Articles | Volume 8, issue 10
https://doi.org/10.5194/gmd-8-3365-2015
https://doi.org/10.5194/gmd-8-3365-2015
Model description paper
 | 
26 Oct 2015
Model description paper |  | 26 Oct 2015

CranSLIK v2.0: improving the stochastic prediction of oil spill transport and fate using approximation methods

R. Rutherford, I. Moulitsas, B. J. Snow, A. J. Kolios, and M. De Dominicis

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Cited articles

Choi, S.-K., Grandhi, R. V., and Canfield, R. A.: Reliability-based Structural Design, Springer, London, 3rd edn., 2007.
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, Marine Pollut. B., 62, 140–153, 2011.
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, 2013a.
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, 2013b.
Dobricic, S. and Pinardi, N.: An oceanographic three-dimensional variational data assimilation scheme, Ocean Model., 22, 89–105, 2008.
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Short summary
CranSLIK is a model that predicts the movement and spread of a surface oil spill at sea via a statistical approach that takes into account the random, and hence unpredictable, nature, of the affecting parameters. CranSLIK v2.0 demonstrated significant forecasting improvements by capturing the oil spill accurately in real oil spill validation cases and also proved capable of simulating a broader range of oil spill scenarios, while maintaining the run-time efficiency of the method.