Offshore wind farm facing extreme wave conditions.

Navigating Extreme Ocean Waves: How Safe Are Offshore Wind Farms?

Reese Marlowe in Climate & Environment September 2025 • 4 min read.

"A deep dive into the science of predicting rogue waves and their impact on the future of renewable energy infrastructure."

The quest for renewable energy sources has led to increased interest in offshore wind turbine installations. Unlike land-based wind farms, these structures require relatively shallow waters to be economically feasible. The Doggerbank area in the southern North Sea is a prime location, but it presents unique challenges. Water depth varies significantly, from approximately 60 meters in the north to just 20 meters in the south, posing complex engineering problems.

Designing these bottom-fixed wind turbines demands a thorough understanding of environmental forces, especially extreme wave conditions. Predicting these conditions is crucial, but it comes with inherent uncertainties. While wave kinematics and structural loads are important, the ability to forecast the most powerful waves remains paramount for ensuring the safety and longevity of these renewable energy giants.

Reliable metocean data—meteorological and oceanographic information—is essential for accurate predictions. For the North Sea, the Norwegian Meteorological Institute's NORA10 hindcast model provides valuable data. While NORA10 is accurate for deeper waters, its effectiveness in reflecting changing wave conditions in shallower waters (less than 70 meters) is less certain. The model's spatial resolution of 10 km may not fully capture the complexities of wave behavior as water depths decrease.

The Science of Extreme Wave Prediction: Unpacking the Models

Offshore wind farm facing extreme wave conditions.

To address these uncertainties, scientists are comparing NORA10 data with results from SWAN (Simulating Waves Nearshore), a widely used shallow-water hindcast model. SWAN is designed to simulate wave generation, propagation, and dissipation in coastal regions, accounting for factors like wave shoaling and breaking. By comparing the two models, researchers hope to refine their understanding of wave behavior in the variable water depths of the Doggerbank area.

One key aspect of this research is evaluating SWAN's default parameters for accurately reflecting wave condition changes over sloping bottoms. This involves comparing model outputs with physical model test results to ensure the model's parameters are correctly calibrated. The goal is to ensure that SWAN accurately predicts how waves evolve as they move from deeper to shallower waters.

NORA10: A high-resolution hindcast model providing metocean data from 1957 to present. Known for good agreement with measured data in deep and moderate water depths.
SWAN (Simulating Waves Nearshore): A shallow-water hindcast model designed to simulate wave processes in coastal areas. Accounts for wave generation, propagation, and dissipation.
Environmental Contour Concept: A method used to determine extreme sea conditions by analyzing joint probability density functions of significant wave height and peak period.

Extreme wave conditions are established using NORA10 data for two locations 102.5 km apart along a north-south line. The northern position, assumed to provide good estimates, serves as input for SWAN. The wave evolution southward is then analyzed, and results from the two models are compared at the southern position. Discrepancies between the models can highlight areas where SWAN may need refinement to better capture the true wave behavior.

Future Directions: Ensuring the Safety of Offshore Wind Farms

Ultimately, this research contributes to safer and more reliable designs for offshore wind turbines. By understanding how extreme wave conditions evolve in shallow water environments, engineers can better protect these structures from potential damage. Further studies, including in-situ measurements and refined modeling techniques, are essential to reduce uncertainties and ensure the long-term viability of offshore wind energy as a key component of our renewable energy future.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: 10.1115/1.4033564, Alternate LINK

Title: Extreme Wave Condition At Doggerbank

Subject: Mechanical Engineering

Journal: Journal of Offshore Mechanics and Arctic Engineering

Publisher: ASME International

Authors: Espen Engebretsen, Sverre K. Haver, Dag Myrhaug

Published: 2016-06-02

Everything You Need To Know

Why is the Doggerbank area of interest for offshore wind farms, and what unique challenges does it present?

The Doggerbank area in the southern North Sea is appealing for offshore wind farms due to its relatively shallow waters, making turbine installation economically feasible. However, the water depth varies significantly, from 60 meters in the north to 20 meters in the south. This variation poses complex engineering problems and necessitates a thorough understanding of how extreme wave conditions behave across changing water depths to ensure structural integrity and longevity of wind turbines.

What is the significance of using metocean data, such as that from NORA10, in designing offshore wind turbines?

Reliable metocean data, specifically from sources like the Norwegian Meteorological Institute's NORA10 hindcast model, is essential for accurately predicting extreme wave conditions in the North Sea. These predictions are crucial for designing offshore wind turbines that can withstand the environmental forces they will encounter. While NORA10 is accurate in deeper waters, its reliability decreases in shallower waters (less than 70 meters), requiring further investigation and comparison with models more suited to shallow water environments. This highlights the need for integrating data from multiple sources to minimize uncertainties in design parameters.

How does the SWAN model enhance our understanding of wave behavior in shallow water environments like the Doggerbank?

SWAN (Simulating Waves Nearshore) is specifically designed to simulate wave generation, propagation, and dissipation in coastal regions. It accounts for factors such as wave shoaling and breaking, which are critical in shallow water environments. By comparing SWAN's outputs with data from NORA10, researchers can refine their understanding of wave behavior as waves move from deeper to shallower waters. This comparison allows for the calibration of SWAN's parameters to accurately reflect wave condition changes over sloping bottoms, ensuring that the model effectively predicts wave evolution in complex coastal terrains. However, understanding sediment transport and seabed interactions remains a consideration not directly addressed.

What is the Environmental Contour Concept, and how is it utilized in assessing extreme sea conditions for offshore wind farms?

The Environmental Contour Concept is a method for determining extreme sea conditions by analyzing joint probability density functions of significant wave height and peak period. While not explicitly detailed, this approach enables engineers to estimate the likelihood of specific combinations of wave parameters occurring, which is vital for designing structures that can withstand the most severe conditions. This is a statistical method used for risk assessment, and helps in creating robust designs that can handle rare, but potentially catastrophic, wave events. However, the accuracy of the contour is strongly dependent on the accuracy and length of the data sets used for the statistical analysis.

What are the future directions in ensuring the safety and reliability of offshore wind farms considering extreme wave conditions?

Future directions involve further studies, including in-situ measurements and refined modeling techniques, to reduce uncertainties in predicting extreme wave conditions. Comparing NORA10 data with SWAN model results is one step. More work is needed to ensure the long-term viability of offshore wind energy. Accurately predicting extreme wave conditions in shallow water environments will allow engineers to better protect these structures from potential damage. Also, improvements of spatial resolution of models like NORA10 will better capture wave complexities.