Optical Turbulence Profile Forecasting and Verification in the Offshore Atmospheric Boundary Layer

Manman Xu,Qing Liu,Yong Han,Shiyong Shao,Gang Sun,Ningquan Weng

doi:10.3390/app11188523

Abstract

A backpropagation neural network (BPNN) approach is proposed for the forecasting and verification of optical turbulence profiles in the offshore atmospheric boundary layer. To better evaluate the performance of the BPNN approach, the Holloman Spring 1999 thermosonde campaigns (HMNSP99) model for outer scale, and the Hufnagel/Andrew/Phillips (HAP) model for a single parameter are selected here to estimate profiles. The results have shown that the agreement between the BPNN approach and the measurement is very close. Additionally, statistical operators are used to quantify the performance of the BPNN approach, and the statistical results also show that the BPNN approach and measured profiles are consistent. Furthermore, we focus our attention on the ability of the BPNN approach to rebuild integrated parameters, and calculations show that the BPNN approach is reliable. Therefore, the BPNN approach is reasonable and remarkable for reconstructing the strength of optical turbulence of the offshore atmospheric boundary layer.

Highlights

The atmospheric boundary layer is an important bridge for the exchange of momentum, heat, and water vapor between the earth’s surface and the free atmosphere [1].The strength of optical turbulence is high in the atmospheric boundary layer, which is a distinctive feature that distinguishes the boundary layer from other atmospheric layers.Atmospheric turbulence is the primary reason for laser beam wandering and spreading, and it leads to a serious degradation of image quality and clarity in optical applications.Atmospheric turbulence strength is generally characterized by the structural constant of the refractive index
Utilizing the bias and the RMSE, we retrieve the center root mean square error (CRMSE), which represents the intrinsic uncertainty not affected by the bias, and it provides fundamental information on the systematic bias and statistical uncertainties
The refractive index fluctuation mainly results from temperature fluctuation at visible and near-infrared wavelengths [35]

Summary

Introduction

The atmospheric boundary layer is an important bridge for the exchange of momentum, heat, and water vapor between the earth’s surface and the free atmosphere [1].The strength of optical turbulence is high in the atmospheric boundary layer, which is a distinctive feature that distinguishes the boundary layer from other atmospheric layers.Atmospheric turbulence is the primary reason for laser beam wandering and spreading, and it leads to a serious degradation of image quality and clarity in optical applications.Atmospheric turbulence strength is generally characterized by the structural constant of the refractive index. The strength of optical turbulence is high in the atmospheric boundary layer, which is a distinctive feature that distinguishes the boundary layer from other atmospheric layers. Atmospheric turbulence is the primary reason for laser beam wandering and spreading, and it leads to a serious degradation of image quality and clarity in optical applications. Atmospheric turbulence strength is generally characterized by the structural constant of the refractive index. The fluctuations of the refractive index of the atmosphere Cn2 , known as optical turbulence, are produced by wind blowing over the earth’s surface and temperature gradients between this surface and the air above it [2]. Because of the complexity of atmospheric phenomena, the Cn2 field has a complicated spatio-temporal structure

Methods

Results

Conclusion