Citation: Yang, J.; Liu, E.; Liu, Y.; Lin,
Y.; Yin, Y.; Jing, X. Impact of Vertical
Wind Shear on Summer Orographic
Clouds over Tian Shan Mountains: A
Case Study Based on Radar
Observation and Numerical
Simulation. Remote Sens. 2022, 14,
1583. https://doi.org/10.3390/
rs14071583
Academic Editor: Filomena Romano
Received: 14 February 2022
Accepted: 23 March 2022
Published: 25 March 2022
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remote sensing
Article
Impact of Vertical Wind Shear on Summer Orographic Clouds
over Tian Shan Mountains: A Case Study Based on Radar
Observation and Numerical Simulation
Jing Yang
1,2
, Enhong Liu
1
, Yubao Liu
1,
* , Yanjun Lin
1
, Yan Yin
1
and Xiaoqin Jing
1
1
Key Laboratory for Aerosol Cloud-Precipitation of China Meteorological Administration/Key Laboratory of
Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate
and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters (CIC-FEMD)/Precision Regional Earth Modeling and Information Center (PRMIC),
Nanjing University of Information Science & Technology, Nanjing 210044, China;
jing.yang@nuist.edu.cn (J.Y.); 20191203014@nuist.edu.cn (E.L.); 20191201047@nuist.edu.cn (Y.L.);
yinyan@nuist.edu.cn (Y.Y.); xiaoqin.jing@nuist.edu.cn (X.J.)
2
Key Laboratory of Cloud and Fog Physical Environment of China Meteorological Administration,
Beijing 100081, China
* Correspondence: ybliu@nuist.edu.cn
Abstract: In this research, a summer orographic precipitation process that occurred over the Tian
Shan Mountains on 27 July 2019, was investigated, focusing on the impact of vertical wind shear
on clouds. Multiple remote sensors were deployed to measure the ambient conditions and the
fine structures of clouds and precipitation, including a radiometer, a vertically pointing micro-rain
radar (MRR), and a cloud radar on a truck. In addition, a convection-permitting simulation was
conducted to investigate the role of vertical wind shear. The results show that (1) according to the
MRR measurements, the precipitation was mainly due to a warm rain process and was mostly light
to moderate, with no strong convection occurring; (2) the cloud structures observed by the cloud
radar were very different above and below the shear level, and the cloud evolution was strongly
controlled by the vertical wind shear, and (3) radar observations and model simulations indicated
that vertical wind shear had an inhibiting impact on the vertical development of clouds and was
responsible for the formation of multi-layer clouds. The analysis highlights the advantages of the use
of millimeter radars to measure the fine structures of orographic clouds; thus, they can be powerful
tools with which to improve our understanding of the interactions occurring between vertical wind
shear and clouds over complex terrain.
Keywords: orographic cloud; vertical wind shear; Tian Shan Mountains; radar measurement;
numerical simulation
1. Introduction
In the arid northwest of China, orographic precipitation is the most important water
resource. There is much interest in studying the orographic clouds and precipitation in this
region in various disciplines, such as meteorology, hydrology, ecology, and forestry [1–4].
Tian Shan is among the largest mountain ranges in Central Asia and is home to the head-
waters of several major river systems. However, the measurement of the orographic clouds
and precipitation over the Tian Shan Mountains is challenging because of the complex
terrain and high elevations involved [5,6]. The gauge stations over the Tian Shan Mountains
are sparsely distributed and have very limited capabilities, and gauges only provide point
measurements of surface precipitation. Radar measurements of clouds and precipitation
are also lacking because there is only a single centimeter radar in operation, which covers a
very limited area over the mountains. Therefore, the orographic cloud and precipitation
processes over the Tian Shan Mountains are still poorly understood.
Remote Sens. 2022, 14, 1583. https://doi.org/10.3390/rs14071583 https://www.mdpi.com/journal/remotesensing