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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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AMT | Articles | Volume 13, issue 8
Atmos. Meas. Tech., 13, 4141–4158, 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: CoMet: a mission to improve our understanding and to better...

Atmos. Meas. Tech., 13, 4141–4158, 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

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 et al.

Related authors

Estimating Upper Silesian coal mine methane emissions from airborne in situ observations and dispersion modeling
Julian Kostinek, Anke Roiger, Maximilian Eckl, Alina Fiehn, Andreas Luther, Norman Wildmann, Theresa Klausner, Andreas Fix, Christoph Knote, Andreas Stohl, and André Butz
Atmos. Chem. Phys. Discuss.,,, 2020
Preprint under review for ACP
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Estimating CH4, CO2 and CO emissions from coal mining and industrial activities in the Upper Silesian Coal Basin using an aircraft-based mass balance approach
Alina Fiehn, Julian Kostinek, Maximilian Eckl, Theresa Klausner, Michał Gałkowski, Jinxuan Chen, Christoph Gerbig, Thomas Röckmann, Hossein Maazallahi, Martina Schmidt, Piotr Korbeń, Jarosław Neçki, Pawel Jagoda, Norman Wildmann, Christian Mallaun, Rostyslav Bun, Anna-Leah Nickl, Patrick Jöckel, Andreas Fix, and Anke Roiger
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Analysis of flow in complex terrain using multi-Doppler lidar retrievals
Tyler M. Bell, Petra Klein, Norman Wildmann, and Robert Menke
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Improving boundary layer flow simulations over complex terrain by applying a forest parameterization in WRF
Johannes Wagner, Norman Wildmann, and Thomas Gerz
Wind Energ. Sci. Discuss.,,, 2019
Preprint retracted
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Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Filtering of pulsed lidar data using spatial information and a clustering algorithm
Leonardo Alcayaga
Atmos. Meas. Tech., 13, 6237–6254,,, 2020
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Variability of the Brunt–Väisälä frequency at the OH-airglow layer height at low and midlatitudes
Sabine Wüst, Michael Bittner, Jeng-Hwa Yee, Martin G. Mlynczak, and James M. Russell III
Atmos. Meas. Tech., 13, 6067–6093,,, 2020
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Removing spurious inertial instability signals from gravity wave temperature perturbations using spectral filtering methods
Cornelia Strube, Manfred Ern, Peter Preusse, and Martin Riese
Atmos. Meas. Tech., 13, 4927–4945,,, 2020
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Erik van Schaik, Maurits L. Kooreman, Piet Stammes, L. Gijsbert Tilstra, Olaf N. E. Tuinder, Abram F. J. Sanders, Willem W. Verstraeten, Rüdiger Lang, Alessandra Cacciari, Joanna Joiner, Wouter Peters, and K. Folkert Boersma
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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,, 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,<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,, 2006. a
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