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L-TERRA (LIDAR Turbulence Error Reduction Algorithm)

National Renewable Energy Laboratory

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PDF Document PublicationPublished Application WO 2017-106323 (1,798 KB)

Technology Marketing Summary

Wind resource assessment and turbine power performance testing are typically conducted through the use of instruments on meteorological towers. Recently, LIDAR (light detection and ranging) instruments have started to replace the use of meteorological towers for these applications due to their flexibility and ability to take accurate wind speed measurements from higher heights above ground. While LIDAR instruments can measure mean wind speeds accurately under most conditions, they frequently measure turbulence intensity (TI) differently than anemometers due to various factors, such as instrument noise and volume averaging. These discrepancies in TI measurements alongside the absence of a currently accepted standard process for quantifying and reducing errors within LIDAR TI measurements demonstrate that improvements can be made to ensure that accurate and reliable TI measurements yield from LIDAR instruments.


Researchers at NREL have developed a novel error-reduction algorithm for LIDAR-measured turbulence. The algorithm combines a physics-based approach with machine learning techniques, where a model is trained using co-located LIDAR and meteorological tower data and where LIDAR-measured parameters, such as wind speed, shear, and TI, are utilized to accurately predict the difference between the LIDAR- and tower-measured TI. This system enables LIDAR users and manufacturers to correct LIDAR TI data in real time or in post-processing.

  • Accurate measurements of turbulence
  • Low cost alternative to using meteorological towers
  • Utilizes ease and functionality of LIDARs
Applications and Industries
  • Turbulence Intensity measurements
  • Wind resource assessment
  • Power performance testing 
More Information

Please read this published paper within Wind Energy Science: "An error reduction algorithm to improve LIDAR turbulence estimates for wind energy."

Technology Status
Technology IDDevelopment StageAvailabilityPublishedLast Updated
ROI 16-04 and SWR 15-34Proposed - This technology is in the Proposed/Prototype StageAvailable10/07/201610/07/2016

Contact NREL About This Technology

To: Erin Beaumont<>