<i>In situ</i> measurements and neural network analysis of the profiles of optical turbulence over the Tibetan Plateau

ABSTRACT The vertical profile of $C_n^2$ is the main factor for accurate astronomical observation and laser communication, however, hardware-based instruments associated data are not widely available due to logistical financial issues. In this article, we developed an indirect method, a hybrid network structure which combination backpropagation neural simulated annealing algorithm, fit $C_n^2$. Radiosonde measurements from field campaign over Tibetan Plateau at Dachaidan (37.7○N, 95.3○E, 3180 m ASL) were performed in 2020 August estimate accuracy our model, during balloon-borne portable turbulence meteorological radiosonde was used measure atmospheric optical profiles. Besides, integrated parameters (the coherence length r0, seeing ε0, isoplanatic angle θ0, wavefront time τ0), derived wind-speed profiles, investigated applications using proposed model. addition, quantitative evaluations such as correlation coefficient, root mean squared error, systematic bias quantify performance More interesting, model found outperform external scale prevalent conditions shows better reliable estimates.