An Empirical Parameterization to Separate Coarse and Fine Mode Aerosol Optical Depth Over Land
Retrieving the fine‐mode fraction (FMF) of aerosol optical depth from satellite data is crucial for understanding the impact of natural versus anthropogenic aerosols on climate and air quality. However, few high‐quality global FMF products from MODIS exist. To address this gap, this study derives a...
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| Veröffentlicht in: | Geophysical research letters Jg. 52; H. 6 |
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| Abstract | Retrieving the fine‐mode fraction (FMF) of aerosol optical depth from satellite data is crucial for understanding the impact of natural versus anthropogenic aerosols on climate and air quality. However, few high‐quality global FMF products from MODIS exist. To address this gap, this study derives a new formulation of FMF as a function of the Ångström exponent (AE) based on over 20 years of AERONET measurements. Our results reveal a consistent FMF‐AE relationship across continental regions, supporting the feasibility of globally estimating FMF through a simple empirical function based on AE. Validation with independent NOAA GML data sets shows predicted FMF errors mostly within 0.1. Finally, applying this parameterization to MODIS Aqua and Terra data significantly improved satellite‐derived FMF agreement with AERONET compared to previous derivations. This parameterization provides a simple, valuable tool for accurately deriving FMF over land from MODIS and understanding its impact on climate and air quality.
Plain Language Summary
Aerosols are liquid and solid particles suspended in the atmosphere, with sizes ranging from a few nanometers to tens of micrometers. These particles, produced by natural sources or human activities, play a significant role in air quality and climate. Estimating aerosol size distributions is important for understanding their climate and environmental impacts. However this remains challenging on regional and global scales due to the difficulties in retrieving this information from satellite observations. To address this, we created a parameterization that predicts the fraction of fine particles based on the measured spectral variation of light extinction by aerosols, known as the Ångström exponent (AE). By analyzing 20 years of ground‐based sunphotometer data, we found a reliable pattern between AE and fine particle fraction. We then tested this method with in situ nephelometer data, and confirmed its accuracy. Finally, we applied our formula to satellite data, achieving better agreement with ground‐based observations compared to previous parameterization efforts. Our formula can help scientists understand air pollution and its climate effects more accurately using satellite and ground‐based data independently of location.
Key Points
A parameterization linking the fine‐mode fraction of aerosol optical depth to the Angstrom exponent was developed using AERONET data
Validation of this parameterization with independent in situ nephelometer measurements demonstrates strong predictive capability
Applying this parameterization to MODIS satellite data improves the predictive accuracy for fine‐ and coarse‐mode aerosol optical depth |
|---|---|
| AbstractList | Retrieving the fine‐mode fraction (FMF) of aerosol optical depth from satellite data is crucial for understanding the impact of natural versus anthropogenic aerosols on climate and air quality. However, few high‐quality global FMF products from MODIS exist. To address this gap, this study derives a new formulation of FMF as a function of the Ångström exponent (AE) based on over 20 years of AERONET measurements. Our results reveal a consistent FMF‐AE relationship across continental regions, supporting the feasibility of globally estimating FMF through a simple empirical function based on AE. Validation with independent NOAA GML data sets shows predicted FMF errors mostly within 0.1. Finally, applying this parameterization to MODIS Aqua and Terra data significantly improved satellite‐derived FMF agreement with AERONET compared to previous derivations. This parameterization provides a simple, valuable tool for accurately deriving FMF over land from MODIS and understanding its impact on climate and air quality.
Plain Language Summary
Aerosols are liquid and solid particles suspended in the atmosphere, with sizes ranging from a few nanometers to tens of micrometers. These particles, produced by natural sources or human activities, play a significant role in air quality and climate. Estimating aerosol size distributions is important for understanding their climate and environmental impacts. However this remains challenging on regional and global scales due to the difficulties in retrieving this information from satellite observations. To address this, we created a parameterization that predicts the fraction of fine particles based on the measured spectral variation of light extinction by aerosols, known as the Ångström exponent (AE). By analyzing 20 years of ground‐based sunphotometer data, we found a reliable pattern between AE and fine particle fraction. We then tested this method with in situ nephelometer data, and confirmed its accuracy. Finally, we applied our formula to satellite data, achieving better agreement with ground‐based observations compared to previous parameterization efforts. Our formula can help scientists understand air pollution and its climate effects more accurately using satellite and ground‐based data independently of location.
Key Points
A parameterization linking the fine‐mode fraction of aerosol optical depth to the Angstrom exponent was developed using AERONET data
Validation of this parameterization with independent in situ nephelometer measurements demonstrates strong predictive capability
Applying this parameterization to MODIS satellite data improves the predictive accuracy for fine‐ and coarse‐mode aerosol optical depth Retrieving the fine‐mode fraction (FMF) of aerosol optical depth from satellite data is crucial for understanding the impact of natural versus anthropogenic aerosols on climate and air quality. However, few high‐quality global FMF products from MODIS exist. To address this gap, this study derives a new formulation of FMF as a function of the Ångström exponent (AE) based on over 20 years of AERONET measurements. Our results reveal a consistent FMF‐AE relationship across continental regions, supporting the feasibility of globally estimating FMF through a simple empirical function based on AE. Validation with independent NOAA GML data sets shows predicted FMF errors mostly within 0.1. Finally, applying this parameterization to MODIS Aqua and Terra data significantly improved satellite‐derived FMF agreement with AERONET compared to previous derivations. This parameterization provides a simple, valuable tool for accurately deriving FMF over land from MODIS and understanding its impact on climate and air quality. Abstract Retrieving the fine‐mode fraction (FMF) of aerosol optical depth from satellite data is crucial for understanding the impact of natural versus anthropogenic aerosols on climate and air quality. However, few high‐quality global FMF products from MODIS exist. To address this gap, this study derives a new formulation of FMF as a function of the Ångström exponent (AE) based on over 20 years of AERONET measurements. Our results reveal a consistent FMF‐AE relationship across continental regions, supporting the feasibility of globally estimating FMF through a simple empirical function based on AE. Validation with independent NOAA GML data sets shows predicted FMF errors mostly within 0.1. Finally, applying this parameterization to MODIS Aqua and Terra data significantly improved satellite‐derived FMF agreement with AERONET compared to previous derivations. This parameterization provides a simple, valuable tool for accurately deriving FMF over land from MODIS and understanding its impact on climate and air quality. Retrieving the fine‐mode fraction (FMF) of aerosol optical depth from satellite data is crucial for understanding the impact of natural versus anthropogenic aerosols on climate and air quality. However, few high‐quality global FMF products from MODIS exist. To address this gap, this study derives a new formulation of FMF as a function of the Ångström exponent (AE) based on over 20 years of AERONET measurements. Our results reveal a consistent FMF‐AE relationship across continental regions, supporting the feasibility of globally estimating FMF through a simple empirical function based on AE. Validation with independent NOAA GML data sets shows predicted FMF errors mostly within 0.1. Finally, applying this parameterization to MODIS Aqua and Terra data significantly improved satellite‐derived FMF agreement with AERONET compared to previous derivations. This parameterization provides a simple, valuable tool for accurately deriving FMF over land from MODIS and understanding its impact on climate and air quality. Aerosols are liquid and solid particles suspended in the atmosphere, with sizes ranging from a few nanometers to tens of micrometers. These particles, produced by natural sources or human activities, play a significant role in air quality and climate. Estimating aerosol size distributions is important for understanding their climate and environmental impacts. However this remains challenging on regional and global scales due to the difficulties in retrieving this information from satellite observations. To address this, we created a parameterization that predicts the fraction of fine particles based on the measured spectral variation of light extinction by aerosols, known as the Ångström exponent (AE). By analyzing 20 years of ground‐based sunphotometer data, we found a reliable pattern between AE and fine particle fraction. We then tested this method with in situ nephelometer data, and confirmed its accuracy. Finally, we applied our formula to satellite data, achieving better agreement with ground‐based observations compared to previous parameterization efforts. Our formula can help scientists understand air pollution and its climate effects more accurately using satellite and ground‐based data independently of location. A parameterization linking the fine‐mode fraction of aerosol optical depth to the Angstrom exponent was developed using AERONET data Validation of this parameterization with independent in situ nephelometer measurements demonstrates strong predictive capability Applying this parameterization to MODIS satellite data improves the predictive accuracy for fine‐ and coarse‐mode aerosol optical depth |
| Author | Li, Xiaohan Ginoux, Paul |
| Author_xml | – sequence: 1 givenname: Xiaohan orcidid: 0000-0003-2370-576X surname: Li fullname: Li, Xiaohan email: xiaohanl@princeton.edu organization: Princeton University – sequence: 2 givenname: Paul orcidid: 0000-0003-3642-2988 surname: Ginoux fullname: Ginoux, Paul organization: NOAA Geophysical Fluid Dynamics Laboratory |
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| SubjectTerms | AERONET aerosol Aerosol optical depth Aerosols Air pollution Air quality Anthropogenic factors AOD Climate Climate effects Environmental impact FMF Human influences Information retrieval MODIS Nephelometers Optical analysis Optical thickness Outdoor air quality Parameterization Satellite data Satellite observation Satellites |
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| Title | An Empirical Parameterization to Separate Coarse and Fine Mode Aerosol Optical Depth Over Land |
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