In interpreting Fig. 6, the following should be noted. First, the good agreement between the sonic anemometer and lidars in the low-frequency spectrum shows that large turbulent eddies are captured by the lidars well up to an energetic large-eddy frequency cut off (); a plot of versus shows that most of the along-beam component energy ( along the ARL lidar beam, along the UU lidar beam) is contained below the frequency of the “energy containing” eddies () which is defined as the frequency corresponding to the maximum of the plot. Taking the typical mean velocity as (see Fig. 5), for this time series and using Taylor’s hypothesis, this translates into a relationship between the wave number () and frequency of or an eddy size of , which is a reasonable value based on previous observations.39 Second, note that the sampling Nyquist frequency (, defined as half the sampling frequency) for the UU lidar is 0.125 Hz and for the ARL lidar is 0.5 Hz, and frequencies higher than are to be discarded for the lidar results. Third, the lidar radial velocity is spatially averaged by a weighting function which has a peak value at the center of a range gate; this spatial average is equivalent to spatial filtering with a filter function and the resulting radial velocity has fewer fluctuations than exhibited by the sonic anemometer. The spatial resolution of the lidar (range-gate size) imposes a restriction on the size of eddies that can be resolved. For UU, this is , and hence above the frequency of , which is slightly greater than its sampling Nyquist frequency. For the ARL lidar, the wave number becomes and . The limiting factor for the ARL lidar is its spatial resolution rather than the sampling frequency for this relatively low wind speed of . We expect the classical Kolmogorov spectra [ slope, i.e., slope for ] is applicable for sonic anemometer data, but the slope is slightly steeper for Doppler lidar data, reflecting the spectral attenuation due to the spatial average of the range gate (Fig. 6). A rough estimation can be made of the amount of energy that is becoming “opaque” because of the low resolution of the lidar. Integrating the spectrum up to , we find that TKE is underestimated in lidar measurements by about 7% for the ARL lidar, and 11% for the UU lidar compared with the sonic anemometer. Analogously, the work of Kit et al.40 showed that about 10% of the energy is unaccounted for due to the relatively low resolution of sonic anemometers compared to hot-film probes.