Machine Learning for enhancing Wind Field Resolution in Complex Terrain

JW Wold, F Stadtmann, A Rasheed, M Tabib… - arXiv preprint arXiv …, 2023 - arxiv.org
Atmospheric flows are governed by a broad variety of spatio-temporal scales, thus making
real-time numerical modeling of such turbulent flows in complex terrain at high resolution
computationally intractable. In this study, we demonstrate a neural network approach
motivated by Enhanced Super-Resolution Generative Adversarial Networks to upscale low-
resolution wind fields to generate high-resolution wind fields in an actual wind farm in
Bessaker, Norway. The neural network-based model is shown to successfully reconstruct …

Machine Learning for enhancing Wind Field Resolution in Complex Terrain

J Wulff Wold, F Stadtmann, A Rasheed… - arXiv e …, 2023 - ui.adsabs.harvard.edu
Atmospheric flows are governed by a broad variety of spatio-temporal scales, thus making
real-time numerical modeling of such turbulent flows in complex terrain at high resolution
computationally intractable. In this study, we demonstrate a neural network approach
motivated by Enhanced Super-Resolution Generative Adversarial Networks to upscale low-
resolution wind fields to generate high-resolution wind fields in an actual wind farm in
Bessaker, Norway. The neural network-based model is shown to successfully reconstruct …
以上显示的是最相近的搜索结果。 查看全部搜索结果