Articles | Volume 15, issue 4
https://doi.org/10.5194/gmd-15-1821-2022
© 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-15-1821-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
03 Mar 2022
Development and technical paper |
| 03 Mar 2022
| 03 Mar 2022
A three-dimensional variational data assimilation system for aerosol optical properties based on WRF-Chem v4.0: design, development, and application of assimilating Himawari-8 aerosol observations
Daichun Wang
College of Meteorology and Oceanography, National University of
Defense Technology, Changsha, 410005, China
Wei You
CORRESPONDING AUTHOR
College of Meteorology and Oceanography, National University of
Defense Technology, Changsha, 410005, China
Zengliang Zang
College of Meteorology and Oceanography, National University of
Defense Technology, Changsha, 410005, China
Xiaobin Pan
College of Meteorology and Oceanography, National University of
Defense Technology, Changsha, 410005, China
Yiwen Hu
College of Meteorology and Oceanography, National University of
Defense Technology, Changsha, 410005, China
School of Atmospheric Physics, Nanjing University of Information
Science & Technology, Nanjing, 211101, China
Yanfei Liang
College of Meteorology and Oceanography, National University of
Defense Technology, Changsha, 410005, China
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Cited
18 citations as recorded by crossref.
- Optimizing the Numerical Simulation of the Dust Event of March 2021: Integrating Aerosol Observations through Multi-Scale 3D Variational Assimilation in the WRF-Chem Model S. Mei et al. 10.3390/rs16111852
- 基于高分辨率气溶胶观测资料的多尺度三维变分同化及预报 增. 臧 et al. 10.1360/SSTe-2022-0026
- Multi-scale three-dimensional variational data assimilation for high-resolution aerosol observations: Methodology and application Z. Zang et al. 10.1007/s11430-022-9974-4
- Health impact reduction design strategies according to the circulation pattern of indoor PM 2.5 using computational fluid dynamics models R. Zhang et al. 10.1177/1420326X251324368
- Multisource Remote Sensing Based Estimation of Soil NOx Emissions From Fertilized Cropland at High‐Resolution: Spatio‐Temporal Patterns and Impacts Y. Shen et al. 10.1029/2022JD036741
- Further development and application of the WRFDA-Chem three-dimensional variational (3DVAR) system: Joint assimilation of satellite AOD retrievals and surface observations Y. Zhou et al. 10.1016/j.atmosres.2025.107942
- Improvement of the Aerosol Forecast and Analysis Over East Asia With Joint Assimilation of Two Geostationary Satellite Observations Y. Cheng et al. 10.1029/2022GL099908
- 3DVAR Aerosol Data Assimilation and Evaluation Using Surface PM2.5, Himawari-8 AOD and CALIPSO Profile Observations in the North China Z. Zang et al. 10.3390/rs14164009
- Four-dimensional variational assimilation for SO2 emission and its application around the COVID-19 lockdown in the spring 2020 over China Y. Hu et al. 10.5194/acp-22-13183-2022
- Sensitivity and uncertainties assessment in radiative forcing due to aerosol optical properties in diverse locations in China F. Lu et al. 10.1016/j.scitotenv.2022.160447
- Development of a three-dimensional variational data assimilation system for 137Cs based on WRF-Chem model and applied to the Fukushima nuclear accident Y. Hu et al. 10.1088/2515-7620/ad7a5f
- Effects of joint assimilation of FY-4A AGRI and ground-based microwave radiometer on heavy rainfall prediction Y. Shi et al. 10.3389/fenvs.2023.1083517
- Spatial analysis of particulate matter (PM10) using MODIS aerosol optical thickness observations and GIS over East Malaysia A. Najim et al. 10.1016/j.ejrs.2023.03.001
- Chemical servoing with hexapod robot for gas source localization and YOLO-based visual defect detection G. Morin-Duponchelle et al. 10.1007/s41315-025-00464-0
- Improving Clear-Sky Solar Power Prediction over China by Assimilating Himawari-8 Aerosol Optical Depth with WRF-Chem-Solar S. Wang et al. 10.3390/rs14194990
- Aerosol optical properties and its direct radiative forcing over Tibetan Plateau from 2006 to 2017 H. Bi et al. 10.1016/j.partic.2022.05.007
- Impacts of Fengyun-4A and Ground-Based Observation Data Assimilation on the Forecast of Kaifeng’s Heavy Rainfall (2022) and Mechanism Analysis of the Event J. Zhang et al. 10.3390/rs16101663
- Exploring radiative forcing sensitivity to aerosol optical properties across varied geographical regions in India S. Gautam et al. 10.1007/s11869-024-01537-y
18 citations as recorded by crossref.
- Optimizing the Numerical Simulation of the Dust Event of March 2021: Integrating Aerosol Observations through Multi-Scale 3D Variational Assimilation in the WRF-Chem Model S. Mei et al. 10.3390/rs16111852
- 基于高分辨率气溶胶观测资料的多尺度三维变分同化及预报 增. 臧 et al. 10.1360/SSTe-2022-0026
- Multi-scale three-dimensional variational data assimilation for high-resolution aerosol observations: Methodology and application Z. Zang et al. 10.1007/s11430-022-9974-4
- Health impact reduction design strategies according to the circulation pattern of indoor PM 2.5 using computational fluid dynamics models R. Zhang et al. 10.1177/1420326X251324368
- Multisource Remote Sensing Based Estimation of Soil NOx Emissions From Fertilized Cropland at High‐Resolution: Spatio‐Temporal Patterns and Impacts Y. Shen et al. 10.1029/2022JD036741
- Further development and application of the WRFDA-Chem three-dimensional variational (3DVAR) system: Joint assimilation of satellite AOD retrievals and surface observations Y. Zhou et al. 10.1016/j.atmosres.2025.107942
- Improvement of the Aerosol Forecast and Analysis Over East Asia With Joint Assimilation of Two Geostationary Satellite Observations Y. Cheng et al. 10.1029/2022GL099908
- 3DVAR Aerosol Data Assimilation and Evaluation Using Surface PM2.5, Himawari-8 AOD and CALIPSO Profile Observations in the North China Z. Zang et al. 10.3390/rs14164009
- Four-dimensional variational assimilation for SO2 emission and its application around the COVID-19 lockdown in the spring 2020 over China Y. Hu et al. 10.5194/acp-22-13183-2022
- Sensitivity and uncertainties assessment in radiative forcing due to aerosol optical properties in diverse locations in China F. Lu et al. 10.1016/j.scitotenv.2022.160447
- Development of a three-dimensional variational data assimilation system for 137Cs based on WRF-Chem model and applied to the Fukushima nuclear accident Y. Hu et al. 10.1088/2515-7620/ad7a5f
- Effects of joint assimilation of FY-4A AGRI and ground-based microwave radiometer on heavy rainfall prediction Y. Shi et al. 10.3389/fenvs.2023.1083517
- Spatial analysis of particulate matter (PM10) using MODIS aerosol optical thickness observations and GIS over East Malaysia A. Najim et al. 10.1016/j.ejrs.2023.03.001
- Chemical servoing with hexapod robot for gas source localization and YOLO-based visual defect detection G. Morin-Duponchelle et al. 10.1007/s41315-025-00464-0
- Improving Clear-Sky Solar Power Prediction over China by Assimilating Himawari-8 Aerosol Optical Depth with WRF-Chem-Solar S. Wang et al. 10.3390/rs14194990
- Aerosol optical properties and its direct radiative forcing over Tibetan Plateau from 2006 to 2017 H. Bi et al. 10.1016/j.partic.2022.05.007
- Impacts of Fengyun-4A and Ground-Based Observation Data Assimilation on the Forecast of Kaifeng’s Heavy Rainfall (2022) and Mechanism Analysis of the Event J. Zhang et al. 10.3390/rs16101663
- Exploring radiative forcing sensitivity to aerosol optical properties across varied geographical regions in India S. Gautam et al. 10.1007/s11869-024-01537-y
Latest update: 03 Jul 2025
Short summary
This paper presents a 3D variational data assimilation system for aerosol optical properties, including aerosol optical thickness (AOT) retrievals and lidar-based aerosol profiles, which was developed for a size-resolved sectional model in WRF-Chem. To directly assimilate aerosol optical properties, an observation operator based on the Mie scattering theory was designed. The results show that Himawari-8 AOT assimilation can significantly improve model aerosol analyses and forecasts.
This paper presents a 3D variational data assimilation system for aerosol optical properties,...
