Preprints
https://doi.org/10.5194/egusphere-2024-1548
https://doi.org/10.5194/egusphere-2024-1548
26 Sep 2024
 | 26 Sep 2024
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

SAMURAI-S: Sonic Anemometer on a MUlti-Rotor drone for Atmospheric turbulence Investigation in a Sling load configuration

Mauro Ghirardelli, Stephan T. Kral, Etienne Cheynet, and Joachim Reuder

Abstract. This study introduces the SAMURAI-S, a novel measurement system that incorporates a state-of-the-art sonic anemometer combined with a multi-rotor drone in a sling load configuration, designed to overcome the limitations of traditional mast-based observations in terms of spatial flexibility. This system enables the direct measurement of 3D wind vectors while hovering, providing a significant advantage in manoeuvrability and positional accuracy over fixed mast setups. The capabilities of the system are quantified through a series of 10 min to 28 min flights, conducting close comparisons of turbulence measurements at altitudes of 30 m and 60 m against data from a 60-meter tower equipped with research-grade sonic anemometers. The results demonstrate that SAMURAI-S matches the data quality of conventional setups for horizontal wind measurements while slightly overestimating vertical turbulence components. This overestimation increases as the wind speed increases.

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Mauro Ghirardelli, Stephan T. Kral, Etienne Cheynet, and Joachim Reuder

Status: open (until 31 Oct 2024)

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Mauro Ghirardelli, Stephan T. Kral, Etienne Cheynet, and Joachim Reuder
Mauro Ghirardelli, Stephan T. Kral, Etienne Cheynet, and Joachim Reuder

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Short summary
The SAMURAI-S system is an innovative measurement tool combining a high accuracy wind sensor with a multi-rotor drone to improve atmospheric turbulence observations. While traditional methods lack flexibility and accuracy in dynamic environments, SAMURAI-S provides high manoeuvrability and precise 3D wind measurements. The research demonstrated the system's ability to match the data quality of conventional methods, with a slight overestimation in vertical turbulence under higher wind conditions.