Articles | Volume 22, issue 4
https://doi.org/10.5194/acp-22-2221-2022
© Author(s) 2022. 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-22-2221-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Feb 2022
Research article |
| 17 Feb 2022
| 17 Feb 2022
Development and application of a street-level meteorology and pollutant tracking system (S-TRACK)
Huan Zhang
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Sunling Gong
CORRESPONDING AUTHOR
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Lei Zhang
CORRESPONDING AUTHOR
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Jingwei Ni
Henan Tianlang Ecological Technology Co. Ltd., Zhengzhou 450000, China
Jianjun He
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Yaqiang Wang
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Xu Wang
Hangzhou Yizhang Technology Co., Ltd., Hangzhou 310000, China
Lixin Shi
Key Laboratory of Meteorology and Ecological Environment of Hebei Province, Shijiazhuang 050000, China
Jingyue Mo
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Huabing Ke
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Shuhua Lu
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
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Yarong Li, Zeyang Liu, and Jianjun He
EGUsphere, https://doi.org/10.5194/egusphere-2025-4918, https://doi.org/10.5194/egusphere-2025-4918, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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An attention-augmented ResNet and a transfer training are implemented to derive diurnal variations in near-global planetary boundary layer height. The transfer-trained model shows superior performances compared to conventional algorithms and non-transfer trained mode. The model predicted more reliable diurnal PBLH behaviors, with daily amplitude and peak timing approaching radiosonde results.
Suping Zhao, Shaofeng Qi, Jianjun He, Ye Yu, Longxiang Dong, Tong Zhang, Guo Zhao, and Yiting Lv
EGUsphere, https://doi.org/10.5194/egusphere-2025-3130, https://doi.org/10.5194/egusphere-2025-3130, 2025
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Upper-air secondary pollutants can downward invade to PBL by strong turbulence at the sloped terrain. The results are helpful for understanding formation mechanism of heavy air pollution at the complex terrain, and then taking the targeted countermeasures.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6833–6856, https://doi.org/10.5194/gmd-16-6833-2023, https://doi.org/10.5194/gmd-16-6833-2023, 2023
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In addition to the dominant role of the PBL scheme on the results of the meteorological field, many factors in the model are influenced by large uncertainties. This study focuses on the uncertainties that influence numerical simulation results (including horizontal resolution, vertical resolution, near-surface scheme, initial and boundary conditions, underlying surface update, and update of model version), hoping to provide a reference for scholars conducting research on the model.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6635–6670, https://doi.org/10.5194/gmd-16-6635-2023, https://doi.org/10.5194/gmd-16-6635-2023, 2023
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Most current studies on planetary boundary layer (PBL) parameterization schemes are relatively fragmented and lack systematic in-depth analysis and discussion. In this study, we comprehensively evaluate the performance capability of the PBL scheme in five typical regions of China in different seasons from the mechanism of the scheme and the effects of PBL schemes on the near-surface meteorological parameters, vertical structures of the PBL, PBL height, and turbulent diffusion.
Siting Li, Ping Wang, Hong Wang, Yue Peng, Zhaodong Liu, Wenjie Zhang, Hongli Liu, Yaqiang Wang, Huizheng Che, and Xiaoye Zhang
Geosci. Model Dev., 16, 4171–4191, https://doi.org/10.5194/gmd-16-4171-2023, https://doi.org/10.5194/gmd-16-4171-2023, 2023
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Optimizing the initial state of atmospheric chemistry model input is one of the most essential methods to improve forecast accuracy. Considering the large computational load of the model, we introduce an ensemble optimal interpolation scheme (EnOI) for operational use and efficient updating of the initial fields of chemical components. The results suggest that EnOI provides a practical and cost-effective technique for improving the accuracy of chemical weather numerical forecasts.
Jianyan Lu, Sunling Gong, Jian Zhang, Jianmin Chen, Lei Zhang, and Chunhong Zhou
Atmos. Chem. Phys., 23, 8021–8037, https://doi.org/10.5194/acp-23-8021-2023, https://doi.org/10.5194/acp-23-8021-2023, 2023
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WRF/CUACE was used to assess the cloud chemistry contribution in China. Firstly, the CUACE cloud chemistry scheme was found to reproduce well the cloud processing and consumption of H2O2, O3, and SO2, as well as the increase of sulfate. Secondly, during cloud availability in December under a heavy pollution episode, sulfate production increased 60–95 % and SO2 was reduced by over 80 %. This study provides a way to analyze the phenomenon of overestimation of SO2 in many chemical transport models.
Haixia Xiao, Yaqiang Wang, Yu Zheng, Yuanyuan Zheng, Xiaoran Zhuang, Hongyan Wang, and Mei Gao
Geosci. Model Dev., 16, 3611–3628, https://doi.org/10.5194/gmd-16-3611-2023, https://doi.org/10.5194/gmd-16-3611-2023, 2023
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Due to the small-scale and nonstationary nature of convective wind gusts (CGs), reliable CG nowcasting has remained unattainable. Here, we developed a deep learning model — namely CGsNet — for 0—2 h of quantitative CG nowcasting, first achieving minute—kilometer-level forecasts. Based on the CGsNet model, the average surface wind speed (ASWS) and peak wind gust speed (PWGS) predictions are obtained. Experiments indicate that CGsNet exhibits higher accuracy than the traditional method.
Jian-yan Lu, Sunling Gong, Chun-hong Zhou, Jian Zhang, Jian-min Chen, and Lei Zhang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-716, https://doi.org/10.5194/acp-2022-716, 2022
Revised manuscript not accepted
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A regional online chemical weather model WRF/ CUACE was used to assess the contributions of cloud chemistry to the SO2 and sulfate levels in typical regions in China. The cloud chemistry scheme in CUACE was evaluated, and well reproduces the cloud chemistry processes. During cloud availability in a heavy pollution episode, the sulfate production increases 40–80 % and SO2 reduces over 80 %. This study provides a way to analyze the over-estimate phenomenon of SO2 in many chemical transport models.
Lei Li, Yevgeny Derimian, Cheng Chen, Xindan Zhang, Huizheng Che, Gregory L. Schuster, David Fuertes, Pavel Litvinov, Tatyana Lapyonok, Anton Lopatin, Christian Matar, Fabrice Ducos, Yana Karol, Benjamin Torres, Ke Gui, Yu Zheng, Yuanxin Liang, Yadong Lei, Jibiao Zhu, Lei Zhang, Junting Zhong, Xiaoye Zhang, and Oleg Dubovik
Earth Syst. Sci. Data, 14, 3439–3469, https://doi.org/10.5194/essd-14-3439-2022, https://doi.org/10.5194/essd-14-3439-2022, 2022
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A climatology of aerosol composition concentration derived from POLDER-3 observations using GRASP/Component is presented. The conceptual specifics of the GRASP/Component approach are in the direct retrieval of aerosol speciation without intermediate retrievals of aerosol optical characteristics. The dataset of satellite-derived components represents scarce but imperative information for validation and potential adjustment of chemical transport models.
Junting Zhong, Xiaoye Zhang, Ke Gui, Jie Liao, Ye Fei, Lipeng Jiang, Lifeng Guo, Liangke Liu, Huizheng Che, Yaqiang Wang, Deying Wang, and Zijiang Zhou
Earth Syst. Sci. Data, 14, 3197–3211, https://doi.org/10.5194/essd-14-3197-2022, https://doi.org/10.5194/essd-14-3197-2022, 2022
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Historical long-term PM2.5 records with high temporal resolution are essential but lacking for research and environmental management. Here, we reconstruct site-based and gridded PM2.5 datasets at 6-hour intervals from 1960 to 2020 that combine visibility, meteorological data, and emissions based on a machine learning model with extracted spatial features. These two PM2.5 datasets will lay the foundation of research studies associated with air pollution, climate change, and aerosol reanalysis.
Ke Gui, Wenrui Yao, Huizheng Che, Linchang An, Yu Zheng, Lei Li, Hujia Zhao, Lei Zhang, Junting Zhong, Yaqiang Wang, and Xiaoye Zhang
Atmos. Chem. Phys., 22, 7905–7932, https://doi.org/10.5194/acp-22-7905-2022, https://doi.org/10.5194/acp-22-7905-2022, 2022
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This study investigates the aerosol optical and radiative properties and meteorological drivers during two mega SDS events over Northern China in March 2021. The MODIS-retrieved DOD data registered these two events as the most intense episode in the same period in history over the past 20 years. These two extreme SDS events were associated with both atmospheric circulation extremes and local meteorological anomalies that favor enhanced dust emissions in the Gobi Desert.
Ke Gui, Huizheng Che, Yu Zheng, Hujia Zhao, Wenrui Yao, Lei Li, Lei Zhang, Hong Wang, Yaqiang Wang, and Xiaoye Zhang
Atmos. Chem. Phys., 21, 15309–15336, https://doi.org/10.5194/acp-21-15309-2021, https://doi.org/10.5194/acp-21-15309-2021, 2021
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This study utilized the globally gridded aerosol extinction data from CALIOP during 2007–2019 to investigate the 3D climatology, trends, and meteorological drivers of tropospheric type-dependent aerosols. Results revealed that the planetary boundary layer (PBL) and the free troposphere contribute 62.08 % and 37.92 %, respectively, of the global tropospheric TAOD. Trends in
CALIOP-derived aerosol loading, in particular those partitioned in the PBL, can be explained to a large extent by meteorology.
Sunling Gong, Hongli Liu, Bihui Zhang, Jianjun He, Hengde Zhang, Yaqiang Wang, Shuxiao Wang, Lei Zhang, and Jie Wang
Atmos. Chem. Phys., 21, 2999–3013, https://doi.org/10.5194/acp-21-2999-2021, https://doi.org/10.5194/acp-21-2999-2021, 2021
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Surface concentrations of PM2.5 in China have had a declining trend since 2013 across the country. This research found that the control measures of emission reduction are the dominant factors in the PM2.5 declining trends in various regions. The contribution by the meteorology to the surface PM2.5 concentrations from 2013 to 2019 was not found to show a consistent trend, fluctuating positively or negatively by about 5% on the annual average and 10–20% for the fall–winter heavy-pollution seasons.
Lei Zhang, Sunling Gong, Tianliang Zhao, Chunhong Zhou, Yuesi Wang, Jiawei Li, Dongsheng Ji, Jianjun He, Hongli Liu, Ke Gui, Xiaomei Guo, Jinhui Gao, Yunpeng Shan, Hong Wang, Yaqiang Wang, Huizheng Che, and Xiaoye Zhang
Geosci. Model Dev., 14, 703–718, https://doi.org/10.5194/gmd-14-703-2021, https://doi.org/10.5194/gmd-14-703-2021, 2021
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Development of chemical transport models with advanced physics and chemical schemes is important for improving air-quality forecasts. This study develops the chemical module CUACE by updating with a new particle dry deposition scheme and adding heterogenous chemical reactions and couples it with the WRF model. The coupled model (WRF/CUACE) was able to capture well the variations of PM2.5, O3, NO2, and secondary inorganic aerosols in eastern China.
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Short summary
This study established a multi-model simulation system for street-level circulation and pollutant tracking and applied to real building scenarios and atmospheric conditions. Results showed that for a particular site the potential contribution ratio varies with the height of the site, with a peak not at the ground but at a certain height. This work is of significance for urban planning and improvement of urban air quality.
This study established a multi-model simulation system for street-level circulation and...
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