Analysis of atmospheric optical turbulence model-methods and progress br

Stratification is a significant characteristic of atmospheric turbulence, especially high-altitude turbulence.At a fixed height, the real optical turbulence value fluctuates by 1-2 orders of magnitude or even greater on theaverage value. The turbulence profile model based on the observed data is a statistical average result. It canneither represent the stratification characteristics of an actual atmospheric turbulence profile nor have theprediction function, and can not fully meet the demand of optical engineering. Owing to the limitation of thecapacity and speed of the computer, it is impossible to solve the Navier Stokes equation through directnumerical simulation (DNS) and large eddy simulation (LES) to predict the optical turbulence. The solution isto predict the conventional gas parameters through the mesoscale weather numerical prediction model MM5/WRF, and then calculate the turbulence parameters through the turbulence parameterization scheme. In thispaper, the prediction methods and research results of in surface layer,boundary layer and free atmospherelayer are introduced. Tatarski formula is derived in detail from the turbulence kinetic energy predictionequation and the temperature fluctuation variance prediction equation, and the physical meaning and applicableconditions of the formula are summarized. The latest research progress of neural network prediction andAntarctic astronomical site selection is mainly introduced. The characteristics and differences among differentmodels, such as the empirical model fitted with experimental data, the parameter model with conventionalmeteorological parameters based on Kolmogorov turbulence theory, the prediction model related to mesoscalemeteorological model, and the neural network method based on data driving and so on, are analyzed. It isemphasized that Kolmogorov turbulence theory is the theoretical basis of the existing atmospheric opticalturbulence parameter models.