Stochastic method for turbulence estimation from Doppler lidar measurements

Rottner, Lucie ; Baehr, Christophe ; Dabas, Alain ; Hammoud, Linda

Année de publication
2017
Résumé
The Doppler lidar technology is known for its ability to measure accurate winds with fine time and space resolutions. The derivation of turbulence parameters from lidar wind measurement has been attempted by several authors. All of them relate the turbulence parameters to long-time series (several tens of minutes) of wind measurements. The method presented here retrieves estimations of the atmospheric turbulence at much finer time scales. The technique is based on a wind reconstruction method applied to a five-beam wind Doppler lidar (namely the WindCube model by Leosphere). The method relies on a particle filter. The suggested reconstruction algorithm links the lidar observations to numerical particles to obtain turbulence estimations every time new observations are available. The high frequency of the estimations is an innovation and is detailed and discussed here. Moreover, the presented algorithm enables reconstruction of the wind in three dimensions in the observed volume. Thus, we locally have access to the spatial variability of the turbulent atmosphere. The suggested algorithm is applied to a set of real observations. The results show that the estimation of the turbulent parameters is significantly improved. They open the way to the use of lidars for scientific and industrial purposes such as site studies for wind farms.
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