Computation of Optical Refractive Index Structure Parameter from its Statistical Definition Using Radiosonde Data

TL;DR

This paper presents a model to estimate the atmospheric optical refractive index structure parameter $C_n^2$ using radiosonde data, aiding optical site selection and turbulence profiling for FSO and astronomy.

Contribution

It introduces a $C_n^2$ estimation model based on its statistical definition using radiosonde data, comparable to existing Tatarskii-based models.

Findings

The model accurately estimates $C_n^2$ profiles from radiosonde data.

It can identify isolated turbulent layers using pressure and temperature.

Performance is similar to Tatarskii-based models.

Abstract

Knowledge of the optical refractive index structure parameter $C_n^2$ is of interest for Free Space Optics (FSO) and ground-based optical astronomy, as it depicts the strength of the expected scintillation on the received optical waves. Focus is given here to models using meteorological quantities coming from radiosonde measurements as inputs to estimate the $C_n^2$ profile in the atmosphere. A model relying on the $C_n^2$ statistical definition is presented and applied to recent high-density radiosonde profiles at Trappes (France) and Hilo, HI (USA). It is also compared to thermosonde measurements coming from the T-REX campaign. This model enables to obtain site-specific average profiles and to identify isolated turbulent layers using only pressure and temperature measurements, paving the way for optical site selection. It offers similar performance when compared to a Tatarskii-based model inspired by the literature.