{"id":1217,"date":"2025-06-26T12:10:40","date_gmt":"2025-06-26T12:10:40","guid":{"rendered":"https:\/\/sites.rutgers.edu\/azizezzat\/?page_id=1217"},"modified":"2025-06-26T18:14:54","modified_gmt":"2025-06-26T18:14:54","slug":"airu-wrf-data-science-based-offshore-wind-forecasting-model-for-the-u-s-east-coast","status":"publish","type":"page","link":"https:\/\/sites.rutgers.edu\/azizezzat\/airu-wrf-data-science-based-offshore-wind-forecasting-model-for-the-u-s-east-coast\/","title":{"rendered":"AIRU-WRF: Data-Science-Based Offshore Wind Forecasting for the U.S. East Coast"},"content":{"rendered":"
Introduction and Motivation:<\/strong><\/h5>\n

Accurate short-term forecasts of wind conditions and power generation are critical for the cost-effective and reliable integration of offshore wind farms along the U.S. East Coast. These forecasts, spanning operational horizons from few minutes to several days ahead, are essential inputs to grid- and farm-level operational decision-making. Yet, long-term records of hub-height wind measurements in U.S. offshore regions are scarce, fragmented, or difficult to access. This lack of publicly available, high-quality data presents a significant barrier to the development, benchmarking, and deployment of advanced forecasting models\u2014unlike other regions with significant offshore wind potential (e.g., the North Sea), where well-curated datasets have fueled progress and accelerated the progress in data-driven forecasting.<\/p>\n

In response, and as part of a NOWRDC-supported project, Rutgers University developed one of the first data-driven offshore wind forecasting models specifically tailored to the U.S. East Coast, which is called the AI-Powered Rutgers University Weather Research & Forecasting (AIRU-WRF) model. Extensive evaluations suggest that AIRU-WRF significantly outperforms traditional WRF and standard machine learning baselines in wind speed and power forecasting, achieving significantly lower mean absolute error (MAE) across multiple forecasting horizons (10-min to 24-hour ahead) and geographic locations in the U.S. East Coast.<\/p>\n

 <\/p>\n

Project Information:\u00a0<\/strong><\/h5>\n

Project Title\/Number:<\/span> Project # 133-192900, “AIRU-WRF: AI-powered Physics-based Tool for OSW Forecasting and Grid Integration.”<\/p>\n

Duration:<\/span> 09\/2023 – 07\/2025.<\/p>\n

Funding Agency:<\/span> National Offshore Wind Research & Development Consortium<\/p>\n

Principal Investigators:\u00a0<\/span><\/p>\n