Articles | Volume 26, issue 5
https://doi.org/10.5194/acp-26-3339-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-3339-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Mar 2026
Research article |
| 04 Mar 2026
| 04 Mar 2026
On the nationwide variability of low-level jets prior to warm-season nocturnal rainfall in China revealed by radar wind profilers
Ning Li
State Key Laboratory of Severe Weather Meteorological Science and Technology & Specialized Meteorological Support Technology Research Center, Chinese Academy of Meteorological Sciences, Beijing 100081, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
National Meteorological Centre, Beijing 100081, China
State Key Laboratory of Severe Weather Meteorological Science and Technology & Specialized Meteorological Support Technology Research Center, Chinese Academy of Meteorological Sciences, Beijing 100081, China
CMA Field Scientific Experiment Base for Low-Altitude Economy Meteorological Support of Unmanned Aviation in Guangdong-Hong Kong-Macao Greater Bay Area, Shenzhen 518108, China
Xiaoran Guo
State Key Laboratory of Severe Weather Meteorological Science and Technology & Specialized Meteorological Support Technology Research Center, Chinese Academy of Meteorological Sciences, Beijing 100081, China
CMA Field Scientific Experiment Base for Low-Altitude Economy Meteorological Support of Unmanned Aviation in Guangdong-Hong Kong-Macao Greater Bay Area, Shenzhen 518108, China
Tianmeng Chen
State Key Laboratory of Severe Weather Meteorological Science and Technology & Specialized Meteorological Support Technology Research Center, Chinese Academy of Meteorological Sciences, Beijing 100081, China
CMA Field Scientific Experiment Base for Low-Altitude Economy Meteorological Support of Unmanned Aviation in Guangdong-Hong Kong-Macao Greater Bay Area, Shenzhen 518108, China
Zhen Zhang
State Key Laboratory of Severe Weather Meteorological Science and Technology & Specialized Meteorological Support Technology Research Center, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Na Tang
State Key Laboratory of Severe Weather Meteorological Science and Technology & Specialized Meteorological Support Technology Research Center, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Yifei Wang
State Key Laboratory of Severe Weather Meteorological Science and Technology & Specialized Meteorological Support Technology Research Center, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Honglong Yang
CMA Field Scientific Experiment Base for Low-Altitude Economy Meteorological Support of Unmanned Aviation in Guangdong-Hong Kong-Macao Greater Bay Area, Shenzhen 518108, China
Yongguang Zheng
National Meteorological Centre, Beijing 100081, China
Yongshui Zhou
Guizhou Meteorological Observatory, Guiyang 550001, China
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Publication in AMT not foreseen
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This study analyzed the nature, mechanisms and drivers for hot-and-polluted episodes (HPEs) in the Pearl River Delta, China. A total of eight HPEs were identified and can be grouped into three clusters of HPEs that were respectively driven (1) by weak subsidence and convection induced by approaching tropical cyclones, (2) by calm conditions with low wind speed in the lower atmosphere and (3) by the combination of both aforementioned conditions.
Lei Li, Chao Lu, Pak-Wai Chan, Zi-Juan Lan, Wen-Hai Zhang, Hong-Long Yang, and Hai-Chao Wang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-579, https://doi.org/10.5194/acp-2021-579, 2021
Revised manuscript not accepted
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The COVID-19 induced lockdown provided a time-window to study the impact of emission decrease on atmospheric environment. A 350 m meteorological tower in the Pearl River Delta recorded the vertical distribution of pollutants during the lockdown period. The observation confirmed that an extreme emission reduction, can reduce the concentrations of fine particles and the peak concentration of ozone at the same time, which had been taken as difficult to realize in the past in many regions.
Tianmeng Chen, Zhanqing Li, Ralph A. Kahn, Chuanfeng Zhao, Daniel Rosenfeld, Jianping Guo, Wenchao Han, and Dandan Chen
Atmos. Chem. Phys., 21, 6199–6220, https://doi.org/10.5194/acp-21-6199-2021, https://doi.org/10.5194/acp-21-6199-2021, 2021
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A convective cloud identification process is developed using geostationary satellite data from Himawari-8.
Convective cloud fraction is generally larger before noon and smaller in the afternoon under polluted conditions, but megacities and complex topography can influence the pattern.
A robust relationship between convective cloud and aerosol loading is found. This pattern varies with terrain height and is modulated by varying thermodynamic, dynamical, and humidity conditions during the day.
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Short summary
Nighttime rainfall often links to low-level jets (LLJs), but we lack clarity on nationwide LLJ features. We here used a nationwide radar wind profiler network to study LLJ changes 2 hours before rainfall, covering China’s 2023–2024 rainy seasons. 56% nighttime rainfall had LLJs. The LLJs-associated heavy rain needed a rapid adjustment of LLJs’ vertical structure, especially a significant intensification within 30 minutes preceding rain. This shows the importance of LLJ in nowcasting rainfall.
Nighttime rainfall often links to low-level jets (LLJs), but we lack clarity on nationwide LLJ...
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