Articles | Volume 15, issue 9
https://doi.org/10.5194/gmd-15-3555-2022
© 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/gmd-15-3555-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An aerosol vertical data assimilation system (NAQPMS-PDAF v1.0): development and application
Haibo Wang
The State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
College of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing 100029, China
The State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
Zifa Wang
CORRESPONDING AUTHOR
The State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
College of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing 100029, China
Jianjun Li
China National Environmental Monitoring Centre, Beijing, China
Wenxuan Chai
China National Environmental Monitoring Centre, Beijing, China
Guigang Tang
China National Environmental Monitoring Centre, Beijing, China
The State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
College of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing 100029, China
Xueshun Chen
The State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
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Cited
10 citations as recorded by crossref.
- Algorithm for vertical distribution of boundary layer aerosol components in remote-sensing data F. Wang et al. 10.5194/amt-15-6127-2022
- TEMDI: A Temporal Enhanced Multisource Data Integration model for accurate PM2.5 concentration forecasting K. Ren et al. 10.1016/j.apr.2024.102269
- Short-Term Relationship Between Air Pollution and Mortality from Respiratory and Cardiovascular Diseases in China, 2008–2020 Y. Liu et al. 10.3390/toxics13030156
- Remotely Sensed Soil Moisture Assimilation in the Distributed Hydrological Model Based on the Error Subspace Transform Kalman Filter Y. Li et al. 10.3390/rs15071852
- Next Generation Air Quality Models: Dynamical Mesh, New Insights into Mechanism, Datasets and Applications J. Li et al. 10.1007/s40726-025-00355-9
- Strong Impacts of Regional Atmospheric Transport on the Vertical Distribution of Aerosol Ammonium over Beijing T. Yang et al. 10.1021/acs.estlett.3c00791
- Investigate the important role of 3-D meteorological patterns in haze formation in the context of pollution reduction M. Lu et al. 10.1016/j.atmosres.2024.107843
- The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2 M. Pang et al. 10.5194/gmd-18-3781-2025
- A Study of Air Quality Modeling Based on Transportation Sources through Bibliometric Analysis R. Eko Handriyono et al. 10.1088/1755-1315/1448/1/012008
- NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components H. Li et al. 10.5194/gmd-17-8495-2024
10 citations as recorded by crossref.
- Algorithm for vertical distribution of boundary layer aerosol components in remote-sensing data F. Wang et al. 10.5194/amt-15-6127-2022
- TEMDI: A Temporal Enhanced Multisource Data Integration model for accurate PM2.5 concentration forecasting K. Ren et al. 10.1016/j.apr.2024.102269
- Short-Term Relationship Between Air Pollution and Mortality from Respiratory and Cardiovascular Diseases in China, 2008–2020 Y. Liu et al. 10.3390/toxics13030156
- Remotely Sensed Soil Moisture Assimilation in the Distributed Hydrological Model Based on the Error Subspace Transform Kalman Filter Y. Li et al. 10.3390/rs15071852
- Next Generation Air Quality Models: Dynamical Mesh, New Insights into Mechanism, Datasets and Applications J. Li et al. 10.1007/s40726-025-00355-9
- Strong Impacts of Regional Atmospheric Transport on the Vertical Distribution of Aerosol Ammonium over Beijing T. Yang et al. 10.1021/acs.estlett.3c00791
- Investigate the important role of 3-D meteorological patterns in haze formation in the context of pollution reduction M. Lu et al. 10.1016/j.atmosres.2024.107843
- The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2 M. Pang et al. 10.5194/gmd-18-3781-2025
- A Study of Air Quality Modeling Based on Transportation Sources through Bibliometric Analysis R. Eko Handriyono et al. 10.1088/1755-1315/1448/1/012008
- NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components H. Li et al. 10.5194/gmd-17-8495-2024
Latest update: 30 Jun 2025
Short summary
In this paper, we develop an online data coupled assimilation system (NAQPMS-PDAF) with the Eulerian atmospheric chemistry-transport model. NAQPMS-PDAF allows efficient use of large computational resources. The application and performance of the system are investigated by assimilating 1 month of vertical aerosol observations. The results show that NAQPMS-PDAF can significantly improve the performance of aerosol vertical structure simulation and reduce the uncertainty to a large extent.
In this paper, we develop an online data coupled assimilation system (NAQPMS-PDAF) with the...