Introduction and Background

Chapter
Part of the Ocean Engineering & Oceanography book series (OEO, volume 2)

Abstract

This chapter gives an introduction to the problem area and motivates the research into stochastic models of ocean waves. The importance of knowledge about the environmental operating conditions for ships and other marine structures is emphasized. Furthermore, it is argued that climate change may have an effect on future ocean wave climate and that this needs to be taken into account already in the design process. Integrated sea state parameters such as significant wave height are briefly introduced as a sensible way of describing sea states and various sources of wave are discussed.

Keywords

Wave Height Emission Scenario Wave Period Significant Wave Height Markov Random Field 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Arrhenius, S.: On the influence of carbonic acid in the air upon the temperature of the ground. Philos. Mag. J. Sci. 41, 237–276 (1896)CrossRefGoogle Scholar
  2. 2.
    Bernardo, J.M., Smith, A.F.: Bayesian theory. Wiley, Chichester (1994)Google Scholar
  3. 3.
    Bitner-Gregersen, E.M., Eide, L.I., Toffoli, A., Eide, M.: White paper on effect of climate change on marine structure design. Technical Report No UCTNO911 2008–1014, Det Norske, Veritas (2009)Google Scholar
  4. 4.
    Bitner-Gregersen, E.M., Hørte, T., Skjong, R.: Potential impact of climate change on tanker design. In: Proceedings of the 30th International Conference on Ocean, Offshore and Arctic Engineering (OMAE 2011). American Society of Mechanical Engineers (ASME) (2011)Google Scholar
  5. 5.
    Callendar, G.S.: The artificial production of carbon dioxide and its influence on temperature. Q. J. R. Meteorol. Soc. 64, 223–240 (1938)Google Scholar
  6. 6.
    Collins, M., Chandler, R.E., Cox, P.M., Huthnance, J.M., Rougier, J.: Quantifying future climate change. Nat. clim. change 2, 403–409 (2012)CrossRefGoogle Scholar
  7. 7.
    Corbella, S., Stretch, D.D.: Multivariate return periods of sea storms for coastal erosion risk assessment. Nat. Hazards Earth Syst. Sci. 12, 2699–2708 (2012)CrossRefGoogle Scholar
  8. 8.
    Cressie, N., Wikle, C.K.: Statistics for spatio-temporal data. Wiley, Hoboken (2011)Google Scholar
  9. 9.
    Dessler, A.E.: Introduction to modern climate change. Cambridge University Press, Cambridge (2012)Google Scholar
  10. 10.
    Grabemann, I., Weisse, R.: Climate change impact on extreme wave conditions in the North Sea: an ensemble study. Ocean Dyn. 58, 199–212 (2008)CrossRefGoogle Scholar
  11. 11.
    Group, T.W., Cavaleri, L., Alves, J.H., Ardhuin, F., Babanin, A., Banner, M., Belibassakis, K., Benoit, M., Donelan, M., Groeneweg, J., Herbers, T., Hwang, P., Janssen, P., Janssen, T., Lavrenov, I., Magne, R., Monbaliu, J., Onorato, M., Polnikov, V., Resio, D., Rogers, W., Sheremet, A., McKee Smith, J., Tolman, H., van Vledder, G., Wolf, J., Young, I.: Wave modelling—the state of the art. Prog. Oceanogr. 75, 603–674 (2007)CrossRefGoogle Scholar
  12. 12.
    Haver, S., Winterstein, S.: Environmental contour lines: a method for estimating long term extremes by a short term anaysis. Trans. Soc. Naval Archit. Marine Eng. 116, 116–127 (2009)Google Scholar
  13. 13.
    IPCC: Climate Change: The IPCC scientific assessment. Cambridge University Press, Cambridge (1990)Google Scholar
  14. 14.
    IPCC: Climate Change 1995: The science of climate change. Cambridge University Press, Cambridge (1996)Google Scholar
  15. 15.
    IPCC: Climate Change 2001: The scientific basis. Cambridge University Press, Cambridge (2001)Google Scholar
  16. 16.
    IPCC: Climate Change 2007: The physical sciences basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge (2007)Google Scholar
  17. 17.
    IPCC: Managing the risks of extreme events and disasters to advance climate change adaptation. Cambridge University Press, Cambridge (2011)Google Scholar
  18. 18.
    Longuet-Higgins, M.S.: On the statistical distribution of the height of sea waves. J. Mar. Res. 11, 245–266 (1952)Google Scholar
  19. 19.
    Meinshause, M., Smith, S.J., Calvin, K., Daniel, J.S., Kainuma, M.L.T., Lamarque, J.F., Matsumoto, K., Montzka, S.A., Raper, S.C.B., Riahi, K., Thomson, A., Velders, G.J.M., van Vuuren, D.P.P.: The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Clim. Change 109, 213–241 (2011)CrossRefGoogle Scholar
  20. 20.
    Mínguez, R., Tomás, A., Méndez, F.J., Medina, R.: Mixed extreme wave climate model for reanalysis databases. Stoch. Env. Res. Risk Assess. 27, 757–768 (2013)CrossRefGoogle Scholar
  21. 21.
    Moss, R.H., Edmonds, J.A., Hibbard, K.A., Manning, M.R., Rose, S.K., van Vuuren, D.P., Carter, T.R., Emori, S., Kainuma, M., Kram, T., Meehl, G.A., Mitchell, J.F.B., Nakicenovic, N., Riahi, K., Smith, S.J., Stouffer, R.J., Thomson, A.M., Weyant, J.P., Wilbanks, T.J.: The next generation of scenarios for climate change research and assessment. Nature 463, 747–756 (2010)CrossRefGoogle Scholar
  22. 22.
    Nakićenović, N., Alcamo, J., Davis, G., de Vries, B., Fenhann, J., Gaffin, S., Gregory, K., Grügler, A., Jung, T.Y., Kram, T., La Rovere, E.L., Michaelis, L., Mori, S., Morita, T., Pepper, W., Pitcher, H., Price, L., Riahi, K., Roehrl, A., Rogner, H.H., Sankovski, A., Schlesinger, M., Shukla, P., Smith, S., Swart, R., van Rooijen, S., Victor, N., Dadi, Z.: Emissions scenarios. Cambridge University Press, Cambridge (2000)Google Scholar
  23. 23.
    Natvig, B., Tvete, I.F.: Bayesian hierarchical space-time modeling of earthquake data. Methodol. Comput. Appl. Probab. 9, 89–114 (2007)MathSciNetCrossRefMATHGoogle Scholar
  24. 24.
    Prigogine, I.: The end of certainty. Free Press, New York (1997)Google Scholar
  25. 25.
    Smith, R.L.: Environmental statistics. University of North Carolina (2001). http://www.stat.unc.edu/postscript/rs/envnotes.pdf. Accessed 21 Oct 2010
  26. 26.
    Stephenson, D.B., Collins, M., Rougier, J.C., Chandler, R.E.: Statistical problems in the probabilistic prediction of climate change. Environmetrics 23, 364–372 (2012)MathSciNetCrossRefGoogle Scholar
  27. 27.
    von Storch, H., Zwiers, F.W.: Statistical analysis in climate research. Cambridge University Press, Cambridge (1999)Google Scholar
  28. 28.
    Talley, L.D., Pickard, G.L., Emery, W.J., Swift, J.H.: Descriptive physical oceanography an introduction, 6th edn. Elsevier, Boston (2011)Google Scholar
  29. 29.
    Tebaldi, C., Knutti, R.: The use of the multi-model ensemble in probabilistic climate projections. Philos. Trans. R. Soc. A 365, 2053–2075 (2007)MathSciNetCrossRefGoogle Scholar
  30. 30.
    Vanem, E., Walker, S.E.: Identifying trends in the ocean wave climate by time series analyses of significant wave height data. Ocean Eng. 61, 148–160 (2012)CrossRefGoogle Scholar
  31. 31.
    van Vuuren, D.P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G.C., Kram, T., Krey, V., Lamarque, J.F., Masui, T., Meinshausen, M., Nakicenovic, N., Smith, S.J., Rose, S.K.: The representative concentration pathways: an overview. Clim. Change 109, 5–31 (2011)Google Scholar
  32. 32.
    West, M., Harrison, J.: Bayesian forecasting and dynamic models, 2nd edn. Springer, Heidelberg (1997)Google Scholar
  33. 33.
    Wikle, C.K.: Hierarchical Bayesian models for predicting the spread of ecological processes. Ecology 84, 1382–1392 (2003)CrossRefGoogle Scholar
  34. 34.
    Wikle, C.K.: Hierarchical models in environmental science. Int. Stat. Rev. 71, 181–199 (2003)CrossRefMATHGoogle Scholar
  35. 35.
    Wikle, C.K., Berliner, L.M., Cressie, N.: Hierarchical Bayesian space-time models. Environ. Ecol. Stat. 5, 117–154 (1998)CrossRefGoogle Scholar
  36. 36.
    Wikle, C.K., Milliff, R.F., Nychka, D., Berliner, L.M.: Spatiotemporal hierarchical Bayesian modeling: tropical ocean surface winds. J. Am. Stat. Assoc. 96, 382–397 (2001)MathSciNetCrossRefMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Mathematics DepartmentUniversity of OsloOsloNorway

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