Ocean Dynamics

, Volume 56, Issue 1, pp 26–35 | Cite as

Estimating near-shore wave statistics from regional hindcasts using downscaling techniques

  • Lidia GaslikovaEmail author
  • Ralf Weisse
Original paper


Several downscaling techniques, comprising fully dynamical and statistical–dynamical methods applied to near-shore local wave climate, are tested and assessed in terms of wave statistics with respect to the added value that can be achieved compared to larger scale data. The techniques are applied for the example of Helgoland, a small island in the German Bight. It was found that an improved representation could generally be obtained from all downscaling techniques by comparing the near-shore wave climate. Based on a balance between the required computer resources and the improvements achieved, it is suggested, to this end, that a dynamical–statistical approach based on high-resolution coastal wave modeling and linear regression provides the optimal choice.


Shallow water Wave climate Coastal protection Statistical downscaling 



We would like to thank Gerhard Gayer and Heinz Günther for the numerous valuable discussions and help with the K-model. We are grateful to Dieter Schrader from the BSH (Federal Maritime and Hydrographic Agency) and Olaf Outzen from Oceanwaves GmbH for providing us with observational data and useful comments. We want to thank Eduardo Zorita who helped us with statistical methods, provided subroutines for the Analog and CCA methods and gave useful advice. We also thank Norbert Winkel and Andreas Pluess from BAW for kindly providing topography and water level data.


  1. Caires S, Sterl A, Bidlot J-R, Graham N, Swail V (2002) Climatological assessment of reanalysis ocean data. In: Proceedings of the 7th international workshop on wave hindcasting and forecasting, Banff, Alberta, Canada, 21–25 October 2002Google Scholar
  2. Cavaleri L, Rizzoli PM (1981) Wind wave prediction in shallow water — theory and application. J Geophys Res 86:10961–10973CrossRefGoogle Scholar
  3. Coastal Engineering Manual, CHL, available at
  4. Cox AT, Swail VR (2001) A global wave hindcast over the period 1958–1997: validation and climate assessment. J Geophys Res 106(C2):2313–2329CrossRefGoogle Scholar
  5. Eurowaves project, available at
  6. Feser F, Weisse R, von Storch H (2001) Multi-decadal atmospheric modeling for Europe yields multipurpose data. EOS Trans 82(28):305–310CrossRefGoogle Scholar
  7. Günther H and Rosenthal W (1995) A wave model with nonlinear dissipation source function. In: Proceedings of the 4th International workshop on wave hindcasting and forecasting, Banff, Canada, 16–20 October 1995Google Scholar
  8. Günther H, Rosenthal W, Stawarz M, Carretero JC, Gomez M, Lozano I, Serrano O, Reistad M (1998) The wave climate of the Northeast Atlantic over the period 1955–1994: the WASA wave hindcast. Global Atmos Ocean Syst 6:121–163Google Scholar
  9. Hasselmann K (1974) On the spectral dissipation of ocean waves due to white capping. Boundary–Layer Meteorol 6:107–127Google Scholar
  10. Hasselmann K, Barnett TP, Bouws E, Carlson H, Cartwright DE, Enke K, Ewing JA, Gienapp H, Hasselmann DE, Kruseman P, Meerburg A, Müeller P, Olbers DJ, Richter K, Sell W, Walden H (1973) Measurements of wind–wave growth and swell decay during the Joint North Sea Wave Project (JONSWAP). D Hydrogr Z A8(12):1–95Google Scholar
  11. Hessner K, Reichert K, Dittmer J, Nieto Borge JC, Günther H (2001) Evaluation of WaMoS wave data. In: Proceedings of the WAVES 2001 conference, San Francisco, 2–6 September 2001Google Scholar
  12. JERICHO project, available at
  13. Kushnir Y (1997) The recent increase in North Atlantic Wave Heights. J Climate 10(8):2107–2113CrossRefGoogle Scholar
  14. Moghimi S, Gayer G, Günther H, Shafieefar M (2005) Application of 3rd generation shallow water wave models in a tidal environment. Ocean Dyn 55(1):10–27CrossRefGoogle Scholar
  15. Schneggenburger C (1998) Spectral wave modelling with nonlinear dissipation. Ph.D. thesis, University of HamburgGoogle Scholar
  16. Schneggenburger C, Günther H, Rosenthal W (1997) Shallow water wave modelling with nonlinear dissipation, Dtsch Hydrogr Z 49:431–444CrossRefGoogle Scholar
  17. Soares CG, Weisse R, Carretero JC, Alvarez E (2002) A 40-years hindcast of wind, sea level and waves in European waters. In: Proceedings of the 21st international conference on offshore mechanics and arctic engineering, Oslo, Norway, 23–28 June 2002Google Scholar
  18. Sterl A, Komen GJ, Cotton PD (1998) Fifteen years of global wave hindcasts using winds from the European Centre for medium-range weather forecasts reanalysis: validating the reanalyzed winds and assessing wave climate. J Geophys Res 103:5477–5492CrossRefGoogle Scholar
  19. Vierfuss U (2002) Ermittlung der Seegangsbelastung für Helgoländer Molenbauwerke. Hansa 139:68–73Google Scholar
  20. von Storch H, Zwiers FW (1999) Statistical analysis in climate research. Cambridge University Press, CambridgeGoogle Scholar
  21. WAMDI Group (1988) The WAM model — a third generation ocean wave prediction model. J Phys Oceanogr 18:1775–1810CrossRefGoogle Scholar
  22. WASA Group (1998) Changing waves and storms in the Northeast Atlantic? Bull Am Meteorol Soc 79(5):741–760CrossRefGoogle Scholar
  23. Weisse R, Feser F, Günther H (2002) A 40-year high-resolution wind and wave hindcast for the Southern North Sea. In: Proceedings of the 7th international workshop on wave hindcasting and forecasting, Banff, Alberta, Canada, 21–25 October 2002, pp 97–104Google Scholar
  24. Weisse R, Feser F, Günther H (2003) Wind-und Seegangsklimatologie 1958–2001 für die südliche Nordsee basierend auf Modellrechnungen. GKSS 2003/10 GKSS ForschungszentrumGoogle Scholar
  25. Zorita E, von Storch H (1999) The analog method as a simple statistical downscaling technique: comparison with more complicated methods. J Climate 12:2474–2489CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  1. 1.Institute for Coastal ResearchGKSS Research CentreGeesthachtGermany

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