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
This paper presents a three-dimensional variational (3DVAR) data assimilation (DA) system for aerosol optical properties, including aerosol optical thickness (AOT) retrievals and lidar-based aerosol profiles, developed for the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) within t...
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ftcopernicus:oai:publications.copernicus.org:gmd95730 2023-05-15T13:07:11+02:00 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 Wang, Daichun You, Wei Zang, Zengliang Pan, Xiaobin Hu, Yiwen Liang, Yanfei 2022-03-03 application/pdf https://doi.org/10.5194/gmd-15-1821-2022 https://gmd.copernicus.org/articles/15/1821/2022/ eng eng doi:10.5194/gmd-15-1821-2022 https://gmd.copernicus.org/articles/15/1821/2022/ eISSN: 1991-9603 Text 2022 ftcopernicus https://doi.org/10.5194/gmd-15-1821-2022 2022-03-07T17:22:16Z This paper presents a three-dimensional variational (3DVAR) data assimilation (DA) system for aerosol optical properties, including aerosol optical thickness (AOT) retrievals and lidar-based aerosol profiles, developed for the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) within the Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model. For computational efficiency, 32 model variables in the MOSAIC_4bin scheme are lumped into 20 aerosol state variables that are representative of mass concentrations in the DA system. To directly assimilate aerosol optical properties, an observation operator based on the Mie scattering theory was employed, which was obtained by simplifying the optical module in WRF-Chem. The tangent linear (TL) and adjoint (AD) operators were then established and passed the TL/AD sensitivity test. The Himawari-8 derived AOT data were assimilated to validate the system and investigate the effects of assimilation on both AOT and PM 2.5 simulations. Two comparative experiments were performed with a cycle of 24 h from 23 to 29 November 2018, during which a heavy air pollution event occurred in northern China. The DA performances of the model simulation were evaluated against independent aerosol observations, including the Aerosol Robotic Network (AERONET) AOT and surface PM 2.5 measurements. The results show that Himawari-8 AOT assimilation can significantly improve model AOT analyses and forecasts. Generally, the control experiments without assimilation seriously underestimated AOTs compared with observed values and were therefore unable to describe real aerosol pollution. The analysis fields closer to observations improved AOT simulations, indicating that the system successfully assimilated AOT observations into the model. In terms of statistical metrics, assimilating Himawari-8 AOTs only limitedly improved PM 2.5 analyses in the inner simulation domain (D02); however, the positive effect can last for over 24 h. Assimilation effectively enlarged the underestimated PM 2.5 concentrations to be closer to the real distribution in northern China, which is of great value for studying heavy air pollution events. Text Aerosol Robotic Network Copernicus Publications: E-Journals Geoscientific Model Development 15 4 1821 1840 |
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Copernicus Publications: E-Journals |
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ftcopernicus |
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English |
description |
This paper presents a three-dimensional variational (3DVAR) data assimilation (DA) system for aerosol optical properties, including aerosol optical thickness (AOT) retrievals and lidar-based aerosol profiles, developed for the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) within the Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model. For computational efficiency, 32 model variables in the MOSAIC_4bin scheme are lumped into 20 aerosol state variables that are representative of mass concentrations in the DA system. To directly assimilate aerosol optical properties, an observation operator based on the Mie scattering theory was employed, which was obtained by simplifying the optical module in WRF-Chem. The tangent linear (TL) and adjoint (AD) operators were then established and passed the TL/AD sensitivity test. The Himawari-8 derived AOT data were assimilated to validate the system and investigate the effects of assimilation on both AOT and PM 2.5 simulations. Two comparative experiments were performed with a cycle of 24 h from 23 to 29 November 2018, during which a heavy air pollution event occurred in northern China. The DA performances of the model simulation were evaluated against independent aerosol observations, including the Aerosol Robotic Network (AERONET) AOT and surface PM 2.5 measurements. The results show that Himawari-8 AOT assimilation can significantly improve model AOT analyses and forecasts. Generally, the control experiments without assimilation seriously underestimated AOTs compared with observed values and were therefore unable to describe real aerosol pollution. The analysis fields closer to observations improved AOT simulations, indicating that the system successfully assimilated AOT observations into the model. In terms of statistical metrics, assimilating Himawari-8 AOTs only limitedly improved PM 2.5 analyses in the inner simulation domain (D02); however, the positive effect can last for over 24 h. Assimilation effectively enlarged the underestimated PM 2.5 concentrations to be closer to the real distribution in northern China, which is of great value for studying heavy air pollution events. |
format |
Text |
author |
Wang, Daichun You, Wei Zang, Zengliang Pan, Xiaobin Hu, Yiwen Liang, Yanfei |
spellingShingle |
Wang, Daichun You, Wei Zang, Zengliang Pan, Xiaobin Hu, Yiwen Liang, Yanfei 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 |
author_facet |
Wang, Daichun You, Wei Zang, Zengliang Pan, Xiaobin Hu, Yiwen Liang, Yanfei |
author_sort |
Wang, Daichun |
title |
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 |
title_short |
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 |
title_full |
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 |
title_fullStr |
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 |
title_full_unstemmed |
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 |
title_sort |
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 |
publishDate |
2022 |
url |
https://doi.org/10.5194/gmd-15-1821-2022 https://gmd.copernicus.org/articles/15/1821/2022/ |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
eISSN: 1991-9603 |
op_relation |
doi:10.5194/gmd-15-1821-2022 https://gmd.copernicus.org/articles/15/1821/2022/ |
op_doi |
https://doi.org/10.5194/gmd-15-1821-2022 |
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Geoscientific Model Development |
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15 |
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1821 |
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1840 |
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1766039112223031296 |