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Offshore wind power plants have become an important element of the European electrical grid. Studies of metocean site conditions (wind, sea state, currents, water levels) form a key input to the design of these large infrastructure projects. Such studies rely heavily on reanalysis datasets which provide decades-long model time series over large areas. In turn, these time series are used for assessing wind, water levels and wave conditions and are thereby key inputs to design activities such as calculations of fatigue loads and extreme loads and platform elevations. In this article, we address a known deficiency of one these reanalysis datasets, ERA5, namely that it underestimates strong wind speeds offshore. If left uncorrected, this poses a design risk (high and extreme wind, waves and water level conditions are underestimated). Firstly, comparisons are made against CFSR/CFSv2 reanalyses as well as high-quality wind-energy-specific in situ measurements from floating lidar systems. Then, the ERA5 surface drag formulation and its sea state dependency are analysed in detail, the conditions of the bias identified, and a correction method is suggested. The article concludes with proposing practical and simple ways to incorporate publicly available, high-quality wind energy measurement datasets in air–sea interaction studies alongside legacy measurements such as met buoys. [ABSTRACT FROM AUTHOR]

Confinement is a very common phenomenon in chemistry, for example, when molecules are located inside cavities. In these conditions, the electronic structure of atoms and molecules is modified. These changes could be mapped through the interaction with other molecules since non-covalent interactions between molecules are also influenced by confinement. In this work we address both topics, non-covalent interactions, and confined systems, using quantum chemistry tools with new software, emphasizing the importance of analyzing both fields simultaneously. [ABSTRACT FROM AUTHOR]

Within STEM (Science, Technology, Engineering, and Mathematics) education, integrating real-world problem scenarios is paramount. Within interdisciplinary education, modeling is an approach to fostering student learning and skill development in a student-centered learning environment. This study focuses on an integrated physics and mathematics course in STEM education based on modeling for first-year engineering students. The main objectives of this study are to analyze students' models, assess the effectiveness of the pedagogical approach, and evaluate the benefits of integrative education. This study uses a Model-Application Activity as a closure for the quadratic model and extends the models built to a two-dimensional motion situation. The core activity involves a real-world experiment where students attempt to roll a ball down a ramp into a cup. While most groups successfully constructed theoretical models, only a few hit the target, highlighting the complexities of applying theoretical knowledge to real-world scenarios. The study also emphasizes the seamless integration of physics and mathematics, enriching the learning experience and making the models more robust and versatile. Despite the promising results, the study identifies a gap between theoretical understanding and practical application, suggesting the need for more hands-on activities in the curriculum. In conclusion, this study underlines the value of integrating physics and mathematics through modeling and a student-centered approach, setting the stage for future research to enhance the effectiveness of STEM education. [ABSTRACT FROM AUTHOR]