Articles | Volume 13, issue 8
https://doi.org/10.5194/amt-13-4141-2020
https://doi.org/10.5194/amt-13-4141-2020
Research article
 | 
04 Aug 2020
Research article |  | 04 Aug 2020

Towards improved turbulence estimation with Doppler wind lidar velocity-azimuth display (VAD) scans

Norman Wildmann, Eileen Päschke, Anke Roiger, and Christian Mallaun

Related authors

High-resolution wind speed measurements with quadcopter uncrewed aerial systems: calibration and verification in a wind tunnel with an active grid
Johannes Kistner, Lars Neuhaus, and Norman Wildmann
Atmos. Meas. Tech., 17, 4941–4955, https://doi.org/10.5194/amt-17-4941-2024,https://doi.org/10.5194/amt-17-4941-2024, 2024
Short summary
Data assimilation of realistic boundary-layer flows for wind-turbine applications – An LES study
Linus Wrba, Antonia Englberger, Andreas Dörnbrack, Gerard Kilroy, and Norman Wildmann
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-12,https://doi.org/10.5194/wes-2024-12, 2024
Revised manuscript under review for WES
Short summary
Quantification of methane emissions in Hamburg using a network of FTIR spectrometers and an inverse modeling approach
Andreas Forstmaier, Jia Chen, Florian Dietrich, Juan Bettinelli, Hossein Maazallahi, Carsten Schneider, Dominik Winkler, Xinxu Zhao, Taylor Jones, Carina van der Veen, Norman Wildmann, Moritz Makowski, Aydin Uzun, Friedrich Klappenbach, Hugo Denier van der Gon, Stefan Schwietzke, and Thomas Röckmann
Atmos. Chem. Phys., 23, 6897–6922, https://doi.org/10.5194/acp-23-6897-2023,https://doi.org/10.5194/acp-23-6897-2023, 2023
Short summary
Multi-point in situ measurements of turbulent flow in a wind turbine wake and inflow with a fleet of uncrewed aerial systems
Tamino Wetz and Norman Wildmann
Wind Energ. Sci., 8, 515–534, https://doi.org/10.5194/wes-8-515-2023,https://doi.org/10.5194/wes-8-515-2023, 2023
Short summary
Towards vertical wind and turbulent flux estimation with multicopter uncrewed aircraft systems
Norman Wildmann and Tamino Wetz
Atmos. Meas. Tech., 15, 5465–5477, https://doi.org/10.5194/amt-15-5465-2022,https://doi.org/10.5194/amt-15-5465-2022, 2022
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Sampling the diurnal and annual cycles of the Earth's energy imbalance with constellations of satellite-borne radiometers
Thomas Hocking, Thorsten Mauritsen, and Linda Megner
Atmos. Meas. Tech., 17, 7077–7095, https://doi.org/10.5194/amt-17-7077-2024,https://doi.org/10.5194/amt-17-7077-2024, 2024
Short summary
Retrieval of top-of-atmosphere fluxes from combined EarthCARE lidar, imager, and broadband radiometer observations: the BMA-FLX product
Almudena Velázquez Blázquez, Carlos Domenech, Edward Baudrez, Nicolas Clerbaux, Carla Salas Molar, and Nils Madenach
Atmos. Meas. Tech., 17, 7007–7026, https://doi.org/10.5194/amt-17-7007-2024,https://doi.org/10.5194/amt-17-7007-2024, 2024
Short summary
Analysis of the measurement uncertainty for a 3D wind lidar
Wolf Knöller, Gholamhossein Bagheri, Philipp von Olshausen, and Michael Wilczek
Atmos. Meas. Tech., 17, 6913–6931, https://doi.org/10.5194/amt-17-6913-2024,https://doi.org/10.5194/amt-17-6913-2024, 2024
Short summary
Improving solution availability and temporal consistency of an optimal-estimation physical retrieval for ground-based thermodynamic boundary layer profiling
Bianca Adler, David D. Turner, Laura Bianco, Irina V. Djalalova, Timothy Myers, and James M. Wilczak
Atmos. Meas. Tech., 17, 6603–6624, https://doi.org/10.5194/amt-17-6603-2024,https://doi.org/10.5194/amt-17-6603-2024, 2024
Short summary
An improved geolocation methodology for spaceborne radar and lidar systems
Bernat Puigdomènech Treserras and Pavlos Kollias
Atmos. Meas. Tech., 17, 6301–6314, https://doi.org/10.5194/amt-17-6301-2024,https://doi.org/10.5194/amt-17-6301-2024, 2024
Short summary

Cited articles

Banakh, V. and Smalikho, I.: Coherent Doppler Wind Lidars in a Turbulent Atmosphere, Radar, Artech House, Boston, MA, USA, 2013. a, b
Banakh, V. A. and Smalikho, I. N.: Lidar Estimates of the Anisotropy of Wind Turbulence in a Stable Atmospheric Boundary Layer, Remote Sens.-Basel, 11, 2115, https://doi.org/10.3390/rs11182115, 2019. a
Banakh, V. A., Smalikho, I. N., Köpp, F., and Werner, C.: Measurements of Turbulent Energy Dissipation Rate with a CW Doppler Lidar in the Atmospheric Boundary Layer, J. Atmos. Ocean Tech., 16, 1044–1061, https://doi.org/10.1175/1520-0426(1999)016<1044:MOTEDR>2.0.CO;2, 1999. a
Bange, J., Beyrich, F., and Engelbart, D. A. M.: Airborne Measurements of Turbulent Fluxes during LITFASS-98: A Case Study about Method and Significance, Theor. Appl. Climatol., 73, 35–51, 2002. a
Beyrich, F., Leps, J.-P., Mauder, M., Bange, J., Foken, T., Huneke, S., Lohse, H., Lüdi, A., Meijninger, W., Mironov, D., Weisensee, U., and Zittel, P.: Area-Averaged Surface Fluxes Over the Litfass Region Based on Eddy-Covariance Measurements, Bound.-Lay. Meteorol., 121, 33–65, https://doi.org/10.1007/s10546-006-9052-x, 2006. a