Shuqing Ma

Shuqing Ma


Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
12 January 2022 in Advances in Atmospheric Sciences
Verified
Journal Article
Closed access
PDF file
XZXiaoqiong Zhen
Xiaoqiong Zhen
SMShuqing Ma
Shuqing Ma
HCHongbin Chen
Hongbin Chen
GWGuorong Wang
Guorong Wang
XXXiaoping Xu
Xiaoping Xu
SLSiteng Li
Siteng Li

1 May 2025 in Sensors
Verified
Journal Article
Open access
PDF file
XZXiaoqiong Zhen
Xiaoqiong Zhen
HCHongbin Chen
Hongbin Chen
HSHongRong Shi
HongRong Shi
Xuehua FanXuehua Fan
Xuehua Fan
HCHaojun Chen
Haojun Chen
Jianxin HeJianxin He
Jianxin He
This study investigates a severe summer convective hailstorm that occurred in Shanghai on 18 August 2019, using multisource meteorological datasets, with a particular focus on the innovative application of a single-polarization X-band array weather radar (AWR). Radiosonde data revealed high convective available potential energy and unstable atmospheric indices, while wind profiler radars (WPRs) showed initial easterly moisture transport near the ground and strong southwesterly flow aloft, both contributing significantly to intense convection. Ground-based automatic meteorological stations (AMSs) recorded abrupt temperature drops of approximately 10 °C and wind speed increases exceeding 20 m s−1, which aligned closely with the rapid expansion of the hailstorm. In addition, an integrated analysis of data from AWR, WPRs, and AMSs enabled detailed tracking of the storm’s evolution, providing deeper insights into the interplay between moisture transport and dynamic lifting. The AWR’s unique ability to capture divergence and vorticity fields at different altitudes revealed low-level convergence coupled with high-level divergence and cyclonic rotation, sustaining convective updrafts. This study underscores the value of high-resolution AWR data in capturing short-lived, intense precipitation processes, thereby enhancing our understanding of wind field structures and storm development. These findings highlight the comprehensive application of AWR data and the potential of this new high-spatiotemporal-resolution radar for investigating the mechanisms of short-lived severe convective processes.

27 March 2023 in Remote Sensing
Verified
Journal Article
Open access
PDF file
YTYupeng Teng
Yupeng Teng
LTLI Tianyan
LI Tianyan
SMShuqing Ma
Shuqing Ma
HCHongbin Chen
Hongbin Chen
It is commonly believed that clear-air echoes detected by weather radars are caused by atmobios migration. However, clear-air echoes are sometimes inconsistently related to the activity of living creatures. In some cases, the characteristics of radar products seem to conform to biological scattering, but the movement of echoes cannot be observed. For these reasons, we sought to expand the cause of clear-air echoes from a Chinese Doppler S-band Weather Radar (CINRAD/SA) in Beijing. Some contradictions were discovered in a case which diverged from previous conclusions. It was found that the progression and movement of clear-air echoes do not conform to the rules of biological activities. The frequency distribution of dual-wavelength ratio peaks is 21.5 dB, which is in accordance with Villars–Weisskopf’s turbulence theory. From 1 May to 20 May, the 58% dual-wavelength ratio between the S-band and the X-band was distributed between 18 dB and 24 dB. These results show that more than half of the clear-air echoes of CINRAD/SA at night were caused by turbulence in Beijing. A new model of troposcatter propagation, the reflecting-layers model, was then introduced to explain the radar observations. According to the reflecting-layers model, the echoes’ diurnal variation and reflectivity characteristics are attributed to the effects of turbulent mixing. Excessive turbulent mixing affects the generation of the reflective layer, thereby weakening the echo signal. It is necessary to re-examine the position of turbulence in clear-air echoes.

28 July 2025 in Remote Sensing
Verified
Journal Article
Open access
PDF file
XZXin Zhou
Xin Zhou
LYLing Yang
Ling Yang
SMShuqing Ma
Shuqing Ma
RWRuifeng Wang
Ruifeng Wang
ZLZhaoming Li
Zhaoming Li
JXJinyan Xu
Jinyan Xu
An EF1 tornado struck Nansha District, Guangzhou, Guangdong, on 28 July 2024. To explore the dynamic and thermodynamic changes during the tornado’s life cycle, high-resolution spatiotemporal data from Foshan’s X-band phased-array radar and the direct wind field synthesis algorithm were used to reconstruct the 3D wind field. The dynamics and 3D structure of the tornado were analysed, with a new parameter, vorticity volume (VV), introduced to study its variation. The observation results indicate that the tornado moved roughly from south to north. During the tornado’s early stage (00:10–00:20 UTC), arc-shaped and annular echoes emerged and positive vorticity increased (peaking at 0.042 s−1). Based on the tornado’s movement direction, the right side of the vortex centre was divergent, while the left side was convergent, whereas the vorticity area and volume continued to grow centrally. During the mature stage (00:23–00:25 UTC), the echo intensity weakened and, at 00:24, the vorticity reached its peak and touched the ground, with the vorticity area and volume also reaching their peaks at the same time. During the dissipation stage (00:25–00:30 UTC), the vorticity and echo features faded and the vorticity area and volume also declined rapidly. The analysis showed that the vorticity volume effectively reflects the tornado’s life cycle, enhancing the understanding of the dynamic and thermodynamic processes during the tornado’s development.

15 April 2025 in Remote Sensing
Verified
Journal Article
Open access
PDF file
XZXiaoqiong Zhen
Xiaoqiong Zhen
HCHongbin Chen
Hongbin Chen
Xuehua FanXuehua Fan
Xuehua Fan
HSHongRong Shi
HongRong Shi
HCHaojun Chen
Haojun Chen
Jianxin HeJianxin He
Jianxin He
On 13 August 2019, a severe convective precipitation event affected the Shanghai region. At 850 hPa, a low-level shear line influenced Shanghai with surface convergence, while at 700 hPa, an inversion layer separated warm, moist lower air from colder, drier air aloft, favoring convection. Observations also revealed vertical wind shear, facilitating additional convective growth. Observations from local automatic weather stations (AWSs) and wind profiler radars (WPRs) indicate that five minutes before rainfall began, ground heat and northerly winds collided, triggering the precipitation. Both the S-band Qingpu SA radar and a novel single-polarization X-band Array weather radar system (Array Weather Radar, AWR) with three phased-array radar frontends and one radar backend captured this event. Compared with the relatively coarse spatiotemporal resolution of the Qingpu SA radar, the AWR provides high-resolution wind-field data, enabling the derivation of horizontal divergence and vertical vorticity. A detailed analysis of reflectivity, divergence, and vorticity in the AWR’s overlapping detection areas shows that, during the development and mature stages of the cell’s lifecycle, the volume of echoes with Z > 25 dBZ consistently increases, whereas echoes with Z > 45 dBZ grow in an oscillatory pattern, reaching five peaks. Moreover, at the altitudes where Z > 45 dBZ appears, regions of cyclonic vorticity emerge.

20 September 2019 in Atmosphere
Verified
Journal Article
Open access
PDF file
KYKai Ye
Kai Ye
LYLing Yang
Ling Yang
SMShuqing Ma
Shuqing Ma
XZXiaoqiong Zhen
Xiaoqiong Zhen
Xingang FanXingang Fan
Xingang Fan
Array Weather Radar (AWR) is a novel type weather radar equipped with a distributed phased array technology. As a new instrument with new technology, the AWR offers very high spatiotemporal resolution that enables detection of the fine-scale flow field and reflectivity of severe convective storms. This new AWR provides coordinated observations of a target from three subarrays of transmitter-receiver antenna units. This paper introduces a resolution enhancement concept that the very high range resolution of one subarray can be used to compensate lower azimuth and elevation resolutions of the other subarrays of the AWR. The resolution enhancement effect is estimated using data point density. A data fusion method is then presented to obtain a unified high-resolution reflectivity from the networked and coordinated AWR subarray observations. First, based on the reflectivity data from the AWR subarray volume scans, numbers of the data-point filling in both the azimuth and elevation directions are calculated. Then, the fusion of three subarray reflectivity data is achieved through the vertical and horizontal filling and merging in a common coordinate system. The final product of the fused high-resolution reflectivity is verified using both subjective and objective evaluations. The verification experiments included radar echoes of two simulated weather scenarios, a small-scale heavy precipitation and a tornado, along with a real precipitation event. The real precipitation event was observed from the AWR system that is installed and operational at the Changsha Huanghua International Airport. The performance of the proposed high-resolution reflectivity fusion method yields a 35% smaller root mean square error and an 11% increase in the correlation coefficient to the maximum extent. The real event result shows that the final fused high-resolution reflectivity depicted a more detailed and complete echo structure compared to the China New Generation Weather Radar network observation.