Unlocking the potential of offshore wind energy through an AI approach based on satellite insights

The Mediterranean Sea holds strategic potential for offshore wind energy essential to decarbonization. However, exploiting this potential requires high-quality, long-term metocean data to support wind farm plan- ning, installation, and operation. The Mediterranean’s distinctive geography, including its islands, archipelagos, and jagged coastlines, complicates the acquisition of accurate metocean information. While in-situ sensors provide high-accuracy data, they lack sufficient spatial and temporal coverage, and traditional numerical models often lack the resolution needed for detailed environmental insights. The approach proposed by the authors, referred to here as MESPAC, addresses these challenges by inte- grating satellite data with in-situ measurements through AI-driven algorithms, enhancing data reliability and availability. Unlike traditional approaches, where satellite data are occasionally used to validate numerical models without deeper integration, MESPAC positions satellite data as a key source to reconstruct historical conditions and fill space-time data gaps. This approach not only has the potential to provide essential long- term datasets but also shortens project timelines and improves informed decisions, unlocking the Mediter- ranean’s wind potential to accelerate a sustainable energy transition.