Post on 09-May-2020
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.