Wind LiDARs are based in the Doppler effect of backscattered laser light from aerosol and its most important limitation is that it only provides measurements of the wind speed component that is parallel to the laser beam (line of sight velocity or LoS) and not the transversal components. This limitation implies that for even the simplest measurements several assumptions need to be made in order to be able to calculate the desired variables (e.g. wind speed, direction, turbulence intensity, etc.). Best practices for wind LiDAR measurements take into account the limitations of these instruments and suggest ways of minimizing the error propagation in the measurements, but do not provide comprehensive uncertainty quantification for the different types of possible scans used.
A very efficient and useful approach to the problem of uncertainty quantification is the so-called virtual LiDAR, in which a high-resolution LES simulation of the atmospheric boundary layer is used as the base for the study. The LES simulation provides the three-component velocity vector at all points of the domain and at all times. An algorithm is then applied to the LES velocity field to extract a virtual LiDAR measurement; in other words: it extracts what the LiDAR would measure if that was the real wind field at one particular moment. Virtual LiDAR measurements can be used to calculate or reconstruct the variable of interest and the latter can be directly compared to the LES result . This allows for the quantification of the uncertainty induced in any of the variables by the assumptions mentioned above and excluding any other factors.
Two examples of the application of the virtual LiDAR approach for the evaluation of the uncertainty of LiDAR measurements are presented: (1) a standard profiler scan for the measurement of vertical profiles of the atmospheric boundary layer and (2) a horizontal scan of a wind turbine wake from a nacelle-mounted scanning LiDAR. The uncertainty is evaluated in terms of wind speed, wind direction and turbulence intensity.
 Lundquist et al. Quantifying error of lidar and sodar Doppler beam swinging measurements of wind turbine wakes using computational fluid dynamics, in Atmospheric Measurement Techniques, 8, 907-920, 2015.