Articles | Volume 9, issue 5
Atmos. Meas. Tech., 9, 1993–2013, 2016
https://doi.org/10.5194/amt-9-1993-2016
Atmos. Meas. Tech., 9, 1993–2013, 2016
https://doi.org/10.5194/amt-9-1993-2016
Research article
03 May 2016
Research article | 03 May 2016

Evaluation of three lidar scanning strategies for turbulence measurements

Jennifer F. Newman et al.

Related authors

An error reduction algorithm to improve lidar turbulence estimates for wind energy
Jennifer F. Newman and Andrew Clifton
Wind Energ. Sci., 2, 77–95, https://doi.org/10.5194/wes-2-77-2017,https://doi.org/10.5194/wes-2-77-2017, 2017
Short summary
Improvement of vertical velocity statistics measured by a Doppler lidar through comparison with sonic anemometer observations
Timothy A. Bonin, Jennifer F. Newman, Petra M. Klein, Phillip B. Chilson, and Sonia Wharton
Atmos. Meas. Tech., 9, 5833–5852, https://doi.org/10.5194/amt-9-5833-2016,https://doi.org/10.5194/amt-9-5833-2016, 2016
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Validation and Intercomparisons
An assessment of reprocessed GPS/MET observations spanning 1995–1997
Anthony J. Mannucci, Chi O. Ao, Byron A. Iijima, Thomas K. Meehan, Panagiotis Vergados, E. Robert Kursinski, and William S. Schreiner
Atmos. Meas. Tech., 15, 4971–4987, https://doi.org/10.5194/amt-15-4971-2022,https://doi.org/10.5194/amt-15-4971-2022, 2022
Short summary
Turbulence parameters measured by the Beijing mesosphere–stratosphere–troposphere radar in the troposphere and lower stratosphere with three models: comparison and analyses
Ze Chen, Yufang Tian, Yinan Wang, Yongheng Bi, Xue Wu, Juan Huo, Linjun Pan, Yong Wang, and Daren Lü
Atmos. Meas. Tech., 15, 4785–4800, https://doi.org/10.5194/amt-15-4785-2022,https://doi.org/10.5194/amt-15-4785-2022, 2022
Short summary
Comparison of planetary boundary layer height from ceilometer with ARM radiosonde data
Damao Zhang, Jennifer Comstock, and Victor Morris
Atmos. Meas. Tech., 15, 4735–4749, https://doi.org/10.5194/amt-15-4735-2022,https://doi.org/10.5194/amt-15-4735-2022, 2022
Short summary
Behavior and mechanisms of Doppler wind lidar error in varying stability regimes
Rachel Robey and Julie K. Lundquist
Atmos. Meas. Tech., 15, 4585–4622, https://doi.org/10.5194/amt-15-4585-2022,https://doi.org/10.5194/amt-15-4585-2022, 2022
Short summary
Inter-comparison of atmospheric boundary layer (ABL) height estimates from different profiling sensors and models in the framework of HyMeX-SOP1
Donato Summa, Fabio Madonna, Noemi Franco, Benedetto De Rosa, and Paolo Di Girolamo
Atmos. Meas. Tech., 15, 4153–4170, https://doi.org/10.5194/amt-15-4153-2022,https://doi.org/10.5194/amt-15-4153-2022, 2022
Short summary

Cited articles

Arya, S. P.: Introduction to Micrometeorology, vol. 79 of International Geophysics Series, 2nd edn., Academic Press, Cornwall, UK, 2001.
Bingöl, F., Mann, J., and Foussekis, D.: Conically scanning lidar error in complex terrain, Meteorol. Z., 18, 189–195, 2009.
Bodine, D., Klein, P. M., Arms, S. C., and Shapiro, A.: Variability of surface air temperature over gently sloped terrain, J. Appl. Meteorol. Clim., 48, 1117–1141, 2009.
Bright, D. R. and Mullen, S. L.: The sensitivity of the numerical simulation of the Southwest monsoon boundary layer to the choice of PBL turbulence parameterization in MM5, Weather Forecast., 17, 99–114, 2002.
Download
Short summary
Remote sensing devices known as lidars are often used to take measurements at potential wind farm sites. These instruments are however not optimized for measuring turbulence, small-scale changes in wind speed. In this manuscript, the impact of lidar configurations and atmospheric conditions on turbulence accuracy is explored. A new method was developed to correct lidar turbulence measurements and is described in detail such that other lidar users can apply it to their own instruments.