Articles | Volume 8, issue 2
https://doi.org/10.5194/amt-8-907-2015
https://doi.org/10.5194/amt-8-907-2015
Research article
 | 
23 Feb 2015
Research article |  | 23 Feb 2015

Quantifying error of lidar and sodar Doppler beam swinging measurements of wind turbine wakes using computational fluid dynamics

J. K. Lundquist, M. J. Churchfield, S. Lee, and A. Clifton

Related authors

Offshore wind farms modify low-level jets
Daphne Quint, Julie K. Lundquist, and David Rosencrans
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-48,https://doi.org/10.5194/wes-2024-48, 2024
Preprint under review for WES
Short summary
Meteorological Impacts of Offshore Wind Turbines as Simulated in the Weather Research and Forecasting Model
Daphne Quint, Julie K. Lundquist, Nicola Bodini, and David Rosencrans
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-53,https://doi.org/10.5194/wes-2024-53, 2024
Revised manuscript under review for WES
Short summary
The 2023 National Offshore Wind data set (NOW-23)
Nicola Bodini, Mike Optis, Stephanie Redfern, David Rosencrans, Alex Rybchuk, Julie K. Lundquist, Vincent Pronk, Simon Castagneri, Avi Purkayastha, Caroline Draxl, Raghavendra Krishnamurthy, Ethan Young, Billy Roberts, Evan Rosenlieb, and Walter Musial
Earth Syst. Sci. Data, 16, 1965–2006, https://doi.org/10.5194/essd-16-1965-2024,https://doi.org/10.5194/essd-16-1965-2024, 2024
Short summary
Seasonal variability of wake impacts on US mid-Atlantic offshore wind plant power production
David Rosencrans, Julie K. Lundquist, Mike Optis, Alex Rybchuk, Nicola Bodini, and Michael Rossol
Wind Energ. Sci., 9, 555–583, https://doi.org/10.5194/wes-9-555-2024,https://doi.org/10.5194/wes-9-555-2024, 2024
Short summary
The Effects of Wind Farm Wakes on Freezing Sea Spray in the Mid-Atlantic Offshore Wind Energy Areas
David Rosencrans, Julie K. Lundquist, Mike Optis, and Nicola Bodini
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-2,https://doi.org/10.5194/wes-2024-2, 2024
Revised manuscript under review for WES
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Atmospheric motion vector (AMV) error characterization and bias correction by leveraging independent lidar data: a simulation using an observing system simulation experiment (OSSE) and optical flow AMVs
Hai Nguyen, Derek Posselt, Igor Yanovsky, Longtao Wu, and Svetla Hristova-Veleva
Atmos. Meas. Tech., 17, 3103–3119, https://doi.org/10.5194/amt-17-3103-2024,https://doi.org/10.5194/amt-17-3103-2024, 2024
Short summary
Rotary-wing drone-induced flow – comparison of simulations with lidar measurements
Liqin Jin, Mauro Ghirardelli, Jakob Mann, Mikael Sjöholm, Stephan Thomas Kral, and Joachim Reuder
Atmos. Meas. Tech., 17, 2721–2737, https://doi.org/10.5194/amt-17-2721-2024,https://doi.org/10.5194/amt-17-2721-2024, 2024
Short summary
Application of Doppler sodar in short-term forecasting of PM10 concentration in the air in Krakow (Poland)
Ewa Agnieszka Krajny, Leszek Ośródka, and Marek Jan Wojtylak
Atmos. Meas. Tech., 17, 2451–2464, https://doi.org/10.5194/amt-17-2451-2024,https://doi.org/10.5194/amt-17-2451-2024, 2024
Short summary
Radiative closure tests of collocated hyperspectral microwave and infrared radiometers
Lei Liu, Natalia Bliankinshtein, Yi Huang, John R. Gyakum, Philip M. Gabriel, Shiqi Xu, and Mengistu Wolde
Atmos. Meas. Tech., 17, 2219–2233, https://doi.org/10.5194/amt-17-2219-2024,https://doi.org/10.5194/amt-17-2219-2024, 2024
Short summary
Effects of clouds and aerosols on downwelling surface solar irradiance nowcasting and short-term forecasting
Kyriakoula Papachristopoulou, Ilias Fountoulakis, Alkiviadis F. Bais, Basil E. Psiloglou, Nikolaos Papadimitriou, Ioannis-Panagiotis Raptis, Andreas Kazantzidis, Charalampos Kontoes, Maria Hatzaki, and Stelios Kazadzis
Atmos. Meas. Tech., 17, 1851–1877, https://doi.org/10.5194/amt-17-1851-2024,https://doi.org/10.5194/amt-17-1851-2024, 2024
Short summary

Cited articles

Aitken, M. L., Rhodes, M. E., and Lundquist, J. K.: Performance of a wind-profiling lidar in the region of wind turbine rotor disks, J. Atmos. Ocean. Tech., 29, 347–355, 2012.
Aitken, M. L., Banta, R. M., Pichugina, Y. L., and Lundquist, J. K.: Quantifying wind turbine wake characteristics from scanning remote sensor data, J. Atmos. Ocean. Tech., 31, 765–787, https://doi.org/10.1175/JTECH-D-13-00104.1, 2014a.
Aitken, M. L., Kosovic, B., Mirocha, J., and Lundquist, J. K.: Large-eddy simulation of wind turbine wake dynamics in the stable boundary layer using the Weather Research and Forecasting Model, J. Renew. Sustain. Ener., 6, 033137, https://doi.org/10.1063/1.4885111, 2014b.
Banakh, V. A. and Smalikho, I. N.: Estimation of turbulent energy dissipation rate from data of pulse Doppler lidar, Atmos. Oceanic Opt., 10, 957–965, 1997.
Barthelmie, R. J., Folkerts, L., Ormel, F. T., Sanderhoff, P., Eecen, P. J., Stobbe, O., and Nielsen, N. M.: Offshore wind turbine wakes measured by sodar, J. Atmos. Ocean. Tech., 20, 466–477, https://doi.org/10.1175/1520-0426(2003)20<466:OWTWMB>2.0.CO;2, 2003.
Download
Short summary
Wind-profiling lidars are now regularly used in boundary-layer meteorology and in applications like wind energy, but their use often relies on assuming homogeneity in the wind. Using numerical simulations of stable flow past a wind turbine, we quantify the error expected because of the inhomogeneity of the flow. Large errors (30%) in winds are found near the wind turbine, but by three rotor diameters downwind, errors in the horizontal components have decreased to 15% of the inflow.