Towards Sub-Regional Digital Twins of the Ocean for Integrated Offshore Wind Energy Impact Studies

Recently started the Digital Twin of the Ocean for Offshore Wind Energy (DTO4OWF) project is a 36-month European research and innovation project supporting the sustainable expansion of offshore wind energy in the Baltic and North Seas (BS & NS). According to EMODnet, more than 300 offshore wind farms are planned in EU waters over the incoming decade. This rapid development poses significant challenges related to ecosystem protection and biodiversity conservation, while simultaneously requiring efficient use of wind resources and marine space across multiple temporal scales.
DTO4OWF addresses these challenges through the development of fit-for-purpose, sub-regional Digital Twins of the Ocean (DTOs) that will integrate coupled physical, biogeochemical, ecological, and climate processes. The DTOs will be built using high-resolution, process-based numerical models, constrained by in situ observations, satellite remote sensing, and data assimilation techniques. Machine learning methods are employed to enhance model performance, reduce computational costs, and support scenario-based analyses. The project focuses on five key areas within BS and NS basins, selected to represent contrasting environmental conditions and different stages of offshore wind farm development. For each area, the DTO framework enables the assessment of offshore wind farm impacts across multiple spatial and temporal scales, including short-term operational effects and long-term climate-related changes. The resulting decision-support tools facilitate optimized site selection, safer operations, improved environmental impact assessments, and sustainable marine spatial planning. All applications are designed to be transferable to other European regions and interoperable with EDITO, Destination Earth, and EMODnet infrastructures.
The DTO4OWF consortium consists of 11 partners, and the project leader is Tallinn University of Technology (TalTech, Estonia). The IOPAN contributions focuses on offshore wind farms located in the southern Baltic Sea, with particular emphasis on offshore wind farm–sea ice interactions. The methodological approach is based on high-resolution numerical simulations using the Community Ice CodE (CICE) model, including fast-ice parameterization adapted to shallow, semi-enclosed basin conditions. Model experiments are designed to compare baseline simulations with scenarios including offshore wind farm infrastructure, represented through modified boundary conditions and obstacle-induced ice attachment processes. The simulations are evaluated using available observational data on sea ice extent, thickness, and duration, enabling qualitative and quantitative assessment of wind farm impacts on ice dynamics. This contribution presents the methodological framework, planned sensitivity experiments, and preliminary results illustrating the potential role of offshore wind farms in fast ice formation in the southern Baltic Sea.

Digital Twin of the Ocean for Offshore Wind Energy (DTO4OWE), under the framework of the Sustainable Blue Economy Partnership (SBEP), funded by the National Centre for Research and Development.