# Measurement and Prediction of Wind Fields at an Offshore Site by Scanning Doppler LiDAR and WRF
## 3 Results and Discussion
### Validation of Velocity Vector Retrieved from PPI and RHI Scan Data  
This section presents validation of the two approaches -proposed in Section 2.2--for retrieving velocity vector from LOS velocity fields obtained in the PPI and RHI scans. The first approach, which requires wind direction information (cf. Equations (4) and (5)), is validated against measurements from the anemometer mounted on the nacelle of the neighboring wind turbine (see Figure 1). A PPI scan is employed to collect scanning LiDAR measurements, as shown in Figure 12. The LiDAR beam is swept at \(\varnothing=13.2^{\circ}\) and for an azimuth angle range of 40\({}^{\circ}\), such that the beam passes through the nacelle anemometer, and the wind turbine is in the middle of the azimuth range. In order to obviate the effect of the turbine wake on the nacelle measurement, the comparison was made when the turbine was stopped.  
Figure 11: **(a,b)** Comparison of hourly averaged profiles of horizontal velocity which are further averaged over the period of one-month (for May 2016). Horizontal dashed lines indicate the hub height level, and the dark profiles indicate the percentage error in the WRF profiles compared to the LiDAR measurement.  
Figure 12: Schematic of the LiDAR beam targeting the nacelle-mounted anemometer. The scan is performed in the plan-position indicator (PPI) mode for validating the proposed velocity retrieval approach.  
Since the nacelle anemometer-measured wind speed is influenced by the rotor or the shape of the nacelle, the measurement of the nacelle anemometer is first compared against the wind speed measured by cup anemometers installed at a height of 80 m on the meteorological tower. The comparison showed that on average, the wind speed measured by the nacelle anemometer is 5.7% higher than that obtained from the meteorological tower measurement [19]. Therefore, the measurement of the nacelle anemometer is corrected using the velocity ratio 1.057.  
Figure 13 shows a comparison of 10-min-averaged wind speeds retrieved from the scanning LiDAR measurement against the measurements of the nacelle-mounted anemometer. The time series and scatter plots show a good agreement between the two measurements with \(R^{2}=0.979\), \(\text{RMSE}=0.562\), and slope being 0.976.  
Figures 14 and 15 show comparisons of the wind speed and wind direction obtained by scanning Doppler LiDAR (retrieved using the VAD technique) against the wind speed and wind direction measured by the met mast tower. The comparison height is 90 m. Both the time series and scatter plot show a good agreement between the two measurements. The coefficient of determination is \(R^{2}=0.99\) for both wind speed and wind direction, and the RMSE of wind speed is 0.31 m/s, whereas that of wind direction is 5.6\({}^{\circ}\). However, it should be mentioned that the complete conical scan required by this approach can significantly reduce the data sample. Furthermore, due to uncertainty in the LiDAR measurement, it may be necessary to perform multiple scans for the same elevation angle in order to obtain accurate wind directions. This makes the approach less attractive for constructing the velocity field. The current study employs the former approach validated in this section for velocity field reconstruction.  
Figure 14: Comparison of the time series of wind speed (**a**) and wind direction (**b**) of scanning Doppler LiDAR (retrieved using velocity azimuth display (VAD)) and met mast tower at 90 m height (on 6 September 2016).  
Figure 13: Validation of the scanning LiDAR-measured mean wind speeds against those obtained from the nacelle-mounted anemometer (**a**). Measurement data (**b**) collected from 25 October 2016 22:00 to 26 October 2016 8:00.