Atmospheric turbulence prediction for optical link optimization in laser telemetry and free space telecommunications

Accurate prediction of atmospheric and turbulence conditions are of interest for astronomical community and free space optical communications. The a priori knowledge of atmospheric conditions several hours before the observations allows to optimize the programmation of astronomical observations called "flexible scheduling". In the field of free space optical telecommunications, it can help to identify the optical ground station least impacted by turbulence and to identify when the optical quality of the atmosphere is favorable for transmission/reception. In this thesis, a numerical approach based on the Weather and Research Forecasting (WRF) model coupled with different optical turbulence models has been used. Optimization of the prediction by a "site learning" method has been performed, considering the importance of using local measurements to improve the turbulence model and better take into account the local specificities of a given site. This method has been tested at the Calern Observatory site, France. The results showed that the "site learning" brings an improvement of the prediction. Sensitivity studies to different model options were developed to define a standard methodology to obtain an optimal WRF configuration. This technique has been applied to the Cerro Pachón Observatory site, in Chile. Still in this quest to take into account the specificities of a site, we have developed a new experiment consisting of an instrumented drone to improve the prediction in the planetary boundary layer. Results of a measurement campaign carried out at the Calern Observatory are presented.