Articles | Volume 23, issue 23
https://doi.org/10.5194/acp-23-15011-2023
© Author(s) 2023. 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-23-15011-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Characterizing the near-global cloud vertical structures over land using high-resolution radiosonde measurements
Hui Xu
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Bing Tong
CORRESPONDING AUTHOR
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
Jinqiang Zhang
Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
Tianmeng Chen
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Xiaoran Guo
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Jian Zhang
Hubei Subsurface Multi-Scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan, 430074, China
Wenqing Chen
Business Science and Technology Division, National Meteorological Information Centre, Beijing, 100081, China
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Linye Song, Shangfeng Chen, Wen Chen, Jianping Guo, Conglan Cheng, and Yong Wang
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Ifeanyichukwu C. Nduka, Chi-Yung Tam, Jianping Guo, and Steve Hung Lam Yim
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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.
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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.
Jianping Guo, Boming Liu, Wei Gong, Lijuan Shi, Yong Zhang, Yingying Ma, Jian Zhang, Tianmeng Chen, Kaixu Bai, Ad Stoffelen, Gerrit de Leeuw, and Xiaofeng Xu
Atmos. Chem. Phys., 21, 2945–2958, https://doi.org/10.5194/acp-21-2945-2021, https://doi.org/10.5194/acp-21-2945-2021, 2021
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Vertical wind profiles are crucial to a wide range of atmospheric disciplines. Aeolus is the first satellite mission to directly observe wind profile information on a global scale. However, Aeolus wind products over China have thus far not been evaluated by in situ comparison. This work is expected to let the public and science community better know the Aeolus wind products and to encourage use of these valuable data in future research and applications.
Boming Liu, Jianping Guo, Wei Gong, Yong Zhang, Lijuan Shi, Yingying Ma, Jian Li, Xiaoran Guo, Ad Stoffelen, Gerrit de Leeuw, and Xiaofeng Xu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-41, https://doi.org/10.5194/acp-2021-41, 2021
Revised manuscript not accepted
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Vertical wind profiles are crucial to a wide range of atmospheric disciplines. Aeolus is the first satellite mission to directly observe wind profile information on a global scale. However, Aeolus wind products over China were thus far not evaluated by in-situ comparison. This work is expected to let the public and science community better know the Aeolus wind products and to encourage use of these valuable data in future researches and applications.
Kaixu Bai, Ke Li, Chengbo Wu, Ni-Bin Chang, and Jianping Guo
Earth Syst. Sci. Data, 12, 3067–3080, https://doi.org/10.5194/essd-12-3067-2020, https://doi.org/10.5194/essd-12-3067-2020, 2020
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Yuli Zhang, Mengchu Tao, Jinqiang Zhang, Yi Liu, Hongbin Chen, Zhaonan Cai, and Paul Konopka
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Yang Yang, Min Chen, Xiujuan Zhao, Dan Chen, Shuiyong Fan, Jianping Guo, and Shaukat Ali
Atmos. Chem. Phys., 20, 12527–12547, https://doi.org/10.5194/acp-20-12527-2020, https://doi.org/10.5194/acp-20-12527-2020, 2020
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This study analyzed the impacts of aerosol–radiation interaction on radiation and meteorological forecasts using the offline coupling of WRF and high-frequency updated AOD simulated by WRF-Chem. The results revealed that aerosol–radiation interaction had a positive influence on the improvement of predictive accuracy, including 2 m temperature (~ 73.9 %) and horizontal wind speed (~ 7.8 %), showing potential prospects for its application in regional numerical weather prediction in northern China.
Ruqian Miao, Qi Chen, Yan Zheng, Xi Cheng, Yele Sun, Paul I. Palmer, Manish Shrivastava, Jianping Guo, Qiang Zhang, Yuhan Liu, Zhaofeng Tan, Xuefei Ma, Shiyi Chen, Limin Zeng, Keding Lu, and Yuanhang Zhang
Atmos. Chem. Phys., 20, 12265–12284, https://doi.org/10.5194/acp-20-12265-2020, https://doi.org/10.5194/acp-20-12265-2020, 2020
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In this study we evaluated the model performances for simulating secondary inorganic aerosol (SIA) and organic aerosol (OA) in PM2.5 in China against comprehensive datasets. The potential biases from factors related to meteorology, emission, chemistry, and atmospheric removal are systematically investigated. This study provides a comprehensive understanding of modeling PM2.5, which is important for studies on the effectiveness of emission control strategies.
Minqiang Zhou, Pucai Wang, Bavo Langerock, Corinne Vigouroux, Christian Hermans, Nicolas Kumps, Ting Wang, Yang Yang, Denghui Ji, Liang Ran, Jinqiang Zhang, Yuejian Xuan, Hongbin Chen, Françoise Posny, Valentin Duflot, Jean-Marc Metzger, and Martine De Mazière
Atmos. Meas. Tech., 13, 5379–5394, https://doi.org/10.5194/amt-13-5379-2020, https://doi.org/10.5194/amt-13-5379-2020, 2020
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We study O3 retrievals in the 3040 cm-1 spectral range from FTIR measurements at Xianghe China (39.75° N, 116.96° E; 50 m a.s.l.) between June 2018 and December 2019. It was found that the FTIR O3 (3040 cm-1) retrievals capture the seasonal and synoptic variations of O3 very well. The systematic and random uncertainties of FTIR O3 (3040 cm-1) total column are about 13.6 % and 1.4 %, respectively. The DOFS is 2.4±0.3 (1σ), with two individual pieces of information in surface–20 km and 20–40 km.
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Short summary
The radiative effect of cloud remains one of the largest uncertain factors in climate change, largely due to the lack of cloud vertical structure (CVS) observations. The study presents the first near-global CVS climatology using high-vertical-resolution soundings. Single-layer cloud mainly occurs over arid regions. As the number of cloud layers increases, clouds tend to have lower bases and thinner layer thicknesses. The occurrence frequency of cloud exhibits a pronounced seasonal diurnal cycle.
The radiative effect of cloud remains one of the largest uncertain factors in climate change,...
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