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Comprehensive Radar Observations of Clouds and Precipitation
over the Tibetan Plateau and Preliminary Analysis of Cloud
Properties
LIU Liping1∗ (
), WU Songhua
HU Zhiqun1 (
), RUAN Zheng ( Æ), CUI Zhehu (Û ),
), DAI Guangyao (འ), and WU Yahao ( )
), ZHENG Jiafeng1,2 (
3
(
1
3
1
2
1 State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081
2 Nanjing University of Information Science & Technology, Nanjing 210044
3 Ocean University of China, Qingdao 266100
(Received September 8, 2014; in final form April 20, 2015)
ABSTRACT
Intensive field experiment is an important approach to obtain microphysical information about clouds and
precipitation. From 1 July to 31 August 2014, the third Tibetan Plateau Atmospheric Science Experiment
was carried out and comprehensive measurements of water vapor, clouds, and precipitation were conducted
at Naqu. The most advanced radars in China, such as Ka-band millimeter-wave cloud radar, Ku-band
micro-rain radar, C-band continuous-wave radar and lidar, and microwave radiometer and disdrometer were
deployed to observe high spatial-temporal vertical structures of clouds and precipitation. The C-band duallinear polarization radar was coordinated with the China new generation weather radar to constitute a dualDoppler radar system for the measurements of three-dimensional wind fields within convective precipitations
and the structure and evolution of hydrometeors related to precipitation process. Based on the radar
measurements in this experiment, the diurnal variations of several important cloud properties were analyzed,
including cloud top and base, cloud depth, cloud cover, number of cloud layers, and their vertical structures
during summertime over Naqu. The features of reflectivity, velocity, and depolarization ratio for different
types of clouds observed by cloud radar are discussed. The results indicate that the cloud properties were
successfully measured by using various radars in this field experiment. During the summertime over Naqu,
most of the clouds were located above 6 km and below 4 km above ground level. Statistical analysis shows
that total amounts of clouds, the top of high-level clouds, and cloud depth, all demonstrated a distinct
diurnal variation. Few clouds formed at 1000 LST (local standard time), whereas large amounts of clouds
formed at 2000 LST. Newly formed cumulus and stratus clouds were often found at 3-km height, where there
existed significant updrafts. Deep convection reached up to 16.5 km (21 km above the mean sea level), and
updrafts and downdrafts coexisted in the convective system. Supercooled water might exist in such kinds of
deep convective system. The above measurements and preliminary analysis provide a basis for further study
of cloud physics and precipitation process over the Tibetan Plateau. These observations are also valuable
for modeling studies of cloud and precipitation physics as well as in the development of parameterization
schemes in numerical prediction models.
Key words: the Tibetan Plateau, cloud characteristics, cloud radar
Citation: Liu Liping, Zheng Jiafeng, Ruan Zheng, et al., 2015: Comprehensive radar observations of clouds
and precipitation over the Tibetan Plateau and preliminary analysis of cloud properties. J. Meteor. Res., 29(4), 546–561, doi: 10.1007/s13351-015-4208-6.
1. Introduction
The Tibetan Plateau (TP) in China’s southwestern region is the highest plateau with the most com-
plex terrain in the world. It covers one-fourth of the
total territory of China. The average elevation of the
TP reaches up to the mid troposphere. For this reason, it is also called “the Roof of the World”. By its
Supported by the China Meteorological Administration Special Public Welfare Research Fund (GYHY201406001), National
Key Basic Research and Development (973) Program of China (2012CB417202), and National Natural Science Foundation of China
(91337103 and 41175038).
∗ Corresponding author: [email protected].
©The Chinese Meteorological Society and Springer-Verlag Berlin Heidelberg 2015
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LIU Liping, ZHENG Jiafeng, RUAN Zheng, et al.
thermal-dynamical forcing, the TP significantly affects
the atmospheric circulation, the surface-atmosphere
momentum exchange, and the hydrologic cycle in its
surrounding areas as well as in eastern China. Clouds
and precipitation in the TP impose great impacts on
the atmospheric moisture transport and surface heating. Under certain favorable synoptic conditions, various weather systems above the TP can move out of
the plateau, leading to disastrous weather such as rainstorms in the downstream region. Cloud and microphysics processes above the TP are often different from
those in low altitude areas. Due to the strong surface
heating, factors that suppress the development of convection often disappear quickly after the noon in the
TP. As a result, convective cloud is easy to develop.
Convective processes are more frequently triggered in
the TP than in the downstream plain areas. However,
convective available potential energy (CAPE) is often
small because of the low moisture content in the atmosphere above the plateau. The top of the cumulus
clouds and that of the strong echoes from the radar are
both low due to the small CAPE and low atmospheric
moisture content above the TP. The horizontal scale
of the convective system is often limited, too.
Due to the relatively rare field experiments and
observations of clouds and precipitation in the TP, our
understanding of the microphysical processes in clouds
and precipitation over the plateau is still very limited.
Large uncertainties exist in various numerical modeling studies of cloud physics over the TP, and some critical parameters that are used to describe cloud physics
and precipitation process are probably not appropriate for the TP. As a result, most of the present numerical models cannot reasonably simulate the cloud
microphysics processes over the TP, resulting in large
biases in cloud radiative forcing and precipitation simulation. The above factors significantly deteriorate the
capability of numerical models in their simulation and
forecast of the cloud physics and precipitation. In addition, weather stations are scarce in the heartland of
the TP while from central to western Tibet are large
uninhabited regions. Satellite measurements have become a necessity to obtain high-density observations
over the TP. However, satellite measurements must be
547
continuously calibrated by using surface observations.
The lack of ground observations in the TP remains a
major bottleneck affecting the calibration and quality
control of satellite data. Therefore, it is imperative
to conduct comprehensive observations of clouds and
precipitation over the TP.
During the first TP Atmospheric Science Experiment conducted in 1979, scientists have already recognized the importance of precipitation observation.
Two conventional X-band 711 type radars were set up
in Naqu, central TP, and Lasa (southern plateau) to
measure precipitation. Based on the observations obtained during the experiment, Qin (1983) analyzed the
statistical characteristics of cumulus clouds in Naqu
and revealed the relationship between vertical distribution of moist static energy and convective development. In 1998, China Meteorological Administration
and Chinese Academy of Sciences jointly launched the
second TP Atmospheric Science Experiment. Scientists from China and Japan collaborated on measurements and studies of the energy and water cycles over
Naqu region in the TP (GAME-TIBET). The X-band
Doppler radar from Japan, rain gauges, and radiosondes were deployed to collect comprehensive information about precipitation process in this region. Based
on these measurements, characteristics of radar echoes
from convective precipitation were analyzed; changes
in the convective process before and after the monsoon onset and the diurnal variation of convection were
explored. Precipitation structures by ground-based
radar and TRMM (Tropical Rainfall Measuring Mission) precipitation radar were compared (Liu et al.,
1999, 2002; Shimizu et al., 2001; Uyeda et al., 2001;
Liu, 2003; Fu et al., 2006; Zhuang et al., 2013).
Satellite measurement is always an important approach for meteorological studies over the vast TP.
Based on satellite measurements, TRMM precipitation radar observations, and cloud radar and lidar
measurements from Cloudsat, many previous studies
have analyzed the typical cloud structures related to
deep convective precipitation in the TP. These studies revealed the statistical characteristics of convective
precipitation in the plateau. Differences in characteristic cumulus clouds between the TP and other regions
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of East Asia have also been discussed. It is found that
the deep convection developed over the TP usually remains weak with a feature of small horizontal scale
due to the relatively dry environment and low CAPE
(Fu et al., 2007; Li et al., 2009; Dai et al., 2011; Wang
et al., 2011; Li et al., 2012; Cai et al., 2012). The
microphysical structures of stratus clouds formed over
Qinghai and the eastern TP region have also been analyzed based on in-situ aircraft and radar observations
(Li and De Ligeer, 2001; Zhao et al., 2002; Liu et al.,
2008)
China Meteorological Administration has set up
a new generation weather radar system in the TP for
operational measurement of various precipitation processes. Unfortunately, the observations for precipitation are far less than satisfactory due to the topographic beam blocking. It is well known that weather
radars (S-band, C-band, and X-band weather radars)
are mainly employed to obtain the three-dimensional
structure of precipitation echoes, whereas their capability for cloud observation is very limited. Millimeterwavelength cloud radar and lidar are two primary tools
for cloud observations.
Based on the above discussion, weather radars
have been applied for precipitation observation over
the TP (Zhuang and Liu, 2012) while satellite remote
sensing has been used for cloud observation. However,
little observation has been done in comprehensive and
continuous measurements of microphysical parameters
in the cloud physics using various active remote sensing technologies over the TP. Due to the lack of cloud
observations, little research has been done on microphysical processes within cumulus clouds over the TP,
and appropriate determination of the important parameters in the cloud physics still remains a question
that has not been answered yet. So far, our knowledge about cloud physics over the TP is very limited.
Meanwhile, new cloud observation technology such as
millimeter-wavelength cloud radar has been applied in
field experiments conducted in Guangdong and Yunnan provinces. The data analysis method has been
developed by Liu et al. (2014) specifically to process cloud radar observations. The study by Liu et
al. (2014) provides a solid basis to retrieve important
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cloud physics parameters for cumulus clouds over the
TP, which is important for the scientific community
to better understand the temporal-spatial variation
of clouds and precipitation over the TP, and further
investigate the cloud physics and precipitation process. For this purpose, the reanalysis dataset based on
multiband radar observations has been produced and
applied for the development of cloud physics schemes
and retrieval of parameters.
In the third TP Atmospheric Science Experiment
in 2014, intensive observations were conducted from
1 July to 31 August 2014. Various vertically pointing radars, lidars, and dual-polarization radars were
combined with passive remote sensing techniques to
measure atmospheric water vapor, clouds, and precipitation during this intensive observation period. The
millimeter-wavelength radar, C-band frequency modulation and continuous wave (FMCW) radar, and Cband dual-linear polarization radar, which represent
the most advanced atmospheric observation technique
and have been developed independently in China,
were utilized to obtain first-hand field measurements.
These measurements are valuable for cloud and precipitation studies in the TP.
In this paper, the instruments used in cloud and
precipitation observation in this experiment are introduced. The observational data obtained in this experiment are described. Based on the cloud radar measurements, we analyze the statistical characteristics of
clouds (cloud top and base, cloud depth, vertical distribution of clouds, etc.) in the summer over Naqu
region. The radar echo structures of several types of
typical clouds over the plateau are revealed and interesting results are provided.
2. Instruments and measurements in the field
experiment
The field experiment on clouds and precipitation
is an effective approach that can help address the following scientific questions: (1) proposing a method to
conduct comprehensive cloud and precipitation measurements using various radars; (2) providing quality
control algorithms for observations; and (3) developing
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LIU Liping, ZHENG Jiafeng, RUAN Zheng, et al.
a method to retrieve cloud dynamical and microphysical parameters. The purpose of this study is to further understand the microphysical processes involved
in clouds and precipitation and their spatial-temporal
variations. Multi-wavelength active remote sensing
and passive remote sensing techniques are combined
to obtain both micro- and macro-structures of atmospheric water vapor, clouds, and precipitation over
the TP, which form the basis for the development of
retrieval method for cloud and precipitation microphysics. Data obtained in this experiment will help to
reveal the microphysical processes in clouds and precipitation over the TP, and provide evidence for correction and calibration of satellite remote sensing observations. These observations are also valuable in modeling studies of cloud and precipitation physics as well
as in the development of parameterization schemes in
numerical prediction models.
Most of the previous field experiments only used
Doppler weather radar for the measurement of precipitation system. Neither the hydrometeor phase distribution in precipitation system nor the cloud process could be measured in these experiments. In the
field experiment of the present study, various advanced
multiple wavelength radar systems are utilized to obtain not only the macro-feature of precipitation echoes,
but also the three-dimensional wind fields, phases of
precipitation particles, and raindrop size distribution.
The millimeter-wavelength radars are applied in this
study for continuous measurements of the vertical
structure of clouds, which can be retrieved to obtain
the vertical profiles of microphysical and dynamical
cloud parameters. These results are important for further studies of cloud physics over the TP.
2.1 Measurement instruments
The measurement instruments, location, and observational periods are given in Table 1. The exteriors
of the instruments are shown in Fig. 1. Major technical specifications of the instruments are listed in Table
2.
The Ka-band solid-state transmitter-based millimeter wave vertically pointing cloud radar was used
for continuous (uninterrupted) cloud measurements.
The reflectivity, radial velocity, velocity spectrum
width, and linear depolarization ratio were obtained.
Meanwhile, power spectral density data were selected
for further analysis. C-band frequency modulated continuous wave (FMCW) vertically pointing radar system is the first frequency modulated continuous wave
radar system used in China for cloud and precipitation
observations. It utilizes continuous wave, all-phaseparameter Doppler radar to measure the reflectivity,
radial velocity, and velocity spectrum width of cloud
and precipitation at various levels with a vertical resolution of 15–30 m. Ka-band micro-rain radar manufactured in German is used to measure the reflectivity
of clouds and weak precipitation and power spectrum,
Table 1. Measurement instruments, locations, and periods
Classification
Vertically pointing
instruments for
water vapor,
clouds, and
precipitation
observation
Measurement of three-dimensional
structure of precipitation
Name
Quantity
Microwave radiometer
Water vapor and cloud lidar
Ceilometer
Cloud radar
Micro-rain radar
1
1
1
1
1
Observation
location
NQMET
NQMET
NQMET
NQMET
NQMET
Disdrometer
C-band frequency
modulated continuous
wave (FMCW) radar
Disdrometerr
China new generation weather radar
C-band dual-linear polarization radar
1
NQMET
1
NQZX
1 July–31 August
1
1
1
NQZX
NQMET
NQBJ
1 July–31 August
1 July–31 August
1 July–31 August
1
9
9
1
1
Observation
period
July–31 August
July–31 August
July–31 August
July–31 August
1–11 July
11–31 August
July–31 August
Note: NQMET: Naqu Bureau of Meteorology; NQZX: Naqu Zhongxin Hotel; NQBJ: Naqu Climate–Environment Observation
Station.
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Table 2. Major technical parameters of the cloud radar, continuous wave radar, and C-band dual-linear polarization
radar
Order
Index entry
1
Working system
2
3
4
5
6
Cloud radar
Pulsed wave Doppler,
solid state transmitter,
pulse compression,
vertical measurement
Frequency
33.44 GHz (Ka-band)
Measured variables Reflectivity, radial velocity,
velocity spectrum width,
linear depolarization factor,
power spectral density data
Detection range
C-band dual-linear
polarization radar
Persistent wave form,
Pulsed wave Doppler,
vertical measurement
dual polarization radar
utilizing two transmitters
and two receivers
5530±3 MHz
C-band
Reflectivity, radial
Reflectivity, radial velocity,
velocity, velocity spectrum
velocity spectrum width,
width, linear depolarization
differential reflectivity factor,
factor, power spectral
phase shift, correlation
density data
coefficient between horizontal
and vertical signals
0.2–15 km (vertical direction) 150 km (horizontal
direction)
3 s: a radial observation;
6 min, 9-layer scan, range
resolution 30 m
resolution: 150 m
Continuous wave radar
120 m–15 km
(vertical direction)
Spatial-temporal 8.8 s: a cyclic radial
resolution
observation using
three modes (adjustable); 30 m
Detection accuracy Reflectivity 1 dBZ (RMS);
Reflectivity 1 dBZ (RMS)
Radial velocity 0.2 m s−1 (RMS); Radial velocity 0.2 m s−1
Velocity spectrum width 1 m s−1
(RMS)
Velocity spectrum width
1 m s−1
which are used to retrieve the vertical profiles of raindrop size distribution for precipitation below 6 km
(0.109–6-mm diameters) and total precipitation, etc.
The atmospheric water vapor and clouds lidar used in
this study transmitted three wavelengths (1064, 532,
and 355 nm) to measure and retrieve the mixing ratio
of water vapor, cloud depolarization ratio, cloud base
height, atmospheric extinction coefficient, and atmospheric backscatter coefficient profile. The maximum
detection range of the system is 20 km, the range for
water vapor mixing ratio is 0.2–5.0, and 0.2–15.0 km
for cloud base and cloud depolarization ratio. These
vertically pointing radars and lidars with three different wavelengths constitute the comprehensive observing system for measurements of clouds and precipitation with various intensities and at their different
developing stages.
The portable C-band dual-linear polarization
radar operates with polarization base of simultaneous transmissions of horizontal and vertical radar wave
with simultaneous reception using dual receivers to obtain the reflectivity, radial velocity, velocity spectrum
width, differential reflectivity, differential phase, copolar correlation coefficient, etc. During the period of the
Reflectivity 1 dBZ (RMS)
Radial velocity 1 m s−1
(RMS)
Velocity spectrum width
1 m s−1
field experiment, the radar scanned 9 elevation tilts
once every 5 min. Together with the China new generation C-band weather radar operated in Naqu Bureau of Meteorology, they constitute the dual-Doppler
radar observation system.
In order to detect the characteristics of raindrop size distribution, and verify the accuracy of raindrop size distribution retrieved from radar observation, measurement of surface raindrop size distribution was conducted in this experiment using the HSCPS32 disdrometer. The HSC-PS32 disdrometer can
detect liquid and solid particles. Diameters of liquid
particles that can be detected are within 0.2–5.0 mm,
while the diameters of solid particles are within 0.2–
25.0 mm. To coordinate with the retrieval of cloud water content from the vertically pointing radar measurements, microwave radiometer was used in this study.
An MP-3000A 35-channel microwave radiometer made
by U.S. Radiometrics Corp. was deployed. It can produce high-resolution temperature, relative humidity,
and water vapor profiles from the surface to 10-km
height. It also produces low-resolution liquid water
profiles and relatively accurate total liquid water content.
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Fig. 1. The main instruments used in the experiment. (a) Ka-band cloud radar, (b) C-band frequency modulation and
persistent wave (FMCW) radar, (c) C-band mobile polarization radar, (d) vapor and cloud observation lidar, and (e)
Ku-band micro-rain radar.
2.2 Location and periods of experiment
The site for cloud and precipitation observation is
located in Naqu of TP. This site is selected mainly because Naqu is the major area of the TP vortex genesis,
where convective processes develop frequently, making it an ideal location for clouds and precipitation observation. The vertical measurements of cloud properties were conducted at Naqu Bureau of Meteorology (NQMET, 31.48◦ N, 92.01◦ E, 4507 m AGL (above
ground level)). The C-band dual-linear polarization
radar is installed at Naqu Climate-Environment Observation Station, Cold and Arid Region Environmental and Engineering Research Institute, Chinese
Academy of Sciences (NQBJ, 31.37◦ N, 91.90◦ E, 4509
m AGL). However, during the observational period,
the C-band continuous wave radar interfered with
the China new generation weather radar installed at
NQMET. For this reason, the C-band continuous wave
radar and a disdrometer were set up at Naqu Zhongxin
Hotel (NQZX, 31.29◦ N, 92.03◦ E, 4507 m AGL) for observation. The distance between NQZX and NQMET
is about 2 km, and the intensive observation period is
from 1 July to 31 August 2014.
2.3 Measurements
When the intensive observation started on 1 July,
most of the instruments worked properly, and contin-
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uous measurements of cloud evolution were obtained.
In particular, continuous measurements have been
conducted by the cloud radar and C-band continuous wave radar since both radars use solid-state transmitters, which ensures the reliability and stability
of the radar operation. However, the operation of
some instruments became unstable due to the influ-
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ence of the high elevation. For example, the microwave
radiometer could not provide satisfactory measurements. Table 3 lists the instruments and the variables
they can observe. The spatial-temporal resolution, the
total amount of data, and the major weather processes
involved during the observation period are also given
in Table 3.
Table 3. Raw measurements, spatial-temporal resolution, total amount of data, and weather processes involved
during the observation period
Resolution
Amount
of data
50–250 m, 2-min
interval
88.5 MB
3.75 m, 16 s
112 GB
Cloud top and base
5 m, 16 s
694 GB
Cloud radar
Reflectivity, radial
velocity, velocity
spectrum width,
depolarization factor,
power spectral density
data
30 m, 8.8 s
37.9 GB
5
C-band
frequency
modulated
continuous
wave
vertically
pointing
radar system
Reflectivity, radial
velocity, velocity
spectrum width,
depolarization factor,
power spectrum
density data
15, 30 m; 3 s
12 GB
6
Microrain
radar
50–200 m; 1 min
3.44 GB
7
Disdrometer
1 min, raindrop
size distribution,
32-channel
1.5 GB
8
C-band
dual-linear
polarization
radar
0.3 km, 1◦ ; 6 min
65 G
Order
Instrument
1
Microwave
radiometer
2
Water vapor
and cloud
lidar
3
Laser
Ceilometers
4
Measured variable
Temperature,
humidity, liquid water
content, water vapor
density
Water vapor mixing
ratio, cloud base,
linear depolarization
ratio, extinction
coefficient
Reflectivity, raindrop
size distribution,
particle falling speed,
rain rate
Precipitation intensity,
radar reflectivity,
visibility, 32-channel
spectrum data and
falling speed
Reflectivity, radial
velocity, velocity
spectrum width,
depolarization factor,
differential phase
differential
propagation phase
shift, and copolar
correlation coefficient
Major weather process
July
July 5: deep convection;
July 6–7: altostratus and
altocumulus;
July 8–9: deep
convection, altostratus
and altocumulu;
July 10–14: stratus and
cumulus;
July 15: stratus;
July 16–17: altostratus
and cumulus;
July 18–19: cumulus and
deep convection;
July 22: stratocumulus;
July 24–25: stratus;
July 28: deep convection;
July 29–31: stratocululus;
August
Aug. 1: stratus;
Aug. 6: cumulus,
Aug. 7: stratus and
altostratus;
Aug. 20: cumulus;
Aug. 21: deep convection;
Aug. 22: cumulus and
cumulonimbus
Aug. 24: stratus;
Aug. 26: deep convection;
Aug. 28: cumulus and
altocumulus;
Aug. 30–31: stratus and
cumulus.
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3. Statistical characteristics of summer clouds
in the Tibetan Plateau
Continuous evolution of the cloud vertical structures was obtained from cloud radar measurements
during the period of 5 July to 4 August 2014. Based
on the radar measurements during this period, we analyzed the diurnal variation of cloud base and top, cloud
depth, number of cloud layers, and vertical distribution of clouds. Quality control has been performed
first to remove echo interference and noise. The cell
identification-based method was then applied to cloud
classification, while the upper and lower boundaries
of the cloud measured by radar were taken as cloud
top and base respectively. The average cloud top and
base, cloud depth, and number of cloud layers were
then calculated. The results of the statistical analysis
of these variables for the period 5 July to 4 August
and their diurnal variations are analyzed. The diurnal
variations of cloud top and base are shown in Fig. 2.
The height shown in Fig. 2 and hereafter all refer to
the height above the ground level. Figure 2 indicates
that the clouds over the TP are generally classified into
high clouds (with cloud top above 6 km), and mid- to
low-level clouds with a top below 4 km. Few clouds
with a cloud top of above 5 km are found. The top of
high-level clouds above 6 km demonstrates a distinct
Fig. 2. Diurnal variations of cloud top and base during 5
July–4 August 2014.
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diurnal variation. It reaches the highest level during
1600–2000 BT (Beijing time), and becomes the lowest
during 0800–1200 BT. In contrast, no distinct diurnal
variation can be found for the top of mid- to low-level
clouds. Further analysis indicates that altostratus and
altocumulus clouds account for parts of the high clouds
after the deep convection dissipates, while the mid- to
low-level clouds include developing cumulus and stratocumulus clouds.
In order to further analyze the cloud distribution
at different altitudes, we analyzed the occurrence frequency of cloud at various altitudes. The occurrence
frequency of cloud at a specific layer is defined by
the ratio of the number of radar beams with significant cloud detection at the altitude to total number
of radar beams. Note that the occurrence frequency of
cloud defined here is closely related to the minimum
reflectivity radar observed. Under the same condition, the occurrence frequency of cloud decreases with
height because the minimum reflectivity increases with
height. Figure 3 presents the diurnal variation of the
occurrence frequency of cloud at 1-h interval and 1km interval at different vertical levels. It is found that
clouds over the TP largely distribute below 10 km, and
the occurrence frequency of cloud above 10 km is less
than 10%. The vertical distribution of clouds is clearly
stratified. Few clouds are found at 5-km height, while
large amounts of clouds concentrate at levels of 2–4
and 6–9 km. Clouds rapidly develop at levels above
5 km after the noon, especially during 1800–0400 BT.
High frequency of cloud formation is found at levels
between 6 and 9 km, where the number is larger than
50%. Above 6–9 km, parts of the clouds are deep
cumulus clouds and parts are altostratus and altocumulus clouds that form after the dissipation of deep
convection.
Cloud depth is defined as the difference between the heights of cloud top and base. The cloud
depths are made detailed statistical analysis at 1-h and
1-km intervals at vertical direction. Clouds at multiple
levels are considered. The diurnal variation of cloud
depths distribution is shown in Fig. 4. It is found that
the frequency of cloud deep deeper than 5-km clouds
is less than 15%, while shallow clouds with a cloud
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depth less than 2 km has the maximum frequency.
Note that there is no distinct diurnal variation in shallow clouds, whereas clouds deeper than 5 km show
significant diurnal change. The depth of deep clouds
increases rapidly after 1200 BT, reaches the maximum
value at around 1400 BT, and maintains until before it
starts to decrease in the morning. At 1000 BT, clouds
deeper than 5 km are seldom to be observed.
The observed clouds could be single-layer clouds
or multi-layer clouds. The occurrence frequency of
cloud at a specific layer is defined as the ratio between
the number of radar beams with clouds being observed
at this layer and the total number of radar beams with
cloud detection at any layers. The time interval for
the calculation is 60 min. The occurrence frequency
for total amount of clouds, single-layer clouds, doublelayer clouds, triple-layer clouds, and multi-layer (equal
to or larger than four) clouds is shown in Fig. 5. It
shows that the occurrence frequency for total amount
of clouds is generally larger than 60%, and demonstrates a distinct diurnal variation. The occurrence
frequency for total amount of clouds is the smallest at
1200 BT (about 10:30 am in local time), and increases
rapidly with the intensified surface heating. It reaches
the maximum value of 0.9 at 2300 BT. Single-layer
clouds account for about 50% of the total amount of
clouds, and also demonstrate a distinct diurnal variation. With the increase in the cloud layers, the
percentage that they account for the total amount
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Fig. 4. Diurnal variation of cloud depth from 5 July 2014
to 4 August 2014.
Fig. 5. Diurnal variations of cloud occurrence frequency
for total amounts of clouds, single layer clouds (curve A),
double-layer clouds (curve B), triple-layer clouds (curve C),
and multiple layer clouds (curve D; 4 layers).
of clouds decreases. Wang et al. (2011) analyzed the
Cloudsat measurements and found that the total
amount of clouds in July is about 80% over the entire
TP, among which 55% of clouds are single-layer clouds.
This result is consistent with that of the present study.
4. Characteristics for different types of clouds
over the TP
Fig. 3. Occurrence frequency of cloud at various levels
during the period of 5 July to 4 August 2014.
In the International Satellite Cloud Climatology
Project (ISCCP), the values of cloud top pressure and
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LIU Liping, ZHENG Jiafeng, RUAN Zheng, et al.
optical thickness are used to classify different cloud
types, i.e., cumulus, stratocumulus, stratus, altocumulus, altostratus, nimbostratus, cirrus, cirrostrarus, and
deep convective clouds (Rossow and Schiffer, 1999). In
order to better understand the macroscopic features
of clouds over the TP and their difference to that in
other regions, different types of clouds in Naqu region
are selected for further analysis with a focus on the
vertical structure of reflectivity, vertical velocity, and
cloud-particle phase.
Figure 6 shows the time-height cross-sections of
reflectivity, radial velocity (positive upward), velocity spectrum width, and depolarization factor LDR for
the newly formed cumulus clouds. The vertical y-axis
indicates height, the x-axis indicates time, and the
origin indicates the radar antenna (4560 m AGL, the
same hereafter). It shows that cumulus cloud height
555
is about 3 km, and the cloud depth is 2 km. These cumulus clouds are the low-level clouds shown in Fig. 2.
They passed the radar station in a very short time, indicating that the clouds have a small horizontal scale.
Looking at the radial velocity, no precipitation formed
in the two clouds with the maximum reflectivity of
–30 dBZ, while the radar measured radial velocity are
mostly upward with a speed larger than 5 m s−1 , indicating that the clouds are at their developing stage.
Based on the statistical analysis of clouds in the TP,
1400 BT corresponds to the time when cumulus clouds
can develop rapidly. The cloud height and depth both
grow quickly at this time. The radial velocity is negative in the other two clouds whose reflectivity reaches
about –15 dBZ, suggesting that precipitate particles
has formed in these clouds.
Figure 7 shows the case for altocumulus clouds
Fig. 6. Cloud radar observations of cumulus clouds during 1315–1428 BT 15 July 2014. (a) Reflectivity factor, (b)
radial velocity, (c) velocity spectrum width, and (d) depolarization ratio.
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Fig. 7. As in Fig. 6, but for echo features of altocumulus clouds, cumulus clouds, and deep convection measured by
cloud radar during 0222–0449 BT 18 July 2014.
that formed in early morning coexist with cumulus
clouds and well-developed deep convection. The deep
convective clouds reach up to 12 km with a maximum
echo intensity of 15 dBZ (because of the attenuation of
cloud, real reflectivity is larger than this value). Distinct upward draft is found in the upper part of the
clouds, and a significant bright band (characterized by
abrupt increases in LDR and sudden changes in reflectivity and radial velocity) occurs at 1.5 km. The base
of the altocumulus clouds reaches up to 6 km while
the top is above 10 km. Meanwhile, cumulus clouds
are developing at the level of around 2.5 km above
the ground with a depth less than 1 km. The cumulus
cloud top is above the zero-temperature level, suggesting that ice cloud is the major component of the cu-
mulus clouds. The above two clouds are altocumulus
and low cumulus clouds shown in Fig. 2, respectively.
Large LDR is located at 3- and 8-km heights, respectively, corresponding to central parts of the deep convection and indicating that mixed phase clouds might
exist at these levels.
Convection in the TP can reach very high levels
but the convective intensity is relatively weak. There
are many cases showing the coexistence of altocumulus
clouds and deep convection. The altocumulus cloud
top is often consistent with deep convective cloud top,
possibly because the altocumulus clouds are generated
at the dissipative stage of deep convective cloud. In
addition, the cases we discuss in the following paragraph clearly show that the bright band is quite dis-
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LIU Liping, ZHENG Jiafeng, RUAN Zheng, et al.
tinct even during the process of significant convective
development, which is quite different from what happens in the low altitude regions. One possible reason is
that the zero-temperature level is closer to the ground
in the TP than in low altitude regions, resulting in a
relatively weak upward motion in this level.
Figure 8 illustrates the case when altostratus and
stratus clouds coexist in the morning and convective
development is weak. The base and top of the altostratus clouds are 6 and 11 km, respectively. The reflectivity is about –15 dBZ. The base of the stratus clouds
is at around 2.5-km height, and the cloud distribution
is horizontally homogeneous and very shallow. The reflectivity of the stratus clouds is about –35 dBZ, while
upward motion is found in the clouds. This is a period
when convection is the weakest, and the atmospheric
557
stratification is stable. However, upward motion still
exists in the stratus clouds.
Figure 9 is the time-height cross-sections of nimbostratus clouds in the morning. The cloud top is
horizontally homogeneous and reaches up to 8 km.
Reflectivity can be up to 10 dBZ and demonstrates
spatial-temporal variation. Two strong echoes pass
the cloud radar at 73 min. The bright band is quite
distinct, and the reflectivity increases by 15 dBZ after
the melting of ice particles. Radial velocity changes
by 6 m s−1 . The falling speed of liquid and solid precipitate particles can be up to 6 m s−1 if the upward
motion nearby the zero-temperature level is ignored.
The figure of the radial velocity shows that positive
radial velocity (3 m s−1 ) exists at 3-km height, indicating a significant updraft at this level. The height
Fig. 8. As in Fig. 6, but for the echo features of altostratus and stratocumulus observed by cloud radar during
0546–0700 BT 12 July 2014.
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Fig. 9. As in Fig. 6, but for the echo features of nimbostratus clouds observed by cloud radar during 0806–0919 BT 6
July 2014.
of this updraft is consistent with that occurred in the
cumulus in Figs. 6 and 7 and in the newly developed
stratus clouds shown in Fig. 8.
To compare with nimbostratus clouds, Fig. 10
presents a deep convection case. The strong convective echo passed Naqu weather station at about 30
min, and the echo height reached up to 16.5 km. Looking at the radial velocity, it is found that upward motion largely occurred above 3 km, where the maximum
radial velocity is 6 m s−1 . The upward velocity can
be larger if considering the falling speed of precipitate particles. At 1805 BT, negative radial velocity
occurred at the weak echo area at the levels between 2
and 4 km above the ground, where the radial velocity
can be up to –8 m s−1 . The curved echo shape indicates that this is an area of inflow, where the air aloft
subsides and continues to sink in the clouds. This
feature suggests that updrafts and downdrafts occur
simultaneously during deep convective process. Both
large LDR (> −24 dB) and small LDR (< −28 dB)
can be found in the convective updraft zone, implying that mixed phase and supercooled liquid water
are present in deep convective clouds. Similar to the
cumulus clouds shown in Fig. 7, even under such a
strong convective condition, we can found the bright
band clearly. Apparently, vertical motion in this layer
is not significant based on the consideration of radial
velocity and bright band.
5. Conclusions
The third Tibetan Plateau Atmospheric Science
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LIU Liping, ZHENG Jiafeng, RUAN Zheng, et al.
559
Fig. 10. As in Fig. 6, but for the deep convective case that occurred during 1725–1839 BT 5 July 2014.
Experiment was carried out from 1 July to 31 August 2014. Comprehensive measurements of water
vapor, clouds, and precipitation were conducted at
Naqu. The advanced radars in China, such as Kaband millimeter-wave cloud radar, Ku-band microrain radar, C-band continuous-wave radar and lidars,
and microwave radiometer and disdrometer were deployed to observe high spatial-temporal resolution of
vertical structures for clouds and precipitation. The
C-band dual-linear polarization radar was coordinated
with the new generation weather radar to constitute
a dual-Doppler radar system for the measurements
of three-dimensional wind fields and the hydrometeor distributions within precipitations. Based on the
radar measurements in this experiment, we analyzed
the statistical features of clouds in the summer over
Naqu region, and revealed the macro features of different types of clouds. The major conclusions are as
follows.
(1) The cloud properties have been successfully
measured by using various ground-based radars in the
field experiment conducted in the summer of 2014. In
particular, information about the vertical structure
and evolution of clouds obtained in this experiment
provides a strong basis for further studies in cloud
physics and precipitation process.
(2) During the summertime over Naqu, clouds
are largely distributed at levels above 6 km and below
4 km. Few clouds form at around 5 km. Statistical
analysis showed that total amounts of clouds, the top
of high clouds, and cloud depth, all demonstrate a distinct diurnal variation. Few clouds form at 1000 LST,
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whereas the strong surface heating after the noon
effectively promotes the development of convection.
There is distinct diurnal variation in the top of lowand mid-level clouds. The highest frequency of cloud
formation is found at 6–9-km levels during 1800–0400
BT.
(3) Newly formed cumulus and stratus clouds
are often found at 3-km height, where there often exist significant updrafts. Various types of clouds and
clouds at different levels of height often coexist during
this period. Altostratus and altocumulus clouds are
probably related to the dissipating process of the deep
convection.
(4) Analysis of the observed deep convection cases
indicates that updrafts and downdrafts often exist simultaneously in the convective system. Supercooled
water and mixed phase might exist in such kinds of
deep convective system.
The above measurements and preliminary analysis provide a basis for further study of clouds and
precipitation in the TP. These observations are also
valuable in modeling studies of cloud and precipitation
physics as well as in the development of parameterization schemes in numerical prediction models.
Acknowledgments. We appreciate the contribution made by Meteorological Bureau of Tibet Autonomous Region, Naqu Bureau of Meteorology, the
23rd Research Institute of China Aerospace & Industry Corp., and Anhui Sun-create Electronics Limited
Company. We also thank Professor Zhao Ping and
Dr. Gao Wenhua for their suggestions and comments.
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