Abstract
A dual-lidar system comprising two WindCube v2.1 Doppler lidars – one oriented horizontally at a 45° angle relative to the other – was deployed to estimate atmospheric turbulence using the variance method. This approach derives second-order velocity statistics directly from line-of-sight (LOS) velocity variances, enabling the reconstruction of the three-dimensional velocity variance components without retrieving instantaneous wind vectors. Its performance is evaluated against the traditional method commonly used in the wind energy sector, which reconstructs instantaneous velocity components from single-lidar LOS measurements prior to computing turbulence statistics. Both methods are assessed at a single measurement height using a 30 d collocated dataset, with sonic anemometer measurements as reference and classification by atmospheric stability. The analysis focuses on turbulence intensity (TI), and performance is quantified using the mean relative bias error (MRBE) and relative root mean square error (RRMSE), following Det Norske Veritas (DNV) load-validation acceptance criteria (MRBE within ±5 % and RRMSE ≤ 15 %). Results show that the variance method demonstrates improved agreement with the reference measurements across nearly all wind-speed bins. For along-wind TI, MRBE values range between 0 % and −5 %, with RRMSE remaining below 15 % over the full wind-speed range, fully satisfying the DNV criteria. For cross-wind TI, the MRBE criterion is met, while the RRMSE threshold is exceeded. In contrast, the traditional method meets both DNV criteria for along-wind TI only at wind speeds above approximately 7 m s−1 and fails to satisfy either criterion for cross-wind TI across the investigated range. Overall, the results demonstrate that the variance method provides more robust and DNV-compliant TI estimates than the traditional reconstruction approach, particularly for along-wind turbulence relevant to wind turbine load validation.