The SMART‐s Trace Gas and Aerosol Inversions: I. Algorithm Theoretical Basis for Column Property Retrievals

The SMART-s (Spectral Measurements for Atmospheric Radiative Transfer—spectroradiometer) acquires Sun/sky observations for retrieving optimal information on trace gases and aerosols with minimal assumptions. Overall, the algorithm of SMART-s incorporates a series of retrievals, from fundamental quan...

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Main Authors: Jeong, Ukkyo, Tsay, Si‐Chee, Giles, David M., Holben, Brent N., Swap, Robert J., Abuhassan, Nader, Herman, Jay
Format: Article in Journal/Newspaper
Language:English
Published: AGU 2020
Subjects:
Online Access:https://dx.doi.org/10.13016/m2goau-9g2n
https://mdsoar.org/handle/11603/24327
id ftdatacite:10.13016/m2goau-9g2n
record_format openpolar
spelling ftdatacite:10.13016/m2goau-9g2n 2023-05-15T13:06:35+02:00 The SMART‐s Trace Gas and Aerosol Inversions: I. Algorithm Theoretical Basis for Column Property Retrievals Jeong, Ukkyo Tsay, Si‐Chee Giles, David M. Holben, Brent N. Swap, Robert J. Abuhassan, Nader Herman, Jay 2020 https://dx.doi.org/10.13016/m2goau-9g2n https://mdsoar.org/handle/11603/24327 en eng AGU Public Domain Mark 1.0 This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C.105, no copyright protection is available for such works under U.S. Law. http://creativecommons.org/publicdomain/mark/1.0/ PDM article CreativeWork 2020 ftdatacite https://doi.org/10.13016/m2goau-9g2n 2022-04-01T08:47:12Z The SMART-s (Spectral Measurements for Atmospheric Radiative Transfer—spectroradiometer) acquires Sun/sky observations for retrieving optimal information on trace gases and aerosols with minimal assumptions. Overall, the algorithm of SMART-s incorporates a series of retrievals, from fundamental quantities (i.e., column abundance of trace gases and aerosol loading) to higher-order geophysical parameters (e.g., aerosol physicochemical properties and vertical profiles), utilizing Sun/sky spectral radiance measurements. This paper describes the theoretical basis for column retrievals of trace gases and aerosols. Associated profile retrievals will be presented in follow-up papers. The current algorithm retrieves the fine/coarse mode of the particle size distribution and spectral complex index of refraction and, thereby, the spectral aerosol single-scattering albedo ω0. SMART-s retrieval is unique particularly in its high spectral resolution of the complex index of refraction and ω0 from near-ultraviolet to near-infrared wavelengths, which is pivotal information for atmospheric chemistry, climate and other inversions. We theoretically assessed information content and retrieval accuracy of the algorithm and compared different type of measurements including the Aerosol Robotic Network (AERONET) and standard Pandora. For the same levels of radiometric accuracy, SMART-s measurements provide the most informative aerosol retrievals based on theoretical error analyses. Higher spectral resolution measurements are particularly beneficial for particle size distribution and fine-mode refractive index retrievals. We applied this algorithm to the AERONET Sun/sky measurements at Kanpur, India, in 2016 to assess algorithm consistency. Even with different assumptions and numerical methods for the inversion, SMART-s retrieved aerosol parameters agreed well with the AERONET operational products (e.g., absolute mean bias errors less than 0.01 for ω₀). Article in Journal/Newspaper Aerosol Robotic Network DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
description The SMART-s (Spectral Measurements for Atmospheric Radiative Transfer—spectroradiometer) acquires Sun/sky observations for retrieving optimal information on trace gases and aerosols with minimal assumptions. Overall, the algorithm of SMART-s incorporates a series of retrievals, from fundamental quantities (i.e., column abundance of trace gases and aerosol loading) to higher-order geophysical parameters (e.g., aerosol physicochemical properties and vertical profiles), utilizing Sun/sky spectral radiance measurements. This paper describes the theoretical basis for column retrievals of trace gases and aerosols. Associated profile retrievals will be presented in follow-up papers. The current algorithm retrieves the fine/coarse mode of the particle size distribution and spectral complex index of refraction and, thereby, the spectral aerosol single-scattering albedo ω0. SMART-s retrieval is unique particularly in its high spectral resolution of the complex index of refraction and ω0 from near-ultraviolet to near-infrared wavelengths, which is pivotal information for atmospheric chemistry, climate and other inversions. We theoretically assessed information content and retrieval accuracy of the algorithm and compared different type of measurements including the Aerosol Robotic Network (AERONET) and standard Pandora. For the same levels of radiometric accuracy, SMART-s measurements provide the most informative aerosol retrievals based on theoretical error analyses. Higher spectral resolution measurements are particularly beneficial for particle size distribution and fine-mode refractive index retrievals. We applied this algorithm to the AERONET Sun/sky measurements at Kanpur, India, in 2016 to assess algorithm consistency. Even with different assumptions and numerical methods for the inversion, SMART-s retrieved aerosol parameters agreed well with the AERONET operational products (e.g., absolute mean bias errors less than 0.01 for ω₀).
format Article in Journal/Newspaper
author Jeong, Ukkyo
Tsay, Si‐Chee
Giles, David M.
Holben, Brent N.
Swap, Robert J.
Abuhassan, Nader
Herman, Jay
spellingShingle Jeong, Ukkyo
Tsay, Si‐Chee
Giles, David M.
Holben, Brent N.
Swap, Robert J.
Abuhassan, Nader
Herman, Jay
The SMART‐s Trace Gas and Aerosol Inversions: I. Algorithm Theoretical Basis for Column Property Retrievals
author_facet Jeong, Ukkyo
Tsay, Si‐Chee
Giles, David M.
Holben, Brent N.
Swap, Robert J.
Abuhassan, Nader
Herman, Jay
author_sort Jeong, Ukkyo
title The SMART‐s Trace Gas and Aerosol Inversions: I. Algorithm Theoretical Basis for Column Property Retrievals
title_short The SMART‐s Trace Gas and Aerosol Inversions: I. Algorithm Theoretical Basis for Column Property Retrievals
title_full The SMART‐s Trace Gas and Aerosol Inversions: I. Algorithm Theoretical Basis for Column Property Retrievals
title_fullStr The SMART‐s Trace Gas and Aerosol Inversions: I. Algorithm Theoretical Basis for Column Property Retrievals
title_full_unstemmed The SMART‐s Trace Gas and Aerosol Inversions: I. Algorithm Theoretical Basis for Column Property Retrievals
title_sort smart‐s trace gas and aerosol inversions: i. algorithm theoretical basis for column property retrievals
publisher AGU
publishDate 2020
url https://dx.doi.org/10.13016/m2goau-9g2n
https://mdsoar.org/handle/11603/24327
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_rights Public Domain Mark 1.0
This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C.105, no copyright protection is available for such works under U.S. Law.
http://creativecommons.org/publicdomain/mark/1.0/
op_rightsnorm PDM
op_doi https://doi.org/10.13016/m2goau-9g2n
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