Articles | Volume 15, issue 18
https://doi.org/10.5194/amt-15-5323-2022
https://doi.org/10.5194/amt-15-5323-2022
Research article
 | 
20 Sep 2022
Research article |  | 20 Sep 2022

Quantification of motion-induced measurement error on floating lidar systems

Felix Kelberlau and Jakob Mann

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Cited articles

Bischoff, O., Schlipf, D., Würth, I., and Cheng, P. W.: Dynamic Motion Effects and Compensation Methods of a Floating Lidar Buoy, EERA DeepWind 2015 Deep Sea Offshore Wind Conference, Trondheim, Norway, 4–6 February 2015, https://doi.org/10.7567/JJAP.54.07JA03, 2015. a
Bischoff, O., Yu, W., Gottschall, J., and Cheng, P. W.: Validating a simulation environment for floating lidar systems, in: J. Phys.: Conference Series, 1037, 052036, https://doi.org/10.1088/1742-6596/1037/5/052036, 2018. a
Bischoff, O., Wolken-Möhlmann, G., and Cheng, P. W.: An approach and discussion of a simulation based measurement uncertainty estimation for a floating lidar system, J. Phys.: Conference Series, 2265, 022077, https://doi.org/10.1088/1742-6596/2265/2/022077, 2022. a
Carbon Trust: OWA roadmap for the commercial acceptance of floating LiDAR technology, Version 2.0, 2018. a, b, c
Désert, T., Knapp, G., and Aubrun, S.: Quantification and correction of wave-induced turbulence intensity bias for a floating lidar system, Remote Sens., 13, 2973, https://doi.org/10.3390/rs13152973, 2021. a, b
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Short summary
Floating lidar systems are used for measuring wind speeds offshore, and their motion influences the measurements. This study describes the motion-induced bias on mean wind speed estimates by simulating the lidar sampling pattern of a moving lidar. An analytic model is used to validate the simulations. The bias is low and depends on amplitude and frequency of motion as well as on wind shear. It has been estimated for the example of the Fugro SEAWATCH wind lidar buoy carrying a ZX 300M lidar.
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