The ability to monitor and predict marine oil spills depends on access to high-quality information on ocean circulation. Global Ocean Data Assimilation Experiment (GODAE) systems provide data, with global coverage, for currents, temperature, and salinity in the open ocean, and are now being used in oil spill fate forecasting systems. This paper provides examples of how GODAE ocean forcing data are implemented in various oil spill modeling systems, including both through direct application and through nesting of local hydrodynamic models. Benefits of using GODAE data sets for oil spill modeling are improved prediction accuracy, global coverage, and the provision of alternative predictions for a given area.

Hackett, B., E. Comerma, P. Daniel, and H. Ichikawa. 2009. Marine oil pollution prediction. Oceanography 22(3):168–175, https://doi.org/10.5670/oceanog.2009.75.

Beegle-Krause, C.J. 2003. Advantages of separating the circulation model and trajectory model: GNOME trajectory model used with outside circulation models. Pp. 825–840 in Proceedings of the Arctic and Marine Oilspill Program 2003. Victoria, BC, Canada, June 10–12, 2003. Environment Canada, Ottawa, Ontario, volume 2.

Broström G., A. Carrasco, P. Daniel, B. Hackett, and D. Paradis. In press. Comparison of two oil drift models and different ocean forcing with observed drifter trajectories in the Mediterranean. Proceedings of the 5th International Conference on EuroGOOS. Exeter, UK, May 20–22, 2008. Office for Official Publications for the European Communities, Luxembourg.

Daniel, P., P. Josse, P. Dandin, J.-M. Lefevre, G. Lery, F. Cabioch, and V. Gouriou. 2004. Forecasting the prestige oil spills. Proceedings of the Interspill 2004 Conference. June 14–17, 2004, Trondheim, Norway. Available online at: http://www.interspill.com/PDFs/UK/2004/402_DANIEL.pdf (accessed June 11, 2009).

Daniel, P., P. Josse, and Ph. Dandin. 2005. Further improvement of drift forecast at sea based on operational oceanography systems. Pp 13–22 in Coastal Engineering VII, Modelling, Measurements, Engineering and Management of Seas and Coastal Regions. C.A. Brebbia and M. Da Conceicao, eds, WIT Press, Southampton, UK.

Galt, J.A. 1994. Trajectory analysis for oil spills. Journal of Advanced Marine Technology Conference 11:91–126.

Hackett, B., Ø. Breivik, and C. Wettre. 2006. Forecasting the drift of objects and substances in the ocean. Pp. 507–524 in Ocean Weather Forecasting: An Integrated View of Oceanography. E.P. Chassignet and J. Verron, eds, Springer, Dordrecht, The Netherlands.

Reed, M., Ø. Johansen, P.J. Brandvik, P.S. Daling, A. Lewis, R. Fiocco, D. Mackay, and R. Prentki. 1999. Oil spill modelling towards the close of the 20th century: Overview of the state of the art. Spill Science & Technology Bulletin 5(1):3–16.

Usui, N., S. Ishizaki, Y. Fujii, H. Tsujino, T. Yasuda, and M. Kamachi. 2006. Meteorological Research Institute Multivariate Ocean Variational Estimation (MOVE) system: Some early results. Advances in Space Research 37:806–822.

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