Natural Hazards

, Volume 64, Issue 2, pp 1425–1446 | Cite as

Extreme surface and near-bottom currents in the northwest Atlantic

  • Eric C. J. Oliver
  • Jinyu Sheng
  • Keith R. Thompson
  • Jorge R. Urrego Blanco
Original Paper


This study presents a methodology for estimating extreme current speeds from numerical model results using extremal analysis techniques. This method is used to estimate the extreme near-surface and near-bottom current speeds of the northwest Atlantic Ocean with 50-year return periods from 17 years of model output. The non-tidal currents produced by a three-dimensional ocean circulation model for the 1988–2004 period were first used to estimate and map the 17-year return period extreme current speeds at the surface and near the bottom. Extremal analysis techniques (i.e., fitting the annual maxima to the Type I probability distribution) are used to estimate and map the 50-year extreme current speeds. Tidal currents are dominant in some parts of the northwest Atlantic, and a Monte Carlo-based methodology is developed to take into account the fact that large non-tidal extrema may occur at different tidal phases. The inclusion of tidal currents in this way modifies the estimated 50-year extreme current speeds, and this is illustrated along several representative transects and depth profiles. Seasonal variations are examined by calculating the extreme current speeds for fall-winter and spring–summer. Finally, the distribution of extreme currents is interpreted taking into account (1) variability about the time-mean current speeds, (2) wind-driven Ekman currents, and (3) flow along isobaths.


Extreme current speeds Extremal analysis Northwest Atlantic Ocean circulation model Monte Carlo methods 



The authors would like to thank Kyoko Ohashi for providing the code used to generate tidal current predictions. The work was also supported by The Lloyd’s Register Educational Trust (The LRET), which is an independent charity working to achieve advances in transportation, science, engineering and technology education, training, and research worldwide for the benefit of all. The authors would also like to thank the anonymous reviewers for their constructive comments.


  1. Bernier N, Thompson K (2006) Predicting the frequency of storm surges and extreme sea levels in the northwest Atlantic. J Geophys Res 111(C10):C10,009CrossRefGoogle Scholar
  2. Bernier N, Thompson K, Ou J, Ritchie H (2007) Mapping the return periods of extreme sea levels: allowing for short sea level records, seasonality, and climate change. Global Planet Change 57(1–2):139–150CrossRefGoogle Scholar
  3. Carter D, Loyens J, Challenor P (1987) Estimates of extreme current speeds over the continental slope off Scotland. Institute of Oceanographic Sciences, Report 239 143Google Scholar
  4. Coles S (2001) An introduction to statistical modeling of extreme values. Springer, BerlinGoogle Scholar
  5. Coles S, Walshaw D (1994) Directional modelling of extreme wind speeds. Appl Stat 43(1):139–157Google Scholar
  6. Cook N (1985) The designer’s guide to wind loading of building structures. Part 1: background damage survey, wind data and structural classification. Building Research Establishment, Garston and Butterworths, LondonGoogle Scholar
  7. Csanady G (1982) Circulation in the coastal ocean. Springer, BerlinGoogle Scholar
  8. Dixon M, Tawn J, Vassie J (1998) Spatial modelling of extreme sea-levels. Environmetrics 9(3):283–301CrossRefGoogle Scholar
  9. Gaspar P, Grégoris Y, Lefevre J (1990) A simple eddy kinetic energy model for simulations of the oceanic vertical mixing: tests at station Papa and long-term upper ocean study site. J Geophys Res 95(C9):16179–16193CrossRefGoogle Scholar
  10. Geshelin Y, Sheng J, Greatbatch R (1999) Monthly mean climatologies of temperature and salinity in the western North Atlantic. Can Data Rep Hydrogr Ocean Sci. Fisheries and Ocean Canada 153Google Scholar
  11. Greatbatch R, Sheng J, Eden C, Tang L, Zhai X, Zhao J (2004) The semi-prognostic method. Cont Shelf Res 24(18):2149–2165CrossRefGoogle Scholar
  12. Griffies S, Hallberg R (2000) Biharmonic friction with a Smagorinsky-like viscosity for use in large-scale eddy-permitting ocean models. Mon Weather Rev 128(8):2935–2946CrossRefGoogle Scholar
  13. Griffiths C (1996) Extreme residual current speeds upon the UK continental shelf. Health and safety executive offshore technology report, OTH94/437 43Google Scholar
  14. Gumbel E (1958) Statistics of extremes. Columbia University Press, New YorkGoogle Scholar
  15. Hennessey J (1977) Some aspects of wind power statistics. J Appl Met 16(2):119–128CrossRefGoogle Scholar
  16. Hohenegger C, Schar C (2007) Atmospheric predictability at synoptic versus cloud-resolving scales. Bull Am Meteorol Soc 88(11):1783–1794CrossRefGoogle Scholar
  17. Kim S, Matsumi Y, Yasuda T, mase H (2010) Mechanism of abnormal storm surges after passage of typhoons around west coasts of the sea of Japan. J Jpn Soc Civil Eng Ser B2 (Coast Eng) 66(1):221–225Google Scholar
  18. Kundu P (1990) Fluid mechanics. Academic Press, LondonGoogle Scholar
  19. Large W, Pond S (1981) Open ocean momentum flux measurements in moderate to strong winds. J Phys Oceanogr 11(3):324–336CrossRefGoogle Scholar
  20. Large W, Yeager S (2004) Diurnal to decadal global forcing for ocean and sea-ice models: the data sets and flux climatologies. National Center for Atmospheric Research, BoulderGoogle Scholar
  21. Leadbetter M, Lindgren G, Rootzén H (1983) Extremes and related properties of random sequences and processes, vol 11. Springer, BerlinCrossRefGoogle Scholar
  22. Loder J, Petrie B, Gawarkiewicz G (1998) The coastal ocean off northeastern North America: a large-scale view. Sea 11:105–133Google Scholar
  23. Lyard F, Lefevre F, Letellier T, Francis O (2006) Modelling the global ocean tides: modern insights from fes2004. Ocean Dyn 56(5):394–415CrossRefGoogle Scholar
  24. Madec G (2008) NEMO ocean engine. Institut Pierre-Simon Laplace (IPSL), FranceGoogle Scholar
  25. Marchesiello P, McWilliams J, Shchepetkin A (2001) Open boundary conditions for long-term integration of regional oceanic models. Ocean Model 3(1–2):1–20CrossRefGoogle Scholar
  26. Palutikof J, Brabson B, Lister D, Adcock S (1999) A review of methods to calculate extreme wind speeds. Meteorol Appl 6(02):119–132CrossRefGoogle Scholar
  27. Pawlowicz R, Beardsley B, Lentz S (2002) Classical tidal harmonic analysis including error estimates in MATLAB using T_TIDE. Comput Geosci 28(8):929–937CrossRefGoogle Scholar
  28. Powell M, Vickery P, Reinhold T (2003) Reduced drag coefficient for high wind speeds in tropical cyclones. Nature 422(6929):279–283CrossRefGoogle Scholar
  29. Pugh D (1982) Estimating extreme currents by combining tidal and surge probabilities. Ocean Eng 9(4):361–372CrossRefGoogle Scholar
  30. Pugh D, Vassie J (1980) Application of the joint probability method for extreme sea level computations. Proc Inst Civ Eng Part 2(69):959–975CrossRefGoogle Scholar
  31. Sheng J, Tang L (2003) A numerical study of circulation in the western Caribbean Sea. J Phys Oceanogr 33(10):2049–2069CrossRefGoogle Scholar
  32. Sheng J, Greatbatch R, Wright D (2001) Improving the utility of ocean circulation models through adjustment of the momentum balance. J Geophys Res 106(C8):16,711–16CrossRefGoogle Scholar
  33. Smith W, Sandwell D (1997) Global sea floor topography from satellite altimetry and ship depth soundings. Science 277(5334):1956CrossRefGoogle Scholar
  34. Stevens D (1990) On open boundary conditions for three dimensional primitive equation ocean circulation models. Geophys Astrophys Fluid Dyn 51(1–4):103–133CrossRefGoogle Scholar
  35. Tawn J (1992) Estimating probabilities of extreme sea-levels. Appl Stat 41(1):77–93Google Scholar
  36. Tawn J, Vassie J (1989) Extreme sea levels: the joint probability method revisited and revised. Proc Inst Civ Eng Part 2(87):429–442CrossRefGoogle Scholar
  37. Thompson K, Wright D, Lu Y, Demirov E (2006) A simple method for reducing seasonal bias and drift in eddy resolving ocean models. Ocean Model 13(2):109–125CrossRefGoogle Scholar
  38. Timmermann R, Goosse H, Madec G, Fichefet T, Ethe C, Dulière V (2005) On the representation of high latitude processes in the ORCA-LIM global coupled sea ice-ocean model. Ocean Model 8(1–2):175–201CrossRefGoogle Scholar
  39. Urrego-Blanco J, Sheng J (2012) Interannual variability of the circulation over the eastern Canadian shelf. Atmos Ocean. doi: 10.1080/07055900.2012.680430
  40. Wu Y, Tang C, Li M, Prescott R (2011) Modelling extreme storm-induced currents over the grand banks. Atmos Ocean 49(3):259–268CrossRefGoogle Scholar
  41. Zwiers F (1987) An extreme-value analysis of wind speeds at five Canadian locations. Can J Stat 15(4):317–327CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Eric C. J. Oliver
    • 1
    • 2
  • Jinyu Sheng
    • 1
  • Keith R. Thompson
    • 1
  • Jorge R. Urrego Blanco
    • 1
  1. 1.Department of OceanographyDalhousie UniversityHalifaxCanada
  2. 2.Institute for Marine and Antarctic StudiesUniversity of TasmaniaHobartAustralia

Personalised recommendations