  The LiDAR Statistical Barnes Objective Analysis (LiSBOA), presented in
Letizia et al., is a procedure for the optimal design of LiDAR scans and
calculation over a Cartesian grid of the statistical moments of the velocity
field. The LiSBOA is applied to LiDAR data collected in the wake of wind
turbines to reconstruct mean and turbulence intensity of the wind velocity
field. The proposed procedure is firstly tested for a numerical dataset
obtained by means of the virtual LiDAR technique applied to the data obtained
from a large eddy simulation (LES). The optimal sampling parameters for a
scanning Doppler pulsed wind LiDAR are retrieved from the LiSBOA, then the
estimated statistics are calculated showing a maximum error of about 4% for
both the normalized mean velocity and the turbulence intensity. Subsequently,
LiDAR data collected during a field campaign conducted at a wind farm in
complex terrain are analyzed through the LiSBOA for two different
configurations. In the first case, the wake velocity fields of four
utility-scale turbines are reconstructed on a 3D grid, showing the capability
of the LiSBOA to capture complex flow features, such as high-speed jet around
the nacelle and the wake turbulent shear layers. For the second case, the
statistics of the wakes generated by four interacting turbines are calculated
over a 2D Cartesian grid and compared to the measurements provided by the
nacelle-mounted anemometers. Maximum discrepancies as low as 3% for the
normalized mean velocity and turbulence intensity endorse the application of
the LiSBOA for LiDAR-based wind resource assessment and diagnostic surveys for
wind farms.
