Xiaochun Zhai 19th Coherent Laser Radar Conference

CLRC 2018, June 18 – 21 1

Vertical Velocity Statistics and Turbulence Characterization by

Coherent Doppler Lidar during Typhoon MAWAR

Xiaochun Zhai(a), Songhua Wu(a, b), Xiaoquan Song(a, b)

(a)Ocean Remote Sensing Institute, College of Information Science and Engineering,

Ocean University of China, Qingdao 266100, China.

(b) 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 gives an analysis of CDL investigation of gravity wave and

turbulence characteristics during typhoon MAWAR episode over the coastal zone in

south China (CZSC). The FFT and wavelet analysis are used to subtract the organized

wave-like structure. Radiosonde and ECMWF reanalysis data are used to demonstrate

the existent of gravity wave and to explain its mechanism, respectively. The

up/downdraft of vertical velocity in this case are analysed from different time periods.

A wavelet decomposition technique is used to subtract the gravity wave from raw

vertical velocity datasets, and higher-order moments and characteristic scales are also

analysed base on gravity wave time series. As a result, comprehensive atmospheric

dynamic characteristics and their relationship with gravity wave during MAWAR

episode have been studied.

Keywords: Coherent Doppler lidar, gravity wave, turbulence, typhoon

1. Introduction

The coastal zone in South China (CZSC) is one of the regions with the highest level of economic

development in China. It borders Nanling mountain to the north and South China Sea (SCS) to the south.

Due to its special geographical location, CZSC is one of the areas that most frequently suffer from

marine meteorological disasters such as typhoon, rainstorm and sea fog, and is also one of the key areas

that influence the short-term climate change of China. However, due to the lack of sufficient spatial-

temporal monitoring data, the understanding of the characteristics of land-ocean-atmosphere interaction

and its evolution in this area is not sufficient, and the accuracy of weather prediction and forecast is not

ideal as well. Therefore, there has been a pressing need for carrying out the field experiments to

strengthen the knowledge of atmospheric boundary layer dynamics and thermodynamics processes and

to improve the weather and short-term climate prediction. The Marine Meteorological Science

Experiment Base at Bohe of Maoming (M2SE2B), located at the CZSC, is the fixed observation site for

typhoon research with sophisticated and fully functional equipment. The field experiment was carried

out during August - November 2017 at M2SE2B focusing on the spatial-temporal evolution of

atmospheric boundary layer and air-sea interaction during typhoon landfalling. This paper presents a

case study of the wind field and turbulence observations using coherent Doppler lidar (CDL) during

Typhoon MAWAR episode in this experimental campaign.

2. Lidar technology and methodology

Figure 1 shows the sketch map of experimental location and the outfield the experiment at M2SE2

during August-November 2017. The spatial-temporal evolution of signal-to-noise ratio (SNR) and

vertical velocity are shown in figure 2. In this case study, organized wave-like structure can be seen

from SNR and vertical velocity datasets. The FFT and wavelet analysis are used to subtract the large-

scale coherent signal.

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Xiaochun Zhai 19th Coherent Laser Radar Conference

CLRC 2018, June 18 – 21 2

Figure 1. (a) The experimental location (marked with red star) (b) the outfield experiment at M2SE2B.

Figure 2. Time Height Intensity of (a1)(a2) SNR (dB) and (b1)(b2)vertical velocity (m/s) at 00-08 (a1,b1) and

08-18 (a2, b2) 02 Sep 2017.

Figure 3. (a) FFT spectral power and (b)(c) wavelet analysis of vertical velocity at 02 Sep 2017: 00:00-04:00

from height 1000 m to 2000 m.

Figure 3 (a) shows that the peak frequency of FFT spectral power is about 0.0015Hz, corresponding to

the time period of about 11 min, and an apparent frequency at about 0.0016 Hz using Morlet wavelet

analysis can be seen in figure 3 (b)(c). According to the linear mountain wave theory [1], the waves that

can propagate vertically in the atmosphere can be derived by the use of Scorer parameter 2 2 2/l N U ,where N is the Brunt-Vaisala frequency, and U is the cross-mountain wind speed. Based

on the radiosonde data, a profile of the Scorer parameter is calculated shown in figure 4, a wave with

wavelength and associated wave number 2 /k can propagate in the atmosphere if 2 2k l .

(a) (b)

(a1) (a2)

(b1) (b2)

(a)

(b) (c)

(a) (b) (c) (d) (e)

Xiaochun Zhai 19th Coherent Laser Radar Conference

CLRC 2018, June 18 – 21 3

Figure 4. (a) Richardson number (b) wind shear factor (c) Brunt-Väisälä frequency (d) wind velocity (e) derived

Scorer parameter (blue) and approximate wave number corresponding to observed waves.

The gravity wave production mechanism can be explained in a sense from ECMWF reanalysis dataset

[2]. The cyclone structure of typhoon MAWAR can be seen obviously from figure 5 (a). The

experimental location (cross point in figure 5 (b)) has a negative vorticity, which is under the control of

a surface high-pressure system (anti-cyclone). The descending motion outside of typhoon can easily

result in large-area inverse layer. As a result, the continuously northly wind shown in figure 5 (a) induces

the gravity wave, and the relative stationary atmosphere affected by the descending motion outside of

typhoon MAWAR may the main cause that the gravity wave can exist at long time period and large

spatial area.

Figure 5. Synoptic conditions derived from the ECMWF ERA Interim reanalysis at 00:00 (a) Wind vectors and

temperature (b) vorticity distribution.

3. Results

In order to understand this complex field of atmospheric physics, more updraft and downdraft field

observations are required [3]. Figure 6 shows the up/downdraft statistics from 08-18 LST 02 Sep 2017.

A lifting aerosol layer can be seen in figure 2 (b), and the vertical velocity near the ground has a distinct

difference compared with the ones above. Form the updraft/downdraft statistics shown in figure 6, there

also exists obvious difference below 500 m and above 500 m. The organized updraft and downdraft

between 500 m and 2000 m in figure 2 (b) corresponds to relative constant occurrence, duration and

mean vertical velocity shown in figure 6.

Figure 6. (a) Frequency of occurrence (b) duration (c) fractional coverage (d) mean vertical velocity of

downdraft and updraft from height of 100 m to 2500 m during 08-18 LST 02 Sep 2017.

The vertical velocity can be divided into three parts: mean vertical velocity w , wave structure °w and

fine-scale turbulence 'w in this study where the gravity wave is the larger-scale turbulence. A wavelet

multiresolution analysis technique is used to decompose the fine-scale turbulence signal and large-scale

coherent signal, that is, the gravity wave structure [4]. Figure 7 (a) shows the vertical velocity time series

at different iteration process. An example of wavelet decomposition of vertical velocity is shown in

figure 7 (b). It is decomposed into (middle) wave and (down) turbulence fluctuation part, respectively.

(a) (b)

(a) (b)

(c) (d)

Xiaochun Zhai 19th Coherent Laser Radar Conference

CLRC 2018, June 18 – 21 4

Figure 7. (a) Vertical velocity time series at different iteration process. (b) An example of wavelet decomposition

of w wind component of lidar at height of 1000 m at 2017-09-02: 00:00-04:00.

The turbulence characteristic from vertical velocity can be divided into mainly two parts in the present

studies. The first one is its higher-order moments, including variance, skewness and kurtosis,

respectively [5]. The second is the characteristic time length scales. The contribution of °w to total

turbulence is much larger than 'w ’s. Figure 8 shows the °w turbulence statistics. Larger values of

variance shown in figure 8 (a) appear at lower altitudes, which are consistent with the previous analysis.

Since the time series of horizontal wind profile are unavailable in this study, the corresponding length

scale cannot be obtained, but /Lw wT T equals to /w wL at the same height, shown in figure 8 (f) can

be analyzed.

Figure 8. (a) Vertical velocity variance (b) skewness (c) kurtosis-3 (d) peak frequency time (e) integral time

scale (f) the ratio of peak frequency scale and integral scale at 00-24 02 Sep 2017.

4. Conclusions

Various atmospheric dynamic processes based on CDL zenith pointing mode have been observed during

this experimental campaign, including different atmospheric boundary layer type, the cloud and aerosol

layer effect on vertical velocity and turbulence and so forth. This paper focus on a case study during

Typhoon MAWAR episode. Organized wave-like structures can be seen from CDL detection. We

analyze this case using radiosonde and ECMWF reanalysis data to demonstrate that the large-scale

coherent structure is gravity wave. The FFT and Morlet wavelet analysis are used to subtract this

structure, corresponding to about 11-min period. The topography effect and the resulting subsidence

caused by typhoon may be the cause of long-time period existence of gravity wave structure. The

up/downdraft features are specifically analyzed and found that there are significant differences below

and above 500 m, and it may result from more composite effect of solar radiation at daytime and wind

shear below 500 m. The wavelet decomposition technique is used to exactly separate gravity wave and

fine-scale turbulence component. The gravity wave is specially analyzed based on higher-order

moments and characteristic scale retrieval procedure. The relationship between gravity wave and

different turbulence features will be analyzed in further study.

5. References

[1] Durran, D. R.: Mountain waves and downslope winds, in: Atmospheric Process over Complex Terrain,

edited by: Blumen, W.,American Meteorological Society, Boston, 59–81, 1990

(a) (b)

(a) (b) (c) (d) (e) (f)

Xiaochun Zhai 19th Coherent Laser Radar Conference

CLRC 2018, June 18 – 21 5

[2] Chouza Keil, Fernando, et al. "Vertical wind retrieved by airborne lidar and analysis of island induced

gravity waves in combination with numerical models and in situ particle measurements." Atmospheric

Chemistry and Physics (ACP)16.7 (2016): 4675-4692

[3] Ansmann, Albert, Julia Fruntke, and Ronny Engelmann. "Updraft and downdraft characterization with

Doppler lidar: cloud-free versus cumuli-topped mixed layer." Atmospheric Chemistry and Physics 10.16 (2010):

7845-7858.

[4] Wang, Yansen, et al. "Investigation of nocturnal low-level jet–generated gravity waves over Oklahoma City

during morning boundary layer transition period using Doppler wind lidar data." Journal of Applied Remote

Sensing 7.1 (2013): 073487.

[5] Lenschow, Donald H., Volker Wulfmeyer, and Christoph Senff. "Measuring second-through fourth-order

moments in noisy data." Journal of Atmospheric and Oceanic Technology 17.10 (2000): 1330-1347.