Xiaoying Liu et al. 19th Coherent Laser Radar Conference

CLRC 2018, June 18 – 21 1

Comparison of wind measurements between virtual tower and

VAD methods with different elevation angles

Xiaoying Liu1, Songhua Wu1，2*, Hongwei Zhang1, Qichao Wang1, Xiaochun Zhai1

1 Ocean Remote Sensing Institute, College of Information Science and Engineering,

Ocean University of China, Qingdao 266100, China.

2 Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National

Laboratory for Marine Science and Technology, Qingdao 266100, China.

*Email: wush@ouc.edu.cn

Abstract: This paper compares wind retrieval methods of VT (Virtual Tower) mode

and VAD (Velocity-Azimuth Display) with different scanning elevation angles. The

field experiment was performed from September 23 to October 13 2017 at the campus

of Ocean University of China under various weather conditions. A total of seven lidars

were involved in the experiment. Three lidars carried out the staring mode to constitute

the VT. The other four lidars were concurrently operating PPI scanning at different

elevation angles, corresponding to different spatial average volume. The results of wind

speed and direction from VT and VAD shows good correlation when lidars are well

synchronized. The influence of spatial homogeneity on wind retrieval is also described

in this paper.

Keywords: Lidar, Virtual Tower, VAD, Volume Average

1. Introduction

Accurate wind field information can be used to explore the subtle structure of complex wind flow,

meanwhile, it can also provide the possibility to comprehend the underlying physical mechanisms and

to optimize wind field models [1]. The single-lidar commonly uses the Doppler beam swinging (DBS)

strategy and the velocity azimuth display (VAD) technique to obtain high accuracy [2-4]. Both of these

methods are based on spatial horizontal homogeneity assumption, which is often invalid in complex

wind field [5-6]. In response to this question, two or more additional lidars are used to obtain a three-

dimensional wind field by spatiotemporal synchronization scanning, which can be called virtual tower

(VT) [7-8]. In order to demonstrate the feasibility and accuracy of VT, the comparison between DBS

mode and VT are studied in [6, 8], and the VT and sonic anemometer also show good agreement in [1,

9]. This paper introduces the results of VT and VAD mode with different scanning elevation angles.

2. Experiments

The field experiment was performed from September 23 to October 13 2017 at the campus of Ocean

University of China. As shown in Figure 1, a total of seven coherent Doppler lidars were involved in

the experiment. Three lidars (VT1, VT2 and VT3 in the Figure 1 (a) and (b)) constituted the virtual

tower by carrying out the staring mode. They were located on the north, east and south of the playground

respectively to meet the requirements that three lidar beams should be intersecting and non-coplanar

[10]. The other four lidars (as shown in Figure1 (a) and (b), the VAD1, VAD2, VAD3 and VAD4) were

concurrently operating PPI scanning at different elevation angles, corresponding to different spatial

average volume. Four lidars on VAD mode were all placed on the west side of the playground and each

of two adjacent lidars is spaced one meter apart.

During the experiment, three lidars of VT simultaneously stared at the six points (50 m to 300 m with

50 m increments) above the VAD2 (see in Figure 1(b)). The distance of these three lidars to VAD2 were

all 98m, which were approximately the same. This ensured that they had the same elevation angle when

measuring the same height. The three lidar beams are continuously observed for 1 min at each height at

the sampling rate of 0.5Hz, which can capture the rapid atmospheric process while ensuring the high

temporal resolution as much as possible. The other four lidars on VAD mode scanned at the speed of 6

degrees per second for full-cycle PPI scan. Therefore, it took 1 minute to obtain a wind profile. The

experimental parameters of seven lidars are shown in Table 1.

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Xiaoying Liu et al. 19th Coherent Laser Radar Conference

CLRC 2018, June 18 – 21 2

Figure 1. Schematic of experimental configuration. (a) Seven lidars’ location on the playground.

(b)The virtual tower stare scan and four full-cycle PPI scan with different elevation angles.

Table 1. Experimental observation parameters of seven lidars

Lidar Code Retrieval

Methods Azimuth(°)

Elevation(°)

50 m 100 m 150 m 200 m 250 m 300 m

VT1

VT

226.39 26.8 45.3 56.6 63.7 68.4 71.8

VT2 270.55 26.9 45.4 56.7 63.7 68.5 71.8

VT3 338.41 26.9 45.5 56.7 63.8 68.5 71.8

VAD1

VAD 0~360

50

VAD2 60

VAD3 35.3

VAD4 70

3. Methodology

Lidar measures the movement of aerosol particles in the atmosphere to obtain a line-of-sight (LOS)

velocity (or radial velocity). The LOS velocity is a projection of the wind field in the pointing direction

of the laser beam, so the horizontal and vertical velocity can be retrieved from the LOS velocity by

Eq.(1).

sin cos cos cos sinrV u v w (1)

where rV is the LOS velocity, u , v , w are the zonal velocity, the meridional velocity, and the vertical

velocity, respectively. And , are the azimuth and elevation angles, respectively.

In order to retrieve the three components of the wind field, two additional equations are needed.

Therefore, the three radial velocities from three lidars of the virtual tower can form a set of wind vector

equations. In Eq. (2), the terms on the left–hand side are the radial velocity measurements of the VT1,

VT2 and VT3, which can be represented by Vr. The right-hand side includes the geometrical

information in the matrix M and the velocity vector in meteorological coordinates V [10]. So the

relationships among these three vector matrix can be written as Eq. (3). And the vector V is our

concerned actual wind information.

(a) (b)

Xiaoying Liu et al. 19th Coherent Laser Radar Conference

CLRC 2018, June 18 – 21 3

1 1 1 1 1 1

2 2 2 2 2 2

3 3 3 3 3 3

sin cos cos cos sin

sin cos cos cos sin

sin cos cos cos sin

r

r

r

V U

V V

V W

(2)

𝐕 = 𝐌-1Vr (3)

4. Analysis and Results

The single lidar measurements need to consider the difference between scalar and vector average when

compared to the point measurements. The analysis of averaged wind vector need to average these

components over a period of time e.g.10 min by scalar averaging and vector averaging. The magnitude

of the vector is different from the scalar, and the ratio between them and the standard deviation of the

wind direction follow the law of the Bessel function as seen in Figure 2 (a). The ratio of vector to scalar

average can be written in Eq. (4) [11], where vectorV and

scalarV are the vector average and the scalar

average respectively, and is standard deviation of the wind direction in the interval time.

sin 3Ratio

3

vector

scalar

V

V (4)

Figure 2. The Bessel function of the ratio of vector to scalar average with the standard deviation of the

wind direction. (a) The results of theoretical analysis. (b) The results of experimental data with VT

and VAD (The interval time is 10 min).

Analysis of VAD data (volume measurements) can be well fitted to Bessel function. VT is not point

measurements in the strict sense with a certain measurement volume and is sensitive to wind direction.

It is also possible to calculate the vector and scale average in the interval time. And the results of VT

are also fitted to the function well. The following analysis are all based on the vector average of VT and

VAD.

The comparison of horizontal velocity and direction between VT and VAD are shown in Figure 3. The

data came from the observations made on September 27 and 28, 2017. The scanning elevation angle of

the VAD used in the comparison is 60°. As seen from the Figure 3, the results of wind speed and

direction from VT and VAD shows good correlation. The correlation coefficient (R) are the 0.93 and

0.99 in the velocity and direction, respectively. The standard deviation of 0.78 m/s and 3.8° are all in

the reasonable range. Figure 4 shows the time series of horizontal velocity of VT and VAD at four

elevation angles. The absence of data in the plot is due to quality control based on time synchronization

criteria. The wind speed of VT and VAD show a consistent changing trend over time. When the wind

speed is lower, the wind magnitude of VT and VAD are roughly equivalent. As the wind speed continues

to increase, the speed of VT is significantly higher than that of VAD and the fluctuations also increase.

(a) (b)

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CLRC 2018, June 18 – 21 4

Figure 3. Comparison of the (a) horizontal velocity and (b) horizontal direction from the VT technique

with the measurements made by VAD technique.

Figure 4. Time series of horizontal velocity of VT and VAD with four elevation angles, as shown (a)

35.3°, (b) 50°, (c) 60° and (d) 70° at 250 m on September 30, 2018. The shaded portion in the figure

represents the fluctuation of wind speed.

Compared with the cup anemometer, lidar measures the wind with a volume average around a given

height [11]. Lidar has an effective probe length corresponding to a finite height resolution and elevation

angle. In this experiment, the radial resolution is 30m, and the elevation angles is different as seen in

Table 1. Figure 5 shows the result of average volume, where the ratio is the wind speed of volume

average around a given height to the speed of the given height. According to the figure, the larger

elevation angle and the lower height have the smaller ratio, which means the more significant influence

of volume average.

(a) (b)

(a)

(b)

(c)

(d)

Xiaoying Liu et al. 19th Coherent Laser Radar Conference

CLRC 2018, June 18 – 21 5

Figure 5. The ratio of volume average wind speed around a given height to the speed of the given

height.

It is worth to noting that these ratios are all above 0.95. From the perspective of theoretical analysis, the

effect of the volume average on wind speed is not obvious at different elevation angles with the 30 m

radial resolution.

5. Conclusions

This paper introduces the synchronous observation experiments of seven lidars. The comparison

between VT and VAD shows good agreement. The volume average effect is also analyzed theoretically.

In the next work, it is also necessary to analyze the influence on the actual wind field with measurement

data. The time series analysis indicates that VT and VAD have the same tendency.

6. Acknowledgement

This work was supported by National Natural Science Foundation of China (No.41471309) and the

National Key Research and Development Program of China (016YFC1400904). The authors wish to

thank Fanghan Wang for valuable discussion.

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