Ground-based synchronous optical instrument for measuring atmospheric visibility and turbulence intensity: theories, design and experiments

Yong Han; Peng Gao; Jiaolong Huang; Tongxiao Zhang; Jianjun Zhuang; Maohai Hu; Yonghua Wu

doi:10.1364/OE.26.006833

1. Introduction

Atmospheric visibility and atmospheric turbulence intensity play an important role in air quality prediction, boundary layer process, climate environment model, light propagation and communication [1, 2]. Atmospheric visibility is related to atmospheric transparency, which reflects the atmospheric extinction or attenuated properties [3, 4] and directly relates to aerosol loading. In the field of environmental monitoring, it is an important feature of air pollution. For example, atmospheric visibility decline is an important environmental issue in China due to large amount of aerosol emissions [5, 6]. In the aviation, navigation and other areas of transportation, atmospheric visibility is one of the meteorological elements related to safety and security. Therefore, the study of atmospheric visibility has always been widely concerned by all sectors of society. On the other hand, atmospheric turbulence is one of key form of motion in the atmosphere whose intensity is quantitatively described by atmospheric refractive index constant $C_{n}^{2}$ [7]. Particularly, the problem of light propagation in turbulent atmosphere is one of the most difficult parts of atmospheric optics [8–12]. When the beam propagates in the atmospheric turbulence, the turbulence effects on the beam such as flicker, drift and expansion can be caused by the fluctuation of the atmospheric refractive index, which then leads to the beam wavefront distortion, and destroys the coherence of the light and blurs the optical image. Thus, the turbulence can affect the visibility measurement in the conventional light transmission methods. In addition, it also makes astronomical observation very difficult when the air turbulence is strong. Below we briefly introduce the conventional measurement methods and instruments for the visibility and turbulence.

In meteorology, visibility is a measure of the distance at which an object or light can be clearly discerned, and visibility affects all forms of traffic: roads, sailing and aviation [5]. From 1957, the laws of Koshmieder have been established, and scientists developed the visibility measurement techniques [13]. Visibility measurement is mainly achieved by the forward scattering visibility meter and transmission visibility meter, etc.. The forward scattering visibility meter has the advantages of convenient installation, compact structure, small size and low cost, however, whose relatively small measuring space will cause lager errors [14, 15]. The transmittance meter directly detects the transmittance of the atmosphere, whose measurement accuracy is relatively high than forward scatter visibility sensor from its long optical path, but, the conventional transmittance meter does not take into account the impact of atmospheric turbulence. The main reason for this deviation is the mutual drag between aerosol particles and turbulent air mass which can bias the transmission measurement.

As for the turbulence measurement, as early as 1977, Wang had developed an optical technique for measuring the refractive index structure parameter $C_{n}^{2}$ for reflect atmospheric turbulence intensity by using relatively large incoherent transmitting and receiving optics [16]. In 1999, Muschinski et al. studied the local average vertical structure of $C_{n}^{2}$ by using the wind profile radar vertical direction of the return signal power spectrum analysis [17]. Since 2001, various methods for detecting the refractive index structure constants of the atmosphere have been studied such as AMK-02 ultrasonic atmospheric parameter synthesis meter and QHTP-2 temperature pulsating radiosonde [18–21], etc..

Measurements of turbulence are important for studies of aerosol effects on clouds and PBL process, as well as the aerosol emission intensity related to air vertical transport and dispersion. Moreover, a reduced turbulence can exacerbate both the human health impacts of high concentrations of fine particles and conditions favorable for low-visibility fog events [22]. High concentrations of absorbing aerosols in the PBL can suppress the turbulence intensity through revising air thermal-dynamical stability [23].

However, the above conventional measurements ignore the influences from the interaction between aerosol particles and turbulent air masses, which may lead to large measurement deviations [24]. Turbulence is any irregular or disturbed flow in the atmosphere producing eddies and gusts, which includes thermal or convective turbulence and mechanical turbulence from wind flowing. Turbulence may reduce visibility by distorting light phase and intensity (referred to as scintillation). Such effects of turbulence are due to both spatial and temporal random fluctuations of refractive index that are related to the variations of temperature, pressure, aerosols, moisture and wind [25–28]. On the other hand, aerosols can directly absorb and scatter solar radiance, thus affecting visibility by changing atmospheric transmittance and affecting turbulence by changing air thermal structure. For instance, black carbon aerosols strongly absorb the sunlight and thus suppress turbulence in the atmospheric boundary layer [29], as well as make visibility worse.

For example, Fig. 1 shows that there are a lot of aerosol particles illuminated in the air turbulence cell. It is obviously that aerosol particles and air turbulences interact with each other. On the one hand, the atmospheric turbulent cells drive aerosol particles movement and thus change the aerosol spatial distribution and light transmittance. And aerosol particles drag the flow of turbulent cell or change the air thermal-dynamical process by absorbing and scattering light intensity. That is to say, the strong turbulence will modify the light intensity distribution in the detector thus affecting the measurement of the visibility. Also, with the poor visibility and subsequent low atmospheric transmittance, the signal-to-noise in measuring the turbulence will become worse. In order to overcome this shortcoming, we develop a new ground-based synchronous optical system, AVTOM, for measuring atmospheric visibility and turbulence intensity by means of transmission measurements in this paper.

Fig. 1 The experiment image of the influence between aerosol particles and atmospheric turbulence (From Prof. Dr. Ruizhong Rao, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Science).

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The aim of this present study is to develop a novel synchronous optical system for measuring atmospheric visibility and turbulence intensity at the same time. We will discuss the theories, design and experiments of the AVTOM. The layout of the paper is as follows. In section 2, based on the principle of transmission measurement, the measurement methods are described, respectively. And how to design the optical system structure is concerned. The experimental results of the AVTOM and comparative analysis with other commercial instruments are presented in section 3. Section 4 introduces the calibration methods and the error analysis. And a short summary are shown in section 5.

2. Instrument design and method

The detection of atmospheric visibility is based on the principle of extinction while the measurement of atmospheric turbulence is based on the principle of light intensity fluctuation. Both of them convert the received light intensity signal into voltage signal for data analysis and processing. The difference is that the measurement of atmospheric turbulence requires the detection of the pulse signal, and the measurement of atmospheric visibility needs to take these successive pulsed optical signals averaged as a continuous signal in the processing. More details are given in the subsections below.

2.1 Theories of atmospheric visibility measurement

Measurement of the extinction coefficient is essential to understanding how atmospheric aerosols affect the visibility of scenic vistas [26]. Atmospheric visibility, or meteorological optical range ( $M O R$ ), refers to the distance traveled through the road, which the luminous flux of a parallel beam emitted by an incandescent lamp with a color temperature of 2700K is weakened to 5% of the initial value in the atmosphere [30]. According to Bouguer-Lambert's law, if $M O R$ is used to represent the distance of the meteorological distance, that is, the distance through which the luminous flux is reduced to 5% [31]:

M O R = - \frac{\ln ε}{σ} = - \frac{\ln 0.05}{σ}

Here, the

ε

is the visual contrast threshold [4], according to the provisions of the International Meteorological Organization, with

ε = 0.05

.

σ

is atmospheric extinction coefficient. From (1), we can see that the accurate measurement of the visibility value depends on the accurate measurement of the atmospheric extinction coefficient. When the emission spot is filled with the receiver tube field, the extinction coefficient is determined by the following EQs [32–34]:

P = k P_{0} \frac{D^{2}}{4 L^{2} {(\tan θ)}^{2}} \exp (- σ L)

Where

P_{0}

is the transmit power of the LED; P is the power received by the instrument's optical receiver;

D

is the aperture of the photodetector;

L

is the baseline length;

θ

is the divergence angle of the LED light source; k is a constant, which is determined by the system structure considering, for there are a part of the signal light not in the receiving field of view, so the received signal power is only one part of the attenuation of the light source signal. When the divergence angle

θ

is small, the Eq. (2) can be simplified as follows:

P = k P_{0} \frac{D^{2}}{4 L^{2} θ^{2}} exp (- σ L)

Where, the

P_{0}

,

D

,

L

and

θ

are constants. Let’s define

\frac{1}{β} = \frac{D^{2}}{4 L^{2} θ^{2}}

, and

T = \frac{P}{k P_{0}}

, we can derive the atmospheric extinction coefficient as follows:

σ = - \frac{1}{2 L} \ln β T

Where

β

, k,

P_{0}

and

L

are fixed values or constants. As long as the received light wave signal intensity P is measured and the instrument constant is calibrated, the

σ

can be calculated according to (4) to obtain the visibility value. Taking into account the intensity of the light source will be subject to external factors such as interference, the system also performs real-time measurements of

P_{0}

.

2.2 Principle of atmospheric turbulence measurement

The propagation characteristics of light in turbulent atmosphere can be analyzed by the coherence, phase characteristics, light intensity characteristics, and image characteristics. The scintillation method and the angle of arrival are the method of measuring the average atmospheric turbulence intensity of the path.

According to the theory of light transmission, the spherical wave at wavelength $λ$ propagates through atmospheric turbulence. If the light intensity is expressed by $I$ , the logarithmic fluctuation variance of the logarithmic light intensity in the receiving aperture $D$ at the propagation distance $L$ can calculated through following eq.s [28]:

σ_{\ln I}^{2} (D) = 4 \times {(2 π k)}^{2} \times \int_{0}^{L} d z \int_{0}^{\infty} \sin^{2} [\frac{γ (L - z)}{2 k} K^{2}] ϕ_{n} (K) K F (γ K) d K

Where k is the number of light waves, with $k = 2 π / λ$ . And K is the spatial wave number. $γ = z / L$ is the propagation factor of the spherical wave. The $ϕ_{n} (K)$ represents the spatial spectral density of the refractive index fluctuation, and it can be expressed as follows:

ϕ_{n} (K) = 0.033 C_{n}^{2} (z) K^{- 11 / 3} f (K l_{0})

Where $C_{n}^{2} (z)$ is the atmospheric refractive index structure constant, which usually reflects the air turbulence intensity. The _{$f (K l_{0})$}can be described in the factor of scale effect, $f (K l_{0}) = 1$ for the isotropic turbulence, and ε is the aperture of the ring with the ratio of inner to outer diameter [35], and the aperture filter function can be expressed as following eq.:

F (K) = {[\frac{2}{1 - ε^{2}}]}^{2} {[\frac{J_{1} (K D / 2)}{K D / 2} - ε^{2} \frac{J_{1} (ε K D / 2)}{ε K D / 2}]}^{2}

The intensity of light intensity is usually expressed by scintillation index $β_{I}^{2}$ :

β_{I}^{2} = \frac{〈 I^{2} 〉 - {〈 I 〉}^{2}}{{〈 I 〉}^{2}}

where $〈〉$ represents the statistical average. It is known that the relationship between the flicker index and logarithmic intensity fluctuation variance is $β_{I}^{2} = σ_{\ln I}^{2}$ .

If the $β_{I}^{2}$ in a certain aperture can be measured, we can use the known laser wavelength, path length, aperture parameters to calculate $C_{n}^{2}$ . In generally, the principle formula can be expressed as following eq.:

β_{I}^{2} (D) = 0.132 \times {(2 π k)}^{2} \times \int_{0}^{L} C_{n}^{2} (z) d z \int_{0}^{\infty} \sin^{2} [\frac{γ (L - z)}{2 k L} K^{2}] K^{- 8 / 3} \times {[\frac{2}{1 - ε^{2}}]}^{2} {[\frac{J_{1} (z K D / 2 L)}{z K D / 2 L} - ε^{2} \frac{J_{1} (ε z K D / 2 L)}{ε z K D / 2 L}]}^{2} d K

In practical applications, the $C_{n}^{2}$ can be obtained from the Eq. (10) [36]:

C_{n}^{2} = \frac{β_{I}^{2} (D)}{0.496 k^{7 / 6} L^{11 / 6} \times {[1 + 0.214 {(k D^{2} / 4 L)}^{7 / 6}]}^{- 1} \times [0.44 exp (- L / 1079.23) + 0.5]}

2.3 Design scheme of the instrument

The new instrument adopts two ends operation mode (transmitting and receiving) for measuring atmospheric visibility and turbulence intensity. The prototype system consists of four parts, which includes the optical transmitter unit, optical receiver unit, instrument control unit, and data receiver unit, etc. Figure 2 shows the schematic diagram of the AVTOM. The two lasers (Laser1 at 650nm, red light and Laser 2 at 532nm, green light) help align the setup of transmitter and receiver. The optical axis of the Laser 1 and Laser 2 is parallel to the outgoing beam, and they are fixed relative to the light source. When the light of the Laser 1 and Laser 2 pass through the aperture of the receiving at the corresponding position successfully, the alignment is finished. In order to prevent the optical lens from being polluted by the environment, then, there are a window lens covering the transmitter and receiver to protect the lens systems. L is the distance between the transmitter and the receiver, which is about 25m in this study.

Fig. 2 Schematic diagram of the AVTOM.

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The schematic diagram of the transmitting module and the receiving module are shown in Figs. 3(a) and 3(b), respectively. Figure 3(c) represents the AVTOM. The transmitting module includes light source, signal source, light source drive circuit and so on. The light source uses white light, because the World Meteorological Organization recommends wide spectral light sources to measure visibility. The narrow spectral light sources can lead to measurement relatively small errors in certain weather conditions. The wavelength of LED light source is 620 nm, aerosol is the main extinction material in the process of attenuation of light with a relatively weak absorption by ozone at this band. Figure 4 shows some photos of this experiment. Figure 4(a) is out field experiment. Figure 4(b) is the calibration experiment in laboratory.

Fig. 3 The schematic diagram of transmitting module (a), Schematic diagram of receiving module (b), and the AVTOM (c), respectively.

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Fig. 4 The photos are (a) Field experiment and (b) Laboratory calibration experiment, respectively.

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The signal source modulates the light intensity signal using a fixed frequency pulse signal. The light source frequency is required of 10 kHz. The high frequency of light source is to detect turbulence. The light source drive circuit drives the light source to emit a constant power signal.

The receiving module includes the optical detector, amplifier, filter, A/D converter and so on. Because the photomultiplier tube has the advantages of high sensitivity, fast response, high frequency response and high working current, so we use the photomultiplier tube as a photodetector. The amplifier consists of a tube or transistor, a power transformer, and other electrical components. The filter can filter the frequency points of the specific frequency in the power line or the frequency outside the frequency points, and obtain the power signal of a particular frequency. The received optical signal is converted into an electrical signal by optical detector, and then transmitted to industrial computer for processing after amplification, filtering and A/D conversion.

The optical emission unit adopts double lens collimating optical path using the ZEMAX software to optimize the design, and simulates the results. The optical receiving unit uses single lens to focus the light on the photodetector. The specific design parameters of the collimated optical path are as follows: (1)The entrance pupil diameter is 31mm, (2)The distance between the light source and the lens is about 60mm, (3)The divergence angle is less than or equal to 3mrad. It is well known that it is difficult to achieve a complete collimation of the optical path through a single lens. So, it is usually achieved with an aspheric single lens, a dual lens combination or a double glued lens to do that. The desired collimator lens can be obtained by editing the lens parameters in the Zemax software through simulation and optimization methods. In this study, we optimize the design of collimated optical paths in the transmitter by comparing the three different methods as follows:

Option 1: Single lens collimation

Using an aspheric lens with a thickness of 6 mm and a glass material of BK7, the distance between the light source and the lens is 70 mm and the root mean square (RMS) of the emission light is 1.062 μm. RMS reflects the collimation of outgoing rays.

Option 2: Double lens collimation

Two convex lenses with thicknesses of 6.7mm and 13mm are used. The glass materials are BK7, the distance between the light source and the lens is 56.883mm, and the RMS value is 0.904 μm, respectively.

Option 3: Double glued lens collimation

The first lens has a thickness of 12 mm, and the material is H-QK3L. The second lens has a thickness of 6 mm and the material is SF5. The distance between the light source and the lens is 60 mm, and the RMS value of the emission light is 0.998 μm.

Figures 5(a)-5(f) shows the optical path and spot of the three designs, respectively.

Fig. 5 The comparison of three design patterns for instrument transmitter, and (a) single lens collimation optical path, (b) single lens collimation spot, (c) Double lens collimation optical path, (d) Double lens collimation spot, (e) Double glued lens collimation optical path, and (f) Double glued lens collimation spot, respectively. RMS RADIUS (μm) means dispersion radius, and GEO RADIUS (μm) (geometric radius) represents the actual geometric radius, respectively.

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As far as the distance between the light source and the transmitting lens is concerned, the distance between the light source and the lens is 70 mm, 56.883 mm and 60 mm in the three options, respectively. Therefore, the distance of the Option 2 is shorter, and more light can be hit on the lens for collimation. This reduces the loss of the initial light intensity.

In terms of divergence angle RMS, the three options are 1.062, 0.904 and 0.998 μm respectively. The divergence angle of Option 2 is small, and the error is smaller than that of the Option 1 and 3.Thus, we choose the Option 2 to carry out the optical system design.

The appearance of the instrument structure using Solidworks software (version 2014) design simulation, with rotation, lifting and pitch adjustment function, and taking into account tolerance of weather factors such as the temperature, precipitation and contaminant, structural stability, external appearance beautification and other issues. The system support bar is designed to be hollow and open at the bottom end side for circuit alignment.

3. Results and comparison

The AVTOM is located in the School of Atmospheric Sciences, Nanjing University (32.117° N, 118.954° E), over Nanjing, in southeast China. For comparative experiments, we use OSi OWI-430 visibility meter and CAST3A ultrasonic anemometer for simultaneous observation experiments of visibility and turbulence, respectively. The two instruments are located at School of Environmental science, Nanjing University (32.117° N, 118.952° E) and Nanjing University meteorological mountain (32.118° N, 118.957° E), respectively. The location information of the AVTOM, OSi OWI-430 and CAST3A are shown in the map of Nanjing in Fig. 6. OSI OWI-430 is a forward scattering visibility meter from America. It makes the measurement every 1-min with the measuring range of 1-10000m and the measurement accuracy of 10%-15%. Its working temperature is −40~ + 50°C. CAST3A is a three-dimensional ultrasonic wind speed meter, which is mainly used to measure the wind speed and direction, as well as the horizontal and vertical direction of the turbulent pulse. The measuring path length is 10 cm in vertical direction, and 5.8 cm in horizontal direction.

Fig. 6 The location information of the AVTOM (32.117° N, 118.954° E), OSi OWI-430 (32.117° N, 118.952° E) and CAST3A (32.118° N, 118.957° E)

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The experiment was carried out on July 27, 2017. The weather was overcast and slightly polluted. Figure 7(a) represents the original voltage signal and Fig. 7(b) shows the visibility and $C_{n}^{2}$ measured by the AVTOM at 20:00 - 24:00 of Beijing time. From Fig. 7(b) we can see that the minimum visibility is 4.02km at 22:24 and the maximum is 5.99km at 23:19. Most visibility values are between 4 km and 6 km. $C_{n}^{2}$ is centered mainly between 10⁻¹³ and 10⁻¹²m^-2/3. From Sun, the value of $C_{n}^{2}$ near the ground is generally between 10⁻¹⁴ and 10⁻¹³m^-2/3 [37].

Fig. 7 Original voltage signal (a) and Measurement results (b) of the AVTOM on Jul. 27th, 2017. The red and blue lines represent the measurement results of the visibility and $C_{n}^{2}$ , respectively.

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Figure 8 represents the comparison between the AVTOM and existing instruments. The X coordinate axis represents the measurement time, which starts at 20:00 and ends at 24:00 of Beijing time. The output time interval of Fig. 8(a) is 1 minute, and that of Fig. 8(b) is 30 minutes. The red and blue lines represent the measurement results of the existing instrument and the AVTOM, respectively. From Fig. 8 we can see that the visibility values measured by the AVTOM are centered between 4 km and 6 km and that measured by OSi OWI-430 are around 5km. The comparison indicates that their relative difference is 4.7%. Also, the $C_{n}^{2}$ values measured both by the AVTOM and CAST3A are mainly concentrated between 10⁻¹³-10⁻¹²m^-2/3, and their average of relative difference is 3.5%. In conclusion, we can see that the AVTOM's measurement results are consistent with those of existing instruments.

Fig. 8 The results from comparison between the AVTOM and OSi OWI-430(a) visibility meter, CAST3A ultrasonic anemometer (b). The red and blue lines represent the measurement results of the existing instrument and the AVTOM, respectively.

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Figure 9 presents the measurement results under different air pollution conditions on July 20 and 25, 2017. The Air Quality Index (AQI) of July 20 and 25 is 53 and 92, respectively. As seen in Fig. 9, the pollution level was lower in July 20 than in July 25. And the average, maximum, and minimum values of visibility on July 20 are higher than those on July 25. The average, maximum, and minimum values of $C_{n}^{2}$ on July 20 are greater than those of July 25. These results verify that if the atmospheric turbulence intensity is strong, then the pollutant will spread faster, and the visibility becomes higher, which indicates that our measurement results are consistent with the general law of atmospheric turbulence diffusion. Because the aerosol particles are distributed in the air within the atmospheric turbulence cell, the aerosol particles and air turbulence have the mutual influence. Their simultaneous measurements can help understand their interaction role in of the air pollution dispersion and/or vertical transport due to the air turbulence. It indicates that our newly developed instrument, AVTOM, can measure the two parameters of atmospheric visibility and turbulence intensity at the same time, and this method is able to explore some phenomenon of air pollution diffusion.

Fig. 9 Measurement results of the AVTOM on Jul. 20th, 2017 (a) and on Jul. 25th, 2017(b). The red and blue lines represent the measurement results of the visibility and $C_{n}^{2}$ , respectively. AQI is Air Quality Index and Sd is Standard Deviation.

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4. Calibration and error analysis

4.1. Calibration

At present, most of the transmittance meter calibration utilized the artificial plug-in calibration method [38]. However, this calibration method is difficult to ensure its accuracy, and easily affected by human factors. The calibration has more steps to operate and the maintenance cost is higher. In order to solve these problems, we propose a set of semi-automatic calibration systems that is put outside of the instrument optical transmitter. The calibration device is placed in front of the receiving window. The calibration of visibility is to select three filters with different transmittances to simulate the measurement results under different visibility conditions. The calibration system consists of three plates with different transmission through the calibration lens and a base composition. The transmission of the three calibration plates is manually controlled, a total of 4 stalls, and gear 0 is for the normal working condition. The gears 1, 2 and 3 block the measuring state corresponding to the calibration plates 1, 2 and 3, respectively, in a clockwise direction. When the calibration is finished, the calibration plate is removed. The calibration process requires a calibration value giving by a meteorological observer. Moreover, the calibration inquiry is performed only when the instrument detects higher than the set visibility value. The calibration does not require specialized equipment maintenance personnel. For atmospheric refractive index structure constants, the calibration process is mainly to measure the scintillation index ( $β_{I}^{2}$ ), and then obtain the measured values of $C_{n}^{2}$ . And he measured values of $C_{n}^{2}$ is compared with ensemble mean of statistics. After the calibration is complete, the $C_{n}^{2}$ can be measured in real time. Figure 10 presents the details of the calibration process.

Fig. 10 Working flow chart of AVTOM.

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The calibration experiment was carried out in July 26, 2017 in Nanjing University. Figure 11 shows the results of visibility measured at gear 1(a), gear 2(b) and gear 3(c) in calibration experiments, respectively. We used the three calibration gears, the gear-1 with a filter transmittance = 0.9 from 20:00 to 21:00, gear-2 with a filter transmittance = 0.5 from 21:00 to 22:00, and the geat-3 (filter transmittance = 0.1) from 22:00 to 23:00, respectively. The relative errors are $Δ = 2 %$ at gear 1, $Δ = 1.9 %$ at gear 2, and $Δ = 1.7 %$ at gear 3, respectively. Here $Δ$ is the calibration error (for detail error analysis methods to see section 4.2).

Fig. 11 The visibility measured at the gear 1(a), gear 2(b) and gear 3(c), respectively.

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4.2. Error analysis

For single-baseline transmission measuring instrument, the measurement error can be expressed by the following formula [29]:

\frac{d M O R}{M O R} = - \frac{d T}{T \ln T}

Where $T$ is transmission coefficient. Assume that the relationship between visibility and the measurement baseline is $M O R = k \cdot L$ , where k is the amplification coefficient. According to Bouguer-Lambert's law, $M O R = L \frac{\ln 0.05}{\ln T}$ . Then the relationship between the transmission coefficient T and the amplification coefficient k can be obtained:

T = exp (\frac{\ln 0.05}{k})

According to Eqs. (11) and (12):

\frac{d M O R}{M O R} = - \frac{d T}{\frac{\ln 0.05}{k} exp (\frac{\ln 0.05}{k})}

From Eq. (13) we can see that when $k = - \ln 0.05 \approx 3$ , the relative error of the measurement is the smallest, and when k is smaller or larger, the relative measurement error of the visibility will increase. It shows that when the visibility is 3 times of the baseline length, the error is minimum value.

In the calibration process, the calibration threshold MOR₀ and the stability threshold a are considered to be set. When the calibration is checked to be less than ± 10% of the corresponding standard value, the calibration of the corresponding transmittance point can be considered. In combination, three filters with high, medium and low transmittance of 0.9, 0.5 and 0.1 were chosen as the three light attenuation plates. They are placed in the gear 1, 2, and 3, respectively. Calibration error is:

Δ = (M 1 - M 0) / M 0 < \pm a %

Where, $Δ$ is the calibration error, $M 1$ is the measured value, and $M 0$ is the calibration threshold. After the calibration is completed, according to the error theory, the measurement error is:

Δ M = \frac{1}{(1 + \frac{1}{Δ}) \frac{M 0}{M} - 1}

Where, $M$ is the true value of visibility. We can draw three conclusions from the Eq. (15). First, the greater the true value of the actual visibility when calibrating, the smaller the measurement error is. Second, the smaller the calibration error at calibration, the smaller the measurement error is. Third, the smaller the visibility of the actual measurement, the smaller the measured error is.

5. Conclusion

This study revealed that it is feasible to measure atmospheric visibility and atmospheric turbulence simultaneously. We should pay attention to the interaction between aerosol particles and turbulent air masses. It is very important for the study of atmospheric environmental monitoring, air quality forecast, aerosol-cloud-tubulence interaction, etc..

In this paper, a synchronous measurement system of atmospheric visibility and turbulence intensity is developed, including its theory, design and experiments. This system uses the method of transmission and its transmitter and receiver are set separately. The extinction coefficient and the atmospheric refractive index structure constants can be measured synchronously by using the extinction principle and the light intensity scintillation principle, respectively.

The comparison results shows that the instrument accuracy of visibility is generally less than 1.8%, the relative deviation of visibility range between OSI model visibility meter and this AVTOM is 4.7%. The relative deviation of $C_{n}^{2}$ between CAST3A and this AVTOM is 3.5%, respectively.

The result from the campaign experiment shows that if the atmospheric turbulence intensity is strong, then the pollutant will spread faster, and the visibility becomes higher. Which indicates that our newly developed instrument, the AVTOM, can measure both the atmospheric visibility and turbulence intensity at the same time, and this method is able to explore the phenomenon of air pollution diffusion.

In the current stage, there some insufficient of our AVTOM, for instance, the data processing algorithm is not perfect enough so that data processing results are biased. The limitation of the outfield environment may cause some errors in the measurement of the instrument. The initial prototype is rather heavy, which makes transportation and installation difficult. As the next stage of the work, we will improve the instrument signal extraction algorithm, and improve the mechanical design structure, consider the use of new materials, reduce the weight of the instrument, so that the installation and handling more convenient.

Funding

National Science and Technology Major Project (grant 2016YFC0203303); National Science Foundation of Jiangsu Province (grant BE2015151); National Natural Science Foundation of China (NSFC) (grants 41775026, 41075012, 40805006, and 91544230).

Acknowledgments

Y. Wu is supported by the NOAA-CREST grant # NA16SEC4810008. We thank Dr. Qingeng Wang from School of the Environment, Nanjing University for providing the OSi OWI-430 visibility meter data and Drs. Jun Zhou and Jianning Sun from the School of the Atmospheric Sciences, Nanjing University, for providing the CAST3A ultrasonic anemometer data for us to complete compare with our AVTOM. And we gratefully acknowledged the constructive comments from anonymous reviewers that greatly improve the manuscript.

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Ground-based synchronous optical instrument for measuring atmospheric visibility and turbulence intensity: theories, design and experiments

Abstract

1. Introduction

2. Instrument design and method

2.1 Theories of atmospheric visibility measurement

2.2 Principle of atmospheric turbulence measurement

2.3 Design scheme of the instrument

3. Results and comparison

4. Calibration and error analysis

4.1. Calibration

4.2. Error analysis

5. Conclusion

Funding

Acknowledgments

References and links

Cited By

Figures (11)

Equations (15)

Optics Express