# Quantification and Correction of Wave-Induced Turbulence Intensity Bias for a Floating LIDAR System
## 3 Method
### Experimental Campaign  
The correction developed for FLS turbulence intensity estimate is evaluated on experimental data from a floating WindCube v2(r). The FLS measurements are compared with data measured by an anemometer and an additional WindCube v2(r) located on a fixed platform. The experimental campaign took place off the shores of Fecamp (Normandie, France) from 20 April 2018 to 31 October 2018 (6-month trial period). The test site is located at an approximate distance of 14 km from the coast. The distance between the measuring buoy and the platform is 250 m (Figure 2). Both LIDARs allow measurements at 12 altitudes between 40 m and 200 m, plus the natural elevation due to the buoy (3.5 m to Mean Sea Level, MSL) or the platform (14.4 m to MSL). The measurement mast (erected by EDF Renouvelables(r)) is equipped with two anemometers (Risoe P2546 A horizontal boom-mounted) at altitudes 33.8 m and 54.8 m to MSL. Only the measurements from the cup anemometer located at altitude 54.8 m are used in this study. For all the results presented in Section 4.3, the data measured by a WindCube at the desired height for comparison with the anemometer are linearly interpolated from the twelve evaluated altitudes. In the comparisons of the floating LIDAR to the fixed LIDAR, since the fixed LIDAR is taken as the reference, we interpolate the floating LIDAR measurements to the altitudes evaluated by the fixed LIDAR. The floating wind LIDAR is mounted on the WINDSEA_02 buoy developed by AKROCEAN(r) (France). The 12-ton buoy (Figure 2a) is powered by solar panels, a turbine in the wave tank, methanol cartridges and batteries. Through the wave tank, the system uses passive mechanical stabilization to limit the motion of the buoy. The buoy is anchored to the ground and the mooring line is connected to an intermediate buoy to limit the effect of line tension on the buoy movement. A wave buoy is associated with the WINDSEA_02, providing 30-min statistics of waves behavior (height and period). The WindCube v2(r) installed on the buoy is associated with an IMU measuring the six degrees of freedom (\(\Phi,\beta,\Psi,V_{u},V_{v},V_{w}\)) at a frequency rate of 10 Hz. We note that the dynamic behavior of the buoy in response to wave motion depends on its geometry, weight and anchorage. The IMU measurements are directly related to a particular buoy, and are not representative of all experimental setups. The use of inertial measurements to correct the wind LIDAR measurements captures all the physics of the buoy motion perceived by the wind LIDAR. We also note that the yaw measurements from an IMU tend to drift over time. In our study, the model used for the turbulence intensity correction relies on the relative temporal dynamics of the yaw motion in a 10-min interval. Since the drift occurs on time scales longer than 10 min, we keep the yaw measurement from the IMU unchanged. For confidentiality reasons, not all six months of data could be processed. 13 weeks have been selected to reflect the range of meteorological conditions typically encountered by the floating LIDAR at this site. A K-means clustering method [22] was used to segregate the hourly datasets according to wind (mean wind, direction and boundary layer shear coefficient), wave (period and mean height) and atmospheric (temperature and precipitation height) conditions. Seven clusters emerged from the K-means method. Subsequently, the seven most representative weeks of the clusters and the six harshest weeks were selected to build the 13 weeks dataset. The wind data used for the clustering were measured by the floating LIDAR, the wave data by the wave buoy and the atmospheric data were extracted  
Figure 2: Presentation of the experimental means deployed on the site 14 km off the coasts of Fécamp. (**a**) Photograph of the WINDSEA_02 buoy (in the foreground) accompanied by the wave buoy (in red). The fixed platform is visible in the background. (**b**) Diagram of the experimental means, the dimensions are not respected and the LIDAR is not to scale.