, B.B., Cavagnero, M., Colao, F., Colella, S., Coppini, G., Debettio, V., De Carolis, G., De Dominicis, M., Forneris, V., Fontebasso, F., Griffa, A., Iacono, R., Lombardi, E., Marullo, S., Manzella, G., Mercatini, A., Napolitano, E., Pisano, A., Reseghetti, F., Sorgente, R., Sprovieri, M., Terranova, G., Volpe, G., and Zambianchi, E.: Contribution of Cosmo/SkyMed data into PRIMI: A pilot project on marine oil pollution, results after one year of operations, in: Geosci. Remote Sens. Symposium (IGARSS), 2010 IEEE International, 4799–4802, 2010.
Oddo, P., Adani, M., Pinardi, N., Fratianni, C., Tonani, M., and Pettenuzzo, D.: A nested Atlantic-Mediterranean Sea general circulation model for operational forecasting, Ocean Sci., 5, 461–473, https://doi.org/10.5194/os-5-461-2009, 2009.
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.
Poulain, P. M., Gerin, R., Rixen, M., Zanasca, P., Teixeira, J., Griffa, A., Molcard, A., Marte, M. D., and Pinardi, N.: Aspects of the surface circulation in the Liguro-Provençal basin and Gulf of Lion as observed by satellite-tracked drfiters (2007–2009), Bollettino di Geofisica Teorica e Applicata, 53, 261–279, https://doi.org/10.4430/bgta0052, 2011.
Price, J. M., Reed, M., Howard, M. K., Johnson, W. R., Ji, Z. G., Marshall, C. F., Guinasso, N. L., and Rainey, G. B.: Preliminary assessment of an oil-spill trajectory model using satellite-tracked, oil-spill-simulating drifters, Environ. Model. Softw., 21, 258–270, 2006.
Reed, M., Turner, C., and Odulo, A.: The role of wind and emulsification in modelling oil spill and surface drifter trajectories, Spill. Sci. Technol. B., 1, 143–157, 1994.
Robinson, A.: Forecasting and simulating coastal ocean processes and variabilities with the Harvard Ocean Prediction System, Coastal Ocean Prediction, AGU Coastal and Estuarine Studies Series, Am. Geophys. Union, 77–100, 1999.
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 Dynam., 62, 1519–1533, 2012.
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.
Tonani, M., Pinardi, N., Dobricic, S., Pujol, I., and Fratianni, C.: A high-resolution free-surface model of the Mediterranean Sea, Ocean Sci., 4, 1–14, https://doi.org/10.5194/os-4-1-2008, 2008.
Trivero, P., Fiscella, B., Gomez, F., and Pavese, P.: SAR detection and characterization of sea surface slicks, Int. J. Remote Sens., 19, 543–548, 1998.
Trivero, P., Fiscella, B., and Pavese, P.: Sea surface slicks measured by SAR, Il Nuovo Cimento della Società italiana di fisica, 24, 99–111, 2001.
Zodiatis, G., Hayes, D., Lardner, R., Georgiou, G., Kallos, G., Sofianos, S., Pinardi, N., and Panayidou, X.: Marine core and downstream oceanographic services in the Eastern Mediterranean Levantine Basin and their success in assisting the EU response agencies, in: Coastal to Global Operational Oceanography: Achievements and challenges, EuroGoos Conference proceedings, 465–472, 2010.
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.
