Articles | Volume 18, issue 4
https://doi.org/10.5194/essd-18-2689-2026
© 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/essd-18-2689-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
17 Apr 2026
Data description article |
| 17 Apr 2026
| 17 Apr 2026
A high-resolution tropopause folding dataset over China from 2014–2023
Yujia Yang
State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science and Technology, Nanjing, 210044, China
Le Cao
CORRESPONDING AUTHOR
State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science and Technology, Nanjing, 210044, China
Liqiang Xu
State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science and Technology, Nanjing, 210044, China
Mengke Wang
State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science and Technology, Nanjing, 210044, China
Qingjian Yang
State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science and Technology, Nanjing, 210044, China
National Meteorological Information Center, China Meteorological Administration, Beijing, 100081, China
Yuqing Zhang
State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science and Technology, Nanjing, 210044, China
Tianqi Zhang
National Supercomputer Center in Tianjin, Tianjin, 300457, China
Xiuli Lei
National Supercomputer Center in Tianjin, Tianjin, 300457, China
Jiangpeng Miao
State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science and Technology, Nanjing, 210044, China
Tianliang Zhao
State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science and Technology, Nanjing, 210044, China
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Atmos. Chem. Phys., 22, 3579–3593, https://doi.org/10.5194/acp-22-3579-2022, https://doi.org/10.5194/acp-22-3579-2022, 2022
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Xiangde Xu, Chan Sun, Deliang Chen, Tianliang Zhao, Jianjun Xu, Shengjun Zhang, Juan Li, Bin Chen, Yang Zhao, Hongxiong Xu, Lili Dong, Xiaoyun Sun, and Yan Zhu
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A vertical transport window of tropospheric vapor exists on the Tibetan Plateau (TP). The TP's thermal forcing drives the vertical transport
windowof vapor in the troposphere. The effects of the TP's vertical transport window of vapor are of importance in global climate change.
Hongyi Ding, Le Cao, Haimei Jiang, Wenxing Jia, Yong Chen, and Junling An
Geosci. Model Dev., 14, 6135–6153, https://doi.org/10.5194/gmd-14-6135-2021, https://doi.org/10.5194/gmd-14-6135-2021, 2021
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We performed a WRF model study to figure out the mechanism of how the change in minimum eddy diffusivity (Kzmin) in the planetary boundary layer (PBL) closure scheme (ACM2) affects the simulated near-surface temperature in Beijing, China. Moreover, the influence of changing Kzmin on the temperature prediction in areas with different land-use categories was studied. The model performance using a functional-type Kzmin for capturing the temperature change in this area was also clarified.
Xiangde Xu, Wenyue Cai, Tianliang Zhao, Xinfa Qiu, Wenhui Zhu, Chan Sun, Peng Yan, Chunzhu Wang, and Fei Ge
Atmos. Chem. Phys., 21, 14131–14139, https://doi.org/10.5194/acp-21-14131-2021, https://doi.org/10.5194/acp-21-14131-2021, 2021
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We found that the structure of atmospheric thermodynamics in the troposphere can be regarded as a strong forewarning signal for variations of surface PM2.5 concentration in heavy air pollution.
Le Cao, Simeng Li, and Luhang Sun
Atmos. Chem. Phys., 21, 12687–12714, https://doi.org/10.5194/acp-21-12687-2021, https://doi.org/10.5194/acp-21-12687-2021, 2021
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Gas-phase chemical reaction mechanisms, e.g., CB6 mechanism, are essential parts of the atmospheric transport model. In order to better understand the changes caused by the updates between different versions of the CB6 mechanism, in this study, the behavior of three different CB6 mechanisms in simulating ozone, nitrogen oxides and formaldehyde under two different emission conditions was analyzed using a concentration sensitivity analysis, and the reasons causing the deviations were figured out.
Zhuozhi Shu, Yubao Liu, Tianliang Zhao, Junrong Xia, Chenggang Wang, Le Cao, Haoliang Wang, Lei Zhang, Yu Zheng, Lijuan Shen, Lei Luo, and Yueqing Li
Atmos. Chem. Phys., 21, 9253–9268, https://doi.org/10.5194/acp-21-9253-2021, https://doi.org/10.5194/acp-21-9253-2021, 2021
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Focusing on a heavy haze pollution event in the Sichuan Basin (SCB), we investigated the elevated 3D structure of PM2.5 and trans-boundary transport with the WRF-Chem simulation. It is remarkable for vertical PM2.5 that the unique hollows were structured, which which occurred by the interaction of vortex circulations and topographic effects. The SCB was regarded as the major air pollutant source with the trans-boundary transport of PM2.5 affecting atmospheric environment changes.
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Short summary
This study provides a high-resolution (0.25°, hourly) tropopause folding dataset for China (2014–2023) using ERA5 (ECMWF Reanalysis version 5) reanalysis data and a three-dimensional labeling method. It fills a critical data gap, enabling detailed spatiotemporal analysis of tropopause folding events. This validated resource provides a solid foundation for investigating stratosphere-troposphere transport and its impacts on near-surface air quality and extreme weather.
This study provides a high-resolution (0.25°, hourly) tropopause folding dataset for China...
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