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

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dc.contributor.authorRutherford, R.
dc.contributor.authorMoulitsas, Irene
dc.contributor.authorSnow, Ben J.
dc.contributor.authorKolios, Athanasios J.
dc.contributor.authorDe Dominicis, Michela
dc.date.accessioned2019-11-01T11:50:38Z
dc.date.available2019-11-01T11:50:38Z
dc.date.issued2015-10-26
dc.description.abstractOil spill models are used to forecast the transport and fate of oil after it has been released. CranSLIK is a model that predicts the movement and spread of a surface oil spill at sea via a stochastic approach. The aim of this work is to identify parameters that can further improve the forecasting algorithms and expand the functionality of CranSLIK, while maintaining the run-time efficiency of the method. The results from multiple simulations performed using the operational, validated oil spill model, MEDSLIK-II, were analysed using multiple regression in order to identify improvements which could be incorporated into CranSLIK. This has led to a revised model, namely CranSLIK v2.0, which was validated against MEDSLIK-II forecasts for real oil spill cases. The new version of CranSLIK demonstrated significant forecasting improvements by capturing the oil spill accurately in real validation cases and also proved capable of simulating a broader range of oil spill scenarios.en_UK
dc.identifier.citationRutherford R, Moulitsas I, Snow BJ, et al., (2015) CranSLIK v2.0: improving the stochastic prediction of oil spill transport and fate using approximation methods. Geoscientific Model Development, Volume 8, Issue 10, 2015, pp. 3365-3377en_UK
dc.identifier.cris3314011
dc.identifier.issn1991-959X
dc.identifier.urihttps://doi.org/10.5194/gmd-8-3365-2015
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/14668
dc.language.isoenen_UK
dc.publisherEuropean Geosciences Unionen_UK
dc.rightsAttribution 3.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/*
dc.titleCranSLIK v2.0: improving the stochastic prediction of oil spill transport and fate using approximation methodsen_UK
dc.typeArticleen_UK

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