Articles | Volume 18, issue 15
https://doi.org/10.5194/gmd-18-4855-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-4855-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
08 Aug 2025
Development and technical paper |
| 08 Aug 2025
| 08 Aug 2025
Development of the CMA-GFS-AERO 4D-Var assimilation system v1.0 – Part 1: System description and preliminary experimental results
Yongzhu Liu
State Key Laboratory of Severe Weather Meteorological Science and Technology, Beijing, 10081, China
CMA Earth System Modeling and Prediction Centre (CEMC), Beijing, 10081, China
Key Laboratory of Earth System Modeling and Prediction, China Meteorological Administration, Beijing, 10081, China
Xiaoye Zhang
CORRESPONDING AUTHOR
State Key Laboratory of Severe Weather Meteorological Science and Technology, Beijing, 10081, China
Chinese Academy of Meteorological Sciences, Beijing, 10081, China
State Key Laboratory of Severe Weather Meteorological Science and Technology, Beijing, 10081, China
CMA Earth System Modeling and Prediction Centre (CEMC), Beijing, 10081, China
Key Laboratory of Earth System Modeling and Prediction, China Meteorological Administration, Beijing, 10081, China
Chao Wang
State Key Laboratory of Severe Weather Meteorological Science and Technology, Beijing, 10081, China
CMA Earth System Modeling and Prediction Centre (CEMC), Beijing, 10081, China
Key Laboratory of Earth System Modeling and Prediction, China Meteorological Administration, Beijing, 10081, China
Wenxing Jia
State Key Laboratory of Severe Weather Meteorological Science and Technology, Beijing, 10081, China
Chinese Academy of Meteorological Sciences, Beijing, 10081, China
Deying Wang
State Key Laboratory of Severe Weather Meteorological Science and Technology, Beijing, 10081, China
Chinese Academy of Meteorological Sciences, Beijing, 10081, China
Zhaorong Zhuang
State Key Laboratory of Severe Weather Meteorological Science and Technology, Beijing, 10081, China
CMA Earth System Modeling and Prediction Centre (CEMC), Beijing, 10081, China
Key Laboratory of Earth System Modeling and Prediction, China Meteorological Administration, Beijing, 10081, China
Xueshun Shen
CORRESPONDING AUTHOR
State Key Laboratory of Severe Weather Meteorological Science and Technology, Beijing, 10081, China
CMA Earth System Modeling and Prediction Centre (CEMC), Beijing, 10081, China
Key Laboratory of Earth System Modeling and Prediction, China Meteorological Administration, Beijing, 10081, China
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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
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Li Fang, Jianbing Jin, Arjo Segers, Hong Liao, Ke Li, Bufan Xu, Wei Han, Mijie Pang, and Hai Xiang Lin
Geosci. Model Dev., 16, 4867–4882, https://doi.org/10.5194/gmd-16-4867-2023, https://doi.org/10.5194/gmd-16-4867-2023, 2023
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Machine learning models have gained great popularity in air quality prediction. However, they are only available at air quality monitoring stations. In contrast, chemical transport models (CTM) provide predictions that are continuous in the 3D field. Owing to complex error sources, they are typically biased. In this study, we proposed a gridded prediction with high accuracy by fusing predictions from our regional feature selection machine learning prediction (RFSML v1.0) and a CTM prediction.
Yue Peng, Hong Wang, Xiaoye Zhang, Zhaodong Liu, Wenjie Zhang, Siting Li, Chen Han, and Huizheng Che
Atmos. Chem. Phys., 23, 8325–8339, https://doi.org/10.5194/acp-23-8325-2023, https://doi.org/10.5194/acp-23-8325-2023, 2023
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This study demonstrates a strong link between local circulation, aerosol–radiation interaction (ARI), and haze pollution. Under the weak weather-scale systems, the typical local circulation driven by mountainous topography is the main cause of pollutant distribution in the Beijing–Tianjin–Hebei region, and the ARI mechanism amplifies this influence of local circulation on pollutants, making haze pollution aggravated by the superposition of both.
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.
Xiaojing Shen, Junying Sun, Huizheng Che, Yangmei Zhang, Chunhong Zhou, Ke Gui, Wanyun Xu, Quan Liu, Junting Zhong, Can Xia, Xinyao Hu, Sinan Zhang, Jialing Wang, Shuo Liu, Jiayuan Lu, Aoyuan Yu, and Xiaoye Zhang
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Li Liu, Chao Sun, Xinzhu Yu, Hao Yu, Qingu Jiang, Xingliang Li, Ruizhe Li, Bin Wang, Xueshun Shen, and Guangwen Yang
Geosci. Model Dev., 16, 2833–2850, https://doi.org/10.5194/gmd-16-2833-2023, https://doi.org/10.5194/gmd-16-2833-2023, 2023
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C-Coupler3.0 is an integrated coupler infrastructure with new features, i.e. a series of parallel-optimization technologies, a common halo-exchange library, a common module-integration framework, a common framework for conveniently developing a weakly coupled ensemble data assimilation system, and a common framework for flexibly inputting and outputting fields in parallel. It is able to handle coupling under much finer resolutions (e.g. more than 100 million horizontal grid cells).
Xinyao Hu, Junying Sun, Can Xia, Xiaojing Shen, Yangmei Zhang, Quan Liu, Zhaodong Liu, Sinan Zhang, Jialing Wang, Aoyuan Yu, Jiayuan Lu, Shuo Liu, and Xiaoye Zhang
Atmos. Chem. Phys., 23, 5517–5531, https://doi.org/10.5194/acp-23-5517-2023, https://doi.org/10.5194/acp-23-5517-2023, 2023
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The simultaneous measurements under dry conditions of aerosol optical properties were conducted at three wavelengths for PM1 and PM10 in urban Beijing from 2018 to 2021. Considerable reductions in aerosol absorption coefficient and increased single scattering albedo demonstrated that absorbing aerosols were more effectively controlled than scattering aerosols due to pollution control measures. The aerosol radiative effect and the transport's impact on aerosol optical properties were analysed.
Yingfang Li, Zhili Wang, Yadong Lei, Huizheng Che, and Xiaoye Zhang
Atmos. Chem. Phys., 23, 2499–2523, https://doi.org/10.5194/acp-23-2499-2023, https://doi.org/10.5194/acp-23-2499-2023, 2023
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Since few studies have assessed the impacts of future combined reductions in aerosols, ozone, and their precursors on future climate change, we use models with an interactive representation of tropospheric aerosols and atmospheric chemistry schemes to quantify the impact of their reductions on the Asian climate. Our results suggest that their reductions will exacerbate the warming effect caused by greenhouse gases, increasing future climate extremes and associated population exposure risk.
Wenjie Zhang, Hong Wang, Xiaoye Zhang, Liping Huang, Yue Peng, Zhaodong Liu, Xiao Zhang, and Huizheng Che
Atmos. Chem. Phys., 22, 15207–15221, https://doi.org/10.5194/acp-22-15207-2022, https://doi.org/10.5194/acp-22-15207-2022, 2022
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Aerosol–cloud interaction (ACI) is first implemented in the atmospheric chemistry system GRAPES_Meso5.1/CUACE. ACI can improve the simulated cloud, temperature, and precipitation under haze pollution conditions in Jing-Jin-Ji in China. This paper demonstrates the critical role of ACI in current numerical weather prediction over the severely polluted region.
Mengying Li, Shaocai Yu, Xue Chen, Zhen Li, Yibo Zhang, Zhe Song, Weiping Liu, Pengfei Li, Xiaoye Zhang, Meigen Zhang, Yele Sun, Zirui Liu, Caiping Sun, Jingkun Jiang, Shuxiao Wang, Benjamin N. Murphy, Kiran Alapaty, Rohit Mathur, Daniel Rosenfeld, and John H. Seinfeld
Atmos. Chem. Phys., 22, 11845–11866, https://doi.org/10.5194/acp-22-11845-2022, https://doi.org/10.5194/acp-22-11845-2022, 2022
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This study constructed an emission inventory of condensable particulate matter (CPM) in China with a focus on organic aerosols (OAs), based on collected CPM emission information. The results show that OA emissions are enhanced twofold for the years 2014 and 2017 after the inclusion of CPM in the new inventory. Sensitivity cases demonstrated the significant contributions of CPM emissions from stationary combustion and mobile sources to primary, secondary, and total OA concentrations.
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.
Haochi Che, Michal Segal-Rozenhaimer, Lu Zhang, Caroline Dang, Paquita Zuidema, Arthur J. Sedlacek III, Xiaoye Zhang, and Connor Flynn
Atmos. Chem. Phys., 22, 8767–8785, https://doi.org/10.5194/acp-22-8767-2022, https://doi.org/10.5194/acp-22-8767-2022, 2022
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A 17-month in situ study on Ascension Island found low single-scattering albedo and strong absorption enhancement of the marine boundary layer aerosols during biomass burnings on the African continent, along with apparent patterns of regular monthly variability. We further discuss the characteristics and drivers behind these changes and find that biomass burning conditions in Africa may be the main factor influencing the optical properties of marine boundary aerosols.
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.
Jianbing Jin, Mijie Pang, Arjo Segers, Wei Han, Li Fang, Baojie Li, Haochuan Feng, Hai Xiang Lin, and Hong Liao
Atmos. Chem. Phys., 22, 6393–6410, https://doi.org/10.5194/acp-22-6393-2022, https://doi.org/10.5194/acp-22-6393-2022, 2022
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Super dust storms reappeared in East Asia last spring after being absent for one and a half decades. Accurate simulation of such super sandstorms is valuable, but challenging due to imperfect emissions. In this study, the emissions of these dust storms are estimated by assimilating multiple observations. The results reveal that emissions originated from both China and Mongolia. However, for northern China, long-distance transport from Mongolia contributes much more dust than Chinese deserts.
Yu Zheng, Huizheng Che, Yupeng Wang, Xiangao Xia, Xiuqing Hu, Xiaochun Zhang, Jun Zhu, Jibiao Zhu, Hujia Zhao, Lei Li, Ke Gui, and Xiaoye Zhang
Atmos. Meas. Tech., 15, 2139–2158, https://doi.org/10.5194/amt-15-2139-2022, https://doi.org/10.5194/amt-15-2139-2022, 2022
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Ground-based observations of aerosols and aerosol data verification is important for satellite and climate model modification. Here we present an evaluation of aerosol microphysical, optical and radiative properties measured using a multiwavelength photometer with a highly integrated design and smart control performance. The validation of this product is discussed in detail using AERONET as a reference. This work contributes to reducing AOD uncertainties in China and combating climate change.
Wenxing Jia and Xiaoye Zhang
Atmos. Chem. Phys., 21, 16827–16841, https://doi.org/10.5194/acp-21-16827-2021, https://doi.org/10.5194/acp-21-16827-2021, 2021
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Heavy aerosol pollution incidents have attracted much attention since 2013, but the temporal and spatial limitations of observations and the inaccuracy of simulation are a stumbling block to assessing pollution mechanisms. The correct simulation of boundary layer mixing process of pollutant is a challenge for mesoscale numerical models. We add the turbulent diffusion term of aerosol to the WRF-Chem model to prove the impact of turbulent diffusion on pollutant concentration.
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.
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.
Qingyang Xiao, Yixuan Zheng, Guannan Geng, Cuihong Chen, Xiaomeng Huang, Huizheng Che, Xiaoye Zhang, Kebin He, and Qiang Zhang
Atmos. Chem. Phys., 21, 9475–9496, https://doi.org/10.5194/acp-21-9475-2021, https://doi.org/10.5194/acp-21-9475-2021, 2021
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We used both statistical methods and a chemical transport model to assess the contribution of meteorology and emissions to PM2.5 during 2000–2018. Both methods revealed that emissions dominated the long-term PM2.5 trend with notable meteorological effects ranged up to 37.9 % of regional annual average PM2.5. The meteorological contribution became more beneficial to PM2.5 control in southern China but more unfavorable in northern China during the studied period.
Xiaojing Shen, Junying Sun, Fangqun Yu, Ying Wang, Junting Zhong, Yangmei Zhang, Xinyao Hu, Can Xia, Sinan Zhang, and Xiaoye Zhang
Atmos. Chem. Phys., 21, 7039–7052, https://doi.org/10.5194/acp-21-7039-2021, https://doi.org/10.5194/acp-21-7039-2021, 2021
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In this work, we revealed the changes of PNSD and NPF events during the COVID-19 lockdown period in Beijing, China, to illustrate the impact of reduced primary emission and elavated atmospheric oxidized capicity on the nucleation and growth processes. The subsequent growth of nucleated particles and their contribution to the aerosol pollution formation were also explored, to highlight the necessity of controlling the nanoparticles in the future air quality management.
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Short summary
In order to investigate the feedbacks of chemical data assimilation on meteorological forecasts, we developed a strongly coupled aerosol–meteorology four-dimensional variational (4D-Var) assimilation system, CMA-GFS-AERO 4D-Var, based on the framework of the incremental analysis scheme of the China Meteorological Administration Global Forecasting System (CMA-GFS) operational global numerical weather model. The results show that assimilating BC (black carbon) observations can generate analysis increments not only for BC but also for atmospheric variables.
In order to investigate the feedbacks of chemical data assimilation on meteorological forecasts,...
