# An Inter-Comparison Study of Multi- and DBS Lidar Measurements in Complex Terrain
## 4 Conclusions
An alternative is to develop correction methods for the variance which is lost due to the line averaging. First-order corrections could be based on model spectra as often done for eddy-covariance measurements (e.g., [42]). The spectral transfer function, however, needs further attention. Alternatively, the correction could be based on an extrapolation of the spectra in the inertial sub-range [43; 44]. This, however, requires that a part of the inertial sub-range is not affected by line averaging. More sophisticated approaches could exploit e.g., the spectral broadening of the received backscatter [25; 45; 46]. The results for the variance measurements of the DBS lidar clearly illustrate the errors introduced by cross-contamination in this technique and reiterate the unreliability of turbulence measurements from profiling lidars. From a practical perspective, it is interesting that the good results of the ML method could also be maintained if only two lidars were used. This reduces the additional costs, which are one of the disadvantages of the ML method, when compared to the DBS lidar (or other profiling lidar). Differences between the different dual-lidar ML systems are likely to be mainly caused by the setup or, more precisely, the different angles between the WindScanners. While the mean wind speed is only slightly affected, the variances of the horizontal wind-speed components seem to be more sensitive to an unfavourable setup of the WindScanners. A detailed analysis of the effect of the setup on the accuracy of ML measurements is part of ongoing investigations. The authors would like to acknowledge four anonymous referees for their valuable reviews. We would also like to thank [PERSON] and [PERSON] for the support during the field work. The authors are grateful to [PERSON] for fruitful discussions and valuable comments on the manuscript. The authors would like to thank [PERSON] who helped with editing the final figures. The work of this article was funded by the following projects: WindScanner.eu, Windenergie im Binnenland II (Forderkennzeichen 0325171A), and neweuropeanwindatlas.eu. [PERSON] and [PERSON] first initiated the experiment; [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] planned and designed the measurement campaign; [PERSON], [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] performed the experiments; [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] performed the quality control of the measurements/data; [PERSON], [PERSON] and [PERSON] carried out the data analysis; [PERSON] and M.C. were responsible for the provision of the WindScanners; [PERSON] and [PERSON] were responsible for the provision of the DBS lidars; [PERSON] wrote the manuscript; all authors read, reviewed and approved the final manuscript and provided valuable editorial and critical input and feedback for the final document. The authors declare no conflict of interest. The following abbreviations are used in this manuscript: \begin{tabular}{l l} CNR & Carrier-to-noise ratio \\ DBS & Doppler beam swinging \\ lidar & Light detection and ranging \\ ML & Multi-lidar \\ FWHM & Full width at half maximum \\ RMSD & Root-mean-square deviation \\ VAD & Velocity azimuth display \\ \end{tabular}