Preprints
https://doi.org/10.5194/wes-2025-221
https://doi.org/10.5194/wes-2025-221
18 Nov 2025
 | 18 Nov 2025
Status: this preprint is currently under review for the journal WES.

Generating high fidelity wind fields from the wind speed correlation tensor

Matteo Faccioni, Daniel Kiehn, and Patrick Vrancken

Abstract. In this publication a new method to generate stochastic representations of homogeneous and isotropic wind fields is presented. In contrast to the typically employed algorithm, the new approach is based on the wind speed correlation tensor. This allows simulating a homogeneous and isotropic turbulent wind field with very high accuracy. In this publication, a deviation of the obtained dataset's structure function from the theoretical one of at least one order of magnitude lower than the commonly used method is achieved. Furthermore, a compensation method to decrease this error even further is proposed. Moreover, being a generic method, it can be used to simulate other Gaussian phenomena (e.g., temperature or index of refraction fluctuations) on various spatial domains and grid shapes.

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Matteo Faccioni, Daniel Kiehn, and Patrick Vrancken

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Matteo Faccioni, Daniel Kiehn, and Patrick Vrancken
Matteo Faccioni, Daniel Kiehn, and Patrick Vrancken

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Short summary
A new method to synthesize a wind field with very low error with respect to the theoretical, expected statistics is presented. The presented method has been developed with the aim of validating the effectiveness of a wind reconstruction algorithm, in the context of a gust load alleviation project. Finally, the proposed method allows to synthesize Gaussian and stationary phenomena with high accuracy for various spatial domains and grid shapes.
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