How aerosol size matters in aerosol optical depth (AOD) assimilation and the optimization using the Ångström exponent

Satellite-based aerosol optical depth (AOD) has gained popularity as a powerful data source for calibrating aerosol models and correcting model errors through data assimilation. However, simulated airborne particle mass concentrations are not directly comparable to satellite-based AODs. For this, an...

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Published in:Atmospheric Chemistry and Physics
Main Authors: Jin, Jianbing, Henzing, Bas, Segers, Arjo
Format: Text
Language:English
Published: 2023
Subjects:
Online Access:https://doi.org/10.5194/acp-23-1641-2023
https://acp.copernicus.org/articles/23/1641/2023/
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spelling ftcopernicus:oai:publications.copernicus.org:acp106211 2023-05-15T13:06:36+02:00 How aerosol size matters in aerosol optical depth (AOD) assimilation and the optimization using the Ångström exponent Jin, Jianbing Henzing, Bas Segers, Arjo 2023-01-27 application/pdf https://doi.org/10.5194/acp-23-1641-2023 https://acp.copernicus.org/articles/23/1641/2023/ eng eng doi:10.5194/acp-23-1641-2023 https://acp.copernicus.org/articles/23/1641/2023/ eISSN: 1680-7324 Text 2023 ftcopernicus https://doi.org/10.5194/acp-23-1641-2023 2023-01-30T17:22:42Z Satellite-based aerosol optical depth (AOD) has gained popularity as a powerful data source for calibrating aerosol models and correcting model errors through data assimilation. However, simulated airborne particle mass concentrations are not directly comparable to satellite-based AODs. For this, an AOD operator needs to be developed that can convert the simulated mass concentrations into model AODs. The AOD operator is most sensitive to the input of the particle size and chemical composition of aerosols. Furthermore, assumptions regarding particle size vary significantly amongst model AOD operators. More importantly, satellite retrieval algorithms rely on different size assumptions. Consequently, the differences between the simulations and observations do not always reflect the actual difference in aerosol amount. In this study, the sensitivity of the AOD operator to aerosol properties has been explored. We conclude that, to avoid inconsistencies between the AOD operator and retrieved properties, a common understanding of the particle size is required. Accordingly, we designed a hybrid assimilation methodology ( hybrid AOD assimilation) that includes two sequentially conducted procedures. First, aerosol size in the model operator has been brought closer to the assumption of the satellite retrieval algorithm via assimilation of Ångström exponents. This ensures that the model AOD operator is more consistent with the AOD retrieval. The second step in the methodology concerns optimization of aerosol mass concentrations through direct assimilation of AOD ( standard AOD assimilation). The hybrid assimilation method is tested over the European domain using Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue products. The corrections made to the model aerosol size information are validated through a comparison with the ground-based Aerosol Robotic Network (AERONET) optical product. The increments in surface aerosol mass concentration that occur due to either the standard AOD assimilation analysis or the ... Text Aerosol Robotic Network Copernicus Publications: E-Journals Atmospheric Chemistry and Physics 23 2 1641 1660
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language English
description Satellite-based aerosol optical depth (AOD) has gained popularity as a powerful data source for calibrating aerosol models and correcting model errors through data assimilation. However, simulated airborne particle mass concentrations are not directly comparable to satellite-based AODs. For this, an AOD operator needs to be developed that can convert the simulated mass concentrations into model AODs. The AOD operator is most sensitive to the input of the particle size and chemical composition of aerosols. Furthermore, assumptions regarding particle size vary significantly amongst model AOD operators. More importantly, satellite retrieval algorithms rely on different size assumptions. Consequently, the differences between the simulations and observations do not always reflect the actual difference in aerosol amount. In this study, the sensitivity of the AOD operator to aerosol properties has been explored. We conclude that, to avoid inconsistencies between the AOD operator and retrieved properties, a common understanding of the particle size is required. Accordingly, we designed a hybrid assimilation methodology ( hybrid AOD assimilation) that includes two sequentially conducted procedures. First, aerosol size in the model operator has been brought closer to the assumption of the satellite retrieval algorithm via assimilation of Ångström exponents. This ensures that the model AOD operator is more consistent with the AOD retrieval. The second step in the methodology concerns optimization of aerosol mass concentrations through direct assimilation of AOD ( standard AOD assimilation). The hybrid assimilation method is tested over the European domain using Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue products. The corrections made to the model aerosol size information are validated through a comparison with the ground-based Aerosol Robotic Network (AERONET) optical product. The increments in surface aerosol mass concentration that occur due to either the standard AOD assimilation analysis or the ...
format Text
author Jin, Jianbing
Henzing, Bas
Segers, Arjo
spellingShingle Jin, Jianbing
Henzing, Bas
Segers, Arjo
How aerosol size matters in aerosol optical depth (AOD) assimilation and the optimization using the Ångström exponent
author_facet Jin, Jianbing
Henzing, Bas
Segers, Arjo
author_sort Jin, Jianbing
title How aerosol size matters in aerosol optical depth (AOD) assimilation and the optimization using the Ångström exponent
title_short How aerosol size matters in aerosol optical depth (AOD) assimilation and the optimization using the Ångström exponent
title_full How aerosol size matters in aerosol optical depth (AOD) assimilation and the optimization using the Ångström exponent
title_fullStr How aerosol size matters in aerosol optical depth (AOD) assimilation and the optimization using the Ångström exponent
title_full_unstemmed How aerosol size matters in aerosol optical depth (AOD) assimilation and the optimization using the Ångström exponent
title_sort how aerosol size matters in aerosol optical depth (aod) assimilation and the optimization using the ångström exponent
publishDate 2023
url https://doi.org/10.5194/acp-23-1641-2023
https://acp.copernicus.org/articles/23/1641/2023/
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source eISSN: 1680-7324
op_relation doi:10.5194/acp-23-1641-2023
https://acp.copernicus.org/articles/23/1641/2023/
op_doi https://doi.org/10.5194/acp-23-1641-2023
container_title Atmospheric Chemistry and Physics
container_volume 23
container_issue 2
container_start_page 1641
op_container_end_page 1660
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