Model for estimating the astronomical seeing at Dome A, Antarctica.

A model for estimating astronomical seeing at Kunlun Station (Dome A, Antarctica) is proposed. This model is based on the Tatarskii equation, using the wind shear and temperature gradient as inputs, and a seeing model depending directly on the weather data is provided. The seeing and near-ground weather data to build and validate the proposed seeing model were measured at Dome A during the summer of 2019.

Simple method to estimate the optical turbulence over snow and ice.

A simple physics-based method for estimating optical turbulence (2) within the surface layer over snow and ice is proposed, using the Tatarski equation with an improved outer scale model. This improved outer scale model mainly requires the calculation of the wind shear and temperature gradients. Based on the measurements from a mobile polar atmospheric parameter measurement system at the Antarctic Taishan Station in 2014, 2 was estimated using two methods: the Tatarski equation and the Monin-Obukhov similarity (MOS) theory.

Reliable model to estimate the profile of the refractive index structure parameter (C) and integrated astroclimatic parameters in the atmosphere.

Based on the statistical study of meteorological balloons equipped with thermosondes, a new model that estimates the profile of the refractive index structure constant (2) is proposed. Utilizing temperature, pressure, and wind shear as inputs, this new approach can estimate vertical profiles of 2 with 100 m vertical resolution. We used four outer scale models (Thorpe, HMNSP99, Dewan, and our proposed model) on data acquired from Rongcheng (Shandong Peninsula) and Maoming (Guangdong Province) to estimate the 2 profiles and compared the results with the measured 2 profile.

New $\text{C}_{n}^{2}$ statistical model based on first radiosonde turbulence observation over Lhasa.

It is worth highlighting that, for the first time to the best of our knowledge, vertical profiles of atmospheric parameters and $C_n^2$ were measured at Lhasa, south of the Tibetan Plateau, using balloon-borne radiosondes. Based on the measurements, two new statistical models (Lhasa HMN and Lhasa Dewan) for estimating turbulence strength are proposed. Attention has been paid to evaluate the reliability of the two models to reconstruct vertical profiles of $C_n^2$ from a statistical perspective.

Adaptive niche-genetic algorithm based on backpropagation neural network for atmospheric turbulence forecasting.

Because systematic direct measurements of the refractive index structure constant ($C_n^2$Cn2) are not available for many climates and seasons, we developed an indirect method to forecast optical turbulence. The $C_n^2$Cn2 was estimated from a backpropagation neural network optimized by an adaptive niche-genetic algorithm. The estimated result was validated against the corresponding six-day $C_n^2$Cn2 data from a field campaign of the 30th Chinese National Antarctic Research Expedition.

Mesoscale optical turbulence simulations above Tibetan Plateau: first attempt.

The vertical distributions of optical turbulence ( 2 profiles) are a major factor in defining the capabilities of ground-based telescopes and interferometers. As site-testing campaigns are extremely expensive and instruments only provide the local atmospheric parameter, atmospheric modeling might represent an advance prediction result in astronomical sites. The key meteorological parameters and the integrated astroclimatic parameters (Fried parameter r, seeing ɛ, isoplanatic angle θ and wavefront coherence time τ) related to the 2 profiles above the Tibetan Plateau are investigated for astronomical applications by using the Weather Research and Forecasting (WRF) model.