Articles | Volume 9, issue 2
https://doi.org/10.5194/essd-9-955-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/essd-9-955-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Data review article
| 
04 Dec 2017
Data review article |
| 04 Dec 2017
A multi-decadal wind-wave hindcast for the North Sea 1949–2014: coastDat2
Institute for Coastal Research, Helmholtz-Zentrum Geesthacht, 21502 Geesthacht, Germany
Ralf Weisse
Institute for Coastal Research, Helmholtz-Zentrum Geesthacht, 21502 Geesthacht, Germany
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Cited
20 citations as recorded by crossref.
- Long-term statistics of potentially hazardous sea states in the North Sea 1958–2014 T. Teich et al. https://doi.org/10.1007/s10236-018-1210-4
- Correlation of Concurrent Extreme Metocean Hazards Considering Seasonality F. Calderón-Vega et al. https://doi.org/10.3390/app10144794
- EFFECT OF WAVES TO DYNAMIC RESPONSE OF MONOPILE-TYPE OFFSHORE WIND POWER GENERATION FACILITY H. KASHIMA & H. YONEYAMA https://doi.org/10.2208/jscejoe.76.2_I_887
- Wind and wave energy resource of Germany reported by ERA-Interim reanalysis data E. Rusu et al. https://doi.org/10.1051/e3sconf/201912204003
- How does the selection of wave hindcast datasets and statistical models influence the probabilistic design of offshore scour protections? R. Figueiredo et al. https://doi.org/10.1016/j.oceaneng.2022.113123
- The SPAR Model: A New Paradigm for Multivariate Extremes: Application to Joint Distributions of Metocean Variables E. Mackay et al. https://doi.org/10.1115/1.4065968
- Predicting wave heights for marine design by prioritizing extreme events in a global model A. Haselsteiner & K. Thoben https://doi.org/10.1016/j.renene.2020.04.112
- New estimation methods for extremal bivariate return curves C. Murphy‐Barltrop et al. https://doi.org/10.1002/env.2797
- A benchmarking exercise for environmental contours A. Haselsteiner et al. https://doi.org/10.1016/j.oceaneng.2021.109504
- The large-scale impact of offshore wind farm structures on pelagic primary productivity in the southern North Sea K. Slavik et al. https://doi.org/10.1007/s10750-018-3653-5
- The Role of Boundary Mixing for Diapycnal Oxygen Fluxes in a Stratified Marine System P. Holtermann et al. https://doi.org/10.1029/2022GL098917
- Quantifying tropical-cyclone-generated waves in extreme-value-derived design for offshore wind S. McElman et al. https://doi.org/10.5194/wes-10-1529-2025
- Development of a Comparison Framework for Evaluating Environmental Contours of Extreme Sea States A. Eckert et al. https://doi.org/10.3390/jmse9010016
- Long-term shoreline changes at large spatial scales at the Baltic Sea: remote-sensing based assessment and potential drivers J. Tiede et al. https://doi.org/10.3389/fmars.2023.1207524
- A hydrographic dataset of the Wadden Sea as a foundation for a digital twin of the coastal ocean R. Lepper et al. https://doi.org/10.1038/s41597-025-06211-1
- Application of nested artificial neural network for the prediction of significant wave height A. Mahdavi-Meymand & W. Sulisz https://doi.org/10.1016/j.renene.2023.03.118
- Development of pyramid neural networks for prediction of significant wave height for renewable energy farms A. Mahdavi-Meymand & W. Sulisz https://doi.org/10.1016/j.apenergy.2024.123009
- Intercomparison of Assimilated Coastal Wave Data in the Northwestern Pacific Area Y. Hisaki https://doi.org/10.3390/jmse8080579
- An integrated marine data collection for the German Bight – Part 2: Tides, salinity, and waves (1996–2015) R. Hagen et al. https://doi.org/10.5194/essd-13-2573-2021
- Long-term extreme response of an offshore turbine: How accurate are contour-based estimates? A. Haselsteiner et al. https://doi.org/10.1016/j.renene.2021.09.077
20 citations as recorded by crossref.
- Long-term statistics of potentially hazardous sea states in the North Sea 1958–2014 T. Teich et al. https://doi.org/10.1007/s10236-018-1210-4
- Correlation of Concurrent Extreme Metocean Hazards Considering Seasonality F. Calderón-Vega et al. https://doi.org/10.3390/app10144794
- EFFECT OF WAVES TO DYNAMIC RESPONSE OF MONOPILE-TYPE OFFSHORE WIND POWER GENERATION FACILITY H. KASHIMA & H. YONEYAMA https://doi.org/10.2208/jscejoe.76.2_I_887
- Wind and wave energy resource of Germany reported by ERA-Interim reanalysis data E. Rusu et al. https://doi.org/10.1051/e3sconf/201912204003
- How does the selection of wave hindcast datasets and statistical models influence the probabilistic design of offshore scour protections? R. Figueiredo et al. https://doi.org/10.1016/j.oceaneng.2022.113123
- The SPAR Model: A New Paradigm for Multivariate Extremes: Application to Joint Distributions of Metocean Variables E. Mackay et al. https://doi.org/10.1115/1.4065968
- Predicting wave heights for marine design by prioritizing extreme events in a global model A. Haselsteiner & K. Thoben https://doi.org/10.1016/j.renene.2020.04.112
- New estimation methods for extremal bivariate return curves C. Murphy‐Barltrop et al. https://doi.org/10.1002/env.2797
- A benchmarking exercise for environmental contours A. Haselsteiner et al. https://doi.org/10.1016/j.oceaneng.2021.109504
- The large-scale impact of offshore wind farm structures on pelagic primary productivity in the southern North Sea K. Slavik et al. https://doi.org/10.1007/s10750-018-3653-5
- The Role of Boundary Mixing for Diapycnal Oxygen Fluxes in a Stratified Marine System P. Holtermann et al. https://doi.org/10.1029/2022GL098917
- Quantifying tropical-cyclone-generated waves in extreme-value-derived design for offshore wind S. McElman et al. https://doi.org/10.5194/wes-10-1529-2025
- Development of a Comparison Framework for Evaluating Environmental Contours of Extreme Sea States A. Eckert et al. https://doi.org/10.3390/jmse9010016
- Long-term shoreline changes at large spatial scales at the Baltic Sea: remote-sensing based assessment and potential drivers J. Tiede et al. https://doi.org/10.3389/fmars.2023.1207524
- A hydrographic dataset of the Wadden Sea as a foundation for a digital twin of the coastal ocean R. Lepper et al. https://doi.org/10.1038/s41597-025-06211-1
- Application of nested artificial neural network for the prediction of significant wave height A. Mahdavi-Meymand & W. Sulisz https://doi.org/10.1016/j.renene.2023.03.118
- Development of pyramid neural networks for prediction of significant wave height for renewable energy farms A. Mahdavi-Meymand & W. Sulisz https://doi.org/10.1016/j.apenergy.2024.123009
- Intercomparison of Assimilated Coastal Wave Data in the Northwestern Pacific Area Y. Hisaki https://doi.org/10.3390/jmse8080579
- An integrated marine data collection for the German Bight – Part 2: Tides, salinity, and waves (1996–2015) R. Hagen et al. https://doi.org/10.5194/essd-13-2573-2021
- Long-term extreme response of an offshore turbine: How accurate are contour-based estimates? A. Haselsteiner et al. https://doi.org/10.1016/j.renene.2021.09.077
Saved (final revised paper)
Latest update: 24 Aug 2026
Short summary
A wave hindcast for the North Sea covering the period 1949–2014 using the third-generation spectral wave model WAM was produced. The hindcast is part of the coastDat database representing a consistent and homogeneous met-ocean data set. It is shown that, despite not being perfect, data from the wave hindcast are generally suitable for wave climate analysis.
A wave hindcast for the North Sea covering the period 1949–2014 using the third-generation...
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