Articles | Volume 7, issue 1
Wind Energ. Sci., 7, 413–431, 2022
https://doi.org/10.5194/wes-7-413-2022
Wind Energ. Sci., 7, 413–431, 2022
https://doi.org/10.5194/wes-7-413-2022
Research article
01 Mar 2022
Research article | 01 Mar 2022

The five main influencing factors for lidar errors in complex terrain

Tobias Klaas-Witt and Stefan Emeis

Related authors

An analytical solution for wind deficit decay behind a wind energy converter using momentum conservation validated by UAS data
Moritz Mauz, Bram van Kesteren, Andreas Platis, Stefan Emeis, and Jens Bange
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2021-21,https://doi.org/10.5194/wes-2021-21, 2021
Preprint withdrawn
Short summary
An analytical solution for wind deficit decay behind a wind energy converter using momentum flux conservation validated by UAS data
Moritz Mauz, Bram van Kesteren, Andreas Platis, Stefan Emeis, and Jens Bange
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2020-92,https://doi.org/10.5194/wes-2020-92, 2020
Revised manuscript not accepted
Short summary
In situ airborne measurements of atmospheric and sea surface parameters related to offshore wind parks in the German Bight
Astrid Lampert, Konrad Bärfuss, Andreas Platis, Simon Siedersleben, Bughsin Djath, Beatriz Cañadillas, Robert Hunger, Rudolf Hankers, Mark Bitter, Thomas Feuerle, Helmut Schulz, Thomas Rausch, Maik Angermann, Alexander Schwithal, Jens Bange, Johannes Schulz-Stellenfleth, Thomas Neumann, and Stefan Emeis
Earth Syst. Sci. Data, 12, 935–946, https://doi.org/10.5194/essd-12-935-2020,https://doi.org/10.5194/essd-12-935-2020, 2020
Short summary
Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1)
Simon K. Siedersleben, Andreas Platis, Julie K. Lundquist, Bughsin Djath, Astrid Lampert, Konrad Bärfuss, Beatriz Cañadillas, Johannes Schulz-Stellenfleth, Jens Bange, Tom Neumann, and Stefan Emeis
Geosci. Model Dev., 13, 249–268, https://doi.org/10.5194/gmd-13-249-2020,https://doi.org/10.5194/gmd-13-249-2020, 2020
Short summary
Simultaneous multicopter-based air sampling and sensing of meteorological variables
Caroline Brosy, Karina Krampf, Matthias Zeeman, Benjamin Wolf, Wolfgang Junkermann, Klaus Schäfer, Stefan Emeis, and Harald Kunstmann
Atmos. Meas. Tech., 10, 2773–2784, https://doi.org/10.5194/amt-10-2773-2017,https://doi.org/10.5194/amt-10-2773-2017, 2017
Short summary

Related subject area

Wind and turbulence
Evaluation of obstacle modelling approaches for resource assessment and small wind turbine siting: case study in the northern Netherlands
Caleb Phillips, Lindsay M. Sheridan, Patrick Conry, Dimitrios K. Fytanidis, Dmitry Duplyakin, Sagi Zisman, Nicolas Duboc, Matt Nelson, Rao Kotamarthi, Rod Linn, Marc Broersma, Timo Spijkerboer, and Heidi Tinnesand
Wind Energ. Sci., 7, 1153–1169, https://doi.org/10.5194/wes-7-1153-2022,https://doi.org/10.5194/wes-7-1153-2022, 2022
Short summary
Comparing and validating intra-farm and farm-to-farm wakes across different mesoscale and high-resolution wake models
Jana Fischereit, Kurt Schaldemose Hansen, Xiaoli Guo Larsén, Maarten Paul van der Laan, Pierre-Elouan Réthoré, and Juan Pablo Murcia Leon
Wind Energ. Sci., 7, 1069–1091, https://doi.org/10.5194/wes-7-1069-2022,https://doi.org/10.5194/wes-7-1069-2022, 2022
Short summary
Large-eddy simulation of airborne wind energy farms
Thomas Haas, Jochem De Schutter, Moritz Diehl, and Johan Meyers
Wind Energ. Sci., 7, 1093–1135, https://doi.org/10.5194/wes-7-1093-2022,https://doi.org/10.5194/wes-7-1093-2022, 2022
Short summary
Investigation into boundary layer transition using wall-resolved large-eddy simulations and modeled inflow turbulence
Brandon Arthur Lobo, Alois Peter Schaffarczyk, and Michael Breuer
Wind Energ. Sci., 7, 967–990, https://doi.org/10.5194/wes-7-967-2022,https://doi.org/10.5194/wes-7-967-2022, 2022
Short summary
Evaluation of the global-blockage effect on power performance through simulations and measurements
Alessandro Sebastiani, Alfredo Peña, Niels Troldborg, and Alexander Meyer Forsting
Wind Energ. Sci., 7, 875–886, https://doi.org/10.5194/wes-7-875-2022,https://doi.org/10.5194/wes-7-875-2022, 2022
Short summary

Cited articles

Antoniou, I., Courtney, M. S., Jørgensen, H. E., Mikkelsen, T., Hunerbein, S. V., Bradley, S., Piper, B., Harris, M., Marti, I., Aristu, M., Foussekis, D., and Nielsen, M. P.: Remote sensing the wind using Lidars and Sodars, EWEA – European Wind Energy Association, Brussels, https://orbit.dtu.dk/en/publications/remote-sensing-the-wind-using-lidars-and-sodars (last access: 22 February 2022), 2007. 
Ayotte, K. W.: Computational modeling for wind energy assessment, J. Wind Eng. Indust. Aerodynam., 96, 1571–1590, https://doi.org/10.1016/j.jweia.2008.02.002, 2008. 
Behrens, P., O'Sullivan, J., Archer, R., and Bradley, S.: Underestimation of Monostatic Sodar Measurements in Complex Terrain, Bound.-Lay. Meteorol., 143, 97–106, https://doi.org/10.1007/s10546-011-9665-6, 2012. 
Belcher, S. E., Finnigan, J. J., and Harman, I. N.: Flow through forest canopies in complex terrain, Ecol. Appl., 1436–1453, 2008. 
Belcher, S. E., Harman, I. N., and Finnigan, J. J.: The Wind in the Willows: Flow in Forest Canopies in Complex Terrain, Annu. Rev. Fluid Mech., 479–504, 2012. 
Download
Short summary
Light detection and ranging (lidar) has become a valuable technology to assess the wind resource at hub height of modern wind turbines. However, because of their measurement principle, common lidars suffer from errors at orographically complex, i.e. hilly or mountainous, sites. This study analyses the impact of the five main influencing factors in a non-dimensional, model-based parameter study.