<title>Study of optical turbulence in the atmospheric boundary layer by acoustic remote sensing</title>

Among current detection methods of the atmospheric boundary layer, sounding balloon has disadvantages such as low recovery and low reuse rate, anemometer tower has disadvantages such as fixed location and high cost, and remote sensing detection has disadvantages such as low data accuracy. In this paper, a meteorological element sensor was carried on a six-rotor UAV platform to achieve detection of meteorological elements of the atmospheric boundary layer, and the influence of different installation positions of the meteorological element sensor on the detection accuracy of the meteorological element sensor was analyzed through many experiments. Firstly, a six-rotor UAV platform was built through mechanical structure design and control system design. Secondly, data such as temperature, relative humidity, pressure, elevation, and latitude and longitude were collected by designing a meteorological element detection system. Thirdly, data management of the collected data was conducted, including local storage and real-time display on ground host computer. Finally, combined with the comprehensive analysis of the data of automatic weather station, the validity of the data was verified. This six-rotor UAV platform carrying a meteorological element sensor can effectively realize the direct measurement of the atmospheric boundary layer and in some cases can make up for the deficiency of sounding balloon, anemometer tower, and remote sensing detection.

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Some results of turbulence structure in the atmospheric boundary layer by remote sensing

10.1117/12.482313 ◽

2002 ◽

Author(s):

Ningquan Weng ◽

Liming Xiao ◽

Yingjian Wang ◽

Zhiben Gong

Keyword(s):

Remote Sensing ◽

Boundary Layer ◽

Atmospheric Boundary Layer ◽

Turbulence Structure

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Remote Sensing And Surface Observations Of The Response Of The Atmospheric Boundary Layer To A Solar Eclipse

Boundary-Layer Meteorology ◽

10.1023/a:1020837400800 ◽

2003 ◽

Vol 106 (1) ◽

pp. 93-115 ◽

Cited By ~ 14

Author(s):

Fanny Girard-Ardhuin ◽

B. Bénech ◽

B. Campistron ◽

J. Dessens ◽

S. Jacoby-Koaly

Keyword(s):

Remote Sensing ◽

Boundary Layer ◽

Atmospheric Boundary Layer ◽

Solar Eclipse ◽

Surface Observations

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

Applied Sciences ◽

10.3390/app11188523 ◽

2021 ◽

Vol 11 (18) ◽

pp. 8523

Author(s):

Manman Xu ◽

Shiyong Shao ◽

Qing Liu ◽

Gang Sun ◽

Yong Han ◽

...

Keyword(s):

Neural Network ◽

Boundary Layer ◽

Atmospheric Boundary Layer ◽

Single Parameter ◽

Optical Turbulence ◽

Outer Scale ◽

Backpropagation Neural Network ◽

Statistical Results

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.

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