# Measurement and Prediction of Wind Fields at an Offshore Site by Scanning Doppler LiDAR and WRF
## 4 Conclusions  
The current work evaluated the performance of scanning Doppler LiDAR for wind resource measurement and analysis for wind energy applications. The measurement results were also compared with WRF simulations and wake models.  
Firstly, 10-min-averaged wind speeds measured by scanning LiDAR in DBS mode were validated against the measurements of an existing V1 LiDAR. It was observed that the quality of measurements degraded when the minimum threshold value of the CNR was increased. As a result, the agreement between the scanning LiDAR and the V1 LiDAR measurements was better when the availability of the scanning LiDAR was higher. However, even with a lower availability of 20% (30 data per 10 min), fairly good 10-min-averaged wind speed data could be produced. Vertical wind profiles were measured in DBS-mode and then investigated for wind blowing from the land and that from the sea. It was found that the wind speed was higher when the wind was blowing from the sea than when it was blowing from the land. The simulated wind profiles by WRF showed a similar tendency to the LiDAR measurements, but they overestimated the measurements at higher altitudes when the wind was blowing from the land.  
A method for the reconstruction of wind speeds from conical and slice scans (also known as PPI and RHI) was proposed in this study. The method assumes the wind direction at every point in a scan to be the same as that measured by another wind vane. The proposed velocity retrieval method with RHI and wind directions obtained from the wind vane mounted on the meteorological tower was then used to investigate the effect of coastal terrain on the ABL by measuring the flow field between the LiDAR and the coastline. The coastal terrain was responsible for the development of an IBL resulting in strong shear in the region close to the coast. It was also found that this IBL persisted for approximately 2000 m offshore.  
Finally, the flow field around the wind turbine was measured using multiple PPI scans together with wind directions obtained from the wind vane mounted on the meteorological tower and processed to characterize the wind turbine wake. A velocity deficit in the wind turbine wake was clearly visible along with a dual peak in the near-wake region in the flow field visualization. Horizontal profiles of velocity deficit in the wake of the wind turbine showed common characteristics observed in earlier numerical and experimental studies. The LiDAR measurement was also used to validate the wake models. Two of the Gaussian wake models showed better agreement with the measurements than the models with top-hat velocity distribution.  
Conceptualization, J.P.G., A.Y. and T.I.; methodology, J.P.G., A.Y. and T.I.; data curation, A.Y. and T.I.; investigation, J.P.G. and T.I.; formal analysis: J.P.G.; writing--original draft, J.P.G.; writing--review and editing, A.Y. and T.I.; supervision, T.I.; project administration, T.I.; funding acquisition, T.I. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the New Energy and Industrial Technology Department Organization (NEDO), Japan.  
Authors acknowledge the support of New Energy and Industrial Technology Development Organization (NEDO), Japan. Authors also thank [PERSON] from Tokyo Electric Power Company for his assistance during measurement campaigns.  
The authors declare no conflict of interest.