While floating wind lidars provide reliable and cost-effective measurements, these measurements may be inaccurate due to the motion of the installation platforms. Prior studies have not distinguished between systematic errors associated with lidars and errors resulting from motion. This study will fill this gap by examining the impact of platform motion on two types of profiling wind lidar systems: the pulsed WindCube V1 (Leosphere) and the continuous-wave ZephIR 300 (Natural Power). On a moving hexapod platform, both systems were subjected to 50 controlled sinusoidal motion cases in different degrees of freedom. Two reference lidars were placed at a distance of five meters from the platform as reference lidars. Motion-induced errors in mean wind speed and turbulence intensity estimation by lidars are analyzed. Additionally, the effectiveness of a motion correction approach in reducing these errors across various scenarios is evaluated. The results indicate that presence of rotational motion leads to higher turbulence intensity (TI) estimation by moving lidars. The absolute percentage error between lidars is the highest when lidars are exposed to yaw and heave motion and is the lowest when exposed to surge motion. The correlation between lidars, though it is the lowest in the presence of pitch, yaw, and heave motion. Furthermore, applying motion compensation can compensate the correlation drop and erroneous TI estimation.

Kelvin–Helmholtz billows (KHB) and the associated turbulence characteristics in the atmospheric boundary layer (ABL) are mainly investigated through simulations and limited observations. Traditional methods using in-situ wind sensors are constrained by mast height, resulting in a limited understanding of KHBs at higher altitudes. Lidar remote sensing provides a promising approach for studying KHBs at altitudes above 100 m. This study presents observations of KHBs in the marine ABL above 600 m, through ship-borne lidar observations. Two Doppler wind lidars, one scanning lidar, and one wind profiler, were installed for several months on a crew transfer vessel, operating in the Rødsand 2 wind farm off the coast of Denmark. On 2023-02-22, KHBs were detected between 600 and 800 m altitude over 10 min. The standard deviation of vertical turbulence was found to increase by a factor of two during KHB occurrence. The power spectral density of vertical fluctuations showed a greater increase in the frequency range below 0.1 Hz, with a peak indicating a periodic pattern with a period of 55 s. The kurtosis of the vertical component also showed a large increase near the edge of the billows, as documented in the scientific literature for billows occurring near the surface. The billows triggered a downward mixing of aerosols and momentum to around 550 m. Although no interaction between the wind farm and the KHBs was observed, we hypothesise that KHB may reduce wind farm wake losses in shallower stable layers above the farm by enhancing vertical mixing and downward momentum transport.

Vertical momentum entrainment above offshore wind farms plays a key role in the recovery of wind turbine and wind farm wakes but remains poorly documented by field measurements. The LOLland offshore Lidar EXperiment (LOLLEX) campaign introduced a novel measurement approach to address this knowledge gap. The primary objective of this campaign was to develop a new atmospheric measurement strategy to characterise and quantify the vertical momentum entrainment inside and outside an offshore wind farm using Doppler wind lidar technology. LOLLEX was conducted from September 2022 to September 2023 in Denmark in and around the Rødsand II wind farm just south of the island of Lolland. During this campaign, two pulsed Doppler wind lidars, a scanning and a profiling instrument, were deployed onboard a crew transfer vessel (CTV) commuting daily between the harbour and the offshore wind farm Rødsand II. Additionally, a scanning pulsed Doppler wind lidar was mounted on a transformer platform north of the wind farm to perform range height indicator scans across the farm. Motion-corrected mean wind speed data were collected up to 300 m above the sea surface by the profiler lidar. The scanning lidar collected data up to 2.5 km alternating between the profiling mode and vertical stare mode. The latter scan operated with a sampling frequency of 1 Hz and along-beam spatial resolution of 10 m, allowing for the study of the turbulent vertical wind velocity component. The dataset includes several thousand hours of vertical scans. As a result of the moving vessel, many of the observations occurred inside or in the close vicinity of the wind farm, providing insight into the near and far wakes of individual and multiple turbines. The potential and limitations of the new measurement strategy is illustrated using four case studies: (1) the observation of a Kelvin–Helmholtz instability above the wind farm, examined further in a companion paper; (2) turbulent mixing propagating downward from the top of the boundary layer, enhancing momentum entrainment; (3) internal atmospheric waves and (4) wake characterisation inside the wind farm using the range-height indicator scans from the lidar deployed on the platform. This work demonstrates a novel methodology integrating remote sensing with a mobile offshore platform to measure turbulence at unprecedented altitudes. The dataset offers valuable data for wind energy research, boundary-layer meteorology, and further development of atmospheric measurement techniques.

Vertical momentum entrainment is driven by vertical shear and turbulent mixing and plays a key role in the recovery of wind turbine and wind-farm wakes, but remains poorly documented by field measurements. The LOLland offshore Lidar EXperiment (LOLLEX) campaign introduced a novel measurement approach to address this knowledge gap. The primary objective of this campaign was to develop a new atmospheric measurement strategy using Doppler wind lidar technology to better understand atmospheric conditions favourable to enhanced momentum entrainment inside and outside an offshore wind farm. LOLLEX was conducted from September 2022 to August 2023 in Denmark, in and around the Rødsand II wind farm, just south of the island of Lolland. During this campaign, two pulsed Doppler wind lidars, a scanning lidar (WindCube100S) and a lidar wind profiler (WindCubeV2), were deployed onboard a crew transfer vessel (CTV) commuting daily between the harbour and the Rødsand II offshore wind farm. Additionally, a scanning pulsed Doppler wind lidar (Halo Photonics) was mounted on a transformer platform north of the wind farm to perform range height indicator scans across the farm. Horizontal wind speed data were collected up to 300 m above the sea surface by the lidar wind profiler. The scanning lidar on the CTV collected data up to 2.5 km, alternating between the wind profiling mode and vertical stare mode. The latter scan operated at a sampling frequency of 1 Hz and along-beam spatial resolution of 10 m, allowing for the study of the turbulent vertical wind velocity component. The dataset includes several thousand hours of vertical scans. As a result of the moving vessel, many of the observations occurred inside or near the wind farm, providing insight into the near and far wakes of individual and multiple turbines. The potential and limitations of the new measurement strategy are illustrated using four case studies: (1) the observation of a Kelvin-Helmholtz instability above the wind farm, examined further in a companion paper; (2) turbulent mixing propagating downward from the top of the boundary layer; (3) internal atmospheric waves; and (4) wake characterisation inside the wind farm using the range-height indicator scans from the lidar deployed on the platform. This work demonstrates a novel methodology integrating remote sensing with a mobile offshore platform to measure turbulence at unprecedented altitudes. The dataset offers valuable data for wind energy research, boundary-layer meteorology, and further development of atmospheric measurement techniques.

Vertical momentum entrainment above offshore wind farms plays a key role in the recovery of wind turbine and wind farm wakes but remains poorly documented by field measurements. The LOLland offshore Lidar EXperiment (LOLLEX) campaign introduced a novel measurement approach to address this knowledge gap. The primary objective of this campaign was to develop a new atmospheric measurement strategy to characterise and quantify the vertical momentum entrainment inside and outside an offshore wind farm using Doppler wind lidar technology. LOLLEX was conducted from September 2022 to September 2023 in Denmark in and around the Rødsand II wind farm just south of the island of Lolland. During this campaign, two pulsed Doppler wind lidars, a scanning and a profiling instrument, were deployed onboard a crew transfer vessel (CTV) commuting daily between the harbour and the offshore wind farm Rødsand II. Additionally, a scanning pulsed Doppler wind lidar was mounted on a transformer platform north of the wind farm to perform range height indicator scans across the farm. Motion-corrected mean wind speed data were collected up to 300 m above the sea surface by the profiler lidar. The scanning lidar collected data up to 2.5 km alternating between the profiling mode and vertical stare mode. The latter scan operated with a sampling frequency of 1 Hz and along-beam spatial resolution of 10 m, allowing for the study of the turbulent vertical wind velocity component. The dataset includes several thousand hours of vertical scans. As a result of the moving vessel, many of the observations occurred inside or in the close vicinity of the wind farm, providing insight into the near and far wakes of individual and multiple turbines. The potential and limitations of the new measurement strategy is illustrated using four case studies: (1) the observation of a Kelvin–Helmholtz instability above the wind farm, examined further in a companion paper; (2) turbulent mixing propagating downward from the top of the boundary layer, enhancing momentum entrainment; (3) internal atmospheric waves and (4) wake characterisation inside the wind farm using the range-height indicator scans from the lidar deployed on the platform. This work demonstrates a novel methodology integrating remote sensing with a mobile offshore platform to measure turbulence at unprecedented altitudes. The dataset offers valuable data for wind energy research, boundary-layer meteorology, and further development of atmospheric measurement techniques.

Vertical momentum entrainment above offshore wind farms plays a key role in the recovery of wind turbine and wind farm wakes but remains poorly documented by field measurements. The LOLland offshore Lidar EXperiment (LOLLEX) campaign introduced a novel measurement approach to address this knowledge gap. The primary objective of this campaign was to develop a new atmospheric measurement strategy to characterise and quantify the vertical momentum entrainment inside and outside an offshore wind farm using Doppler wind lidar technology. LOLLEX was conducted from September 2022 to September 2023 in Denmark in and around the Rødsand II wind farm just south of the island of Lolland. During this campaign, two pulsed Doppler wind lidars, a scanning and a profiling instrument, were deployed onboard a crew transfer vessel (CTV) commuting daily between the harbour and the offshore wind farm Rødsand II. Additionally, a scanning pulsed Doppler wind lidar was mounted on a transformer platform north of the wind farm to perform range height indicator scans across the farm. Motion-corrected mean wind speed data were collected up to 300 m above the sea surface by the profiler lidar. The scanning lidar collected data up to 2.5 km alternating between the profiling mode and vertical stare mode. The latter scan operated with a sampling frequency of 1 Hz and along-beam spatial resolution of 10 m, allowing for the study of the turbulent vertical wind velocity component. The dataset includes several thousand hours of vertical scans. As a result of the moving vessel, many of the observations occurred inside or in the close vicinity of the wind farm, providing insight into the near and far wakes of individual and multiple turbines. The potential and limitations of the new measurement strategy is illustrated using four case studies: (1) the observation of a Kelvin–Helmholtz instability above the wind farm, examined further in a companion paper; (2) turbulent mixing propagating downward from the top of the boundary layer, enhancing momentum entrainment; (3) internal atmospheric waves and (4) wake characterisation inside the wind farm using the range-height indicator scans from the lidar deployed on the platform. This work demonstrates a novel methodology integrating remote sensing with a mobile offshore platform to measure turbulence at unprecedented altitudes. The dataset offers valuable data for wind energy research, boundary-layer meteorology, and further development of atmospheric measurement techniques.