Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager

Originally developed for the moderate resolution imaging spectroradiometer (MODIS) in polar, sun-synchronous low earth orbit (LEO), the Dark Target (DT) aerosol retrieval algorithm relies on the assumption of a surface reflectance parameterization (SRP) over land surfaces. Specifically for vegetated...

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Published in:Atmospheric Measurement Techniques
Main Authors: M. Kim, R. C. Levy, L. A. Remer, S. Mattoo, P. Gupta
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2024
Subjects:
Online Access:https://doi.org/10.5194/amt-17-1913-2024
https://doaj.org/article/d6b2c4aa03ec4bd0bc90e4aaf591ea1a
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author M. Kim
R. C. Levy
L. A. Remer
S. Mattoo
P. Gupta
author_facet M. Kim
R. C. Levy
L. A. Remer
S. Mattoo
P. Gupta
author_sort M. Kim
collection Directory of Open Access Journals: DOAJ Articles
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container_title Atmospheric Measurement Techniques
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description Originally developed for the moderate resolution imaging spectroradiometer (MODIS) in polar, sun-synchronous low earth orbit (LEO), the Dark Target (DT) aerosol retrieval algorithm relies on the assumption of a surface reflectance parameterization (SRP) over land surfaces. Specifically for vegetated and dark-soiled surfaces, values of surface reflectance in blue and red visible-wavelength bands are assumed to be nearly linearly related to each other and to the value in a shortwave infrared (SWIR) wavelength band. This SRP also includes dependencies on scattering angle and a normalized difference vegetation index computed from two SWIR bands (NDVI SWIR ). As the DT retrieval algorithm is being ported to new sensors to continue and expand the aerosol data record, we assess whether the MODIS-assumed SRP can be used for these sensors. Here, we specifically assess SRP for the Advanced Baseline Imager (ABI) aboard the Geostationary Operational Environmental Satellite (GOES)-16/East (ABIE). First, we find that using MODIS-based SRP leads to higher biases and artificial diurnal signatures in aerosol optical depth (AOD) retrievals from ABIE. The primary reason appears to be that the geostationary orbit (GEO) encounters an entirely different set of observation geometry than does LEO, primarily with regard to solar angles coupled with fixed-view angles. Therefore, we have developed a new SRP for GEO that draws the angular shape of the surface bidirectional reflectance. We also introduce modifications to the parameterization of both red–SWIR and blue–red spectral relationships to include additional information. The revised red–SWIR SRP includes the solar zenith angle, NDVI SWIR , and land-type percentage from an ancillary database. The blue–red SRP adds dependencies on the scattering angle and NDVI SWIR . The new SRPs improve the AOD retrieval of ABIE in terms of overall less bias and mitigation of the overestimation around local noon. The average bias of the DT AOD compared to the Aerosol Robotic Network (AERONET) AOD ...
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spelling ftdoajarticles:oai:doaj.org/article:d6b2c4aa03ec4bd0bc90e4aaf591ea1a 2025-01-16T18:39:07+00:00 Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager M. Kim R. C. Levy L. A. Remer S. Mattoo P. Gupta 2024-04-01T00:00:00Z https://doi.org/10.5194/amt-17-1913-2024 https://doaj.org/article/d6b2c4aa03ec4bd0bc90e4aaf591ea1a EN eng Copernicus Publications https://amt.copernicus.org/articles/17/1913/2024/amt-17-1913-2024.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548 doi:10.5194/amt-17-1913-2024 1867-1381 1867-8548 https://doaj.org/article/d6b2c4aa03ec4bd0bc90e4aaf591ea1a Atmospheric Measurement Techniques, Vol 17, Pp 1913-1939 (2024) Environmental engineering TA170-171 Earthwork. Foundations TA715-787 article 2024 ftdoajarticles https://doi.org/10.5194/amt-17-1913-2024 2024-08-05T17:49:40Z Originally developed for the moderate resolution imaging spectroradiometer (MODIS) in polar, sun-synchronous low earth orbit (LEO), the Dark Target (DT) aerosol retrieval algorithm relies on the assumption of a surface reflectance parameterization (SRP) over land surfaces. Specifically for vegetated and dark-soiled surfaces, values of surface reflectance in blue and red visible-wavelength bands are assumed to be nearly linearly related to each other and to the value in a shortwave infrared (SWIR) wavelength band. This SRP also includes dependencies on scattering angle and a normalized difference vegetation index computed from two SWIR bands (NDVI SWIR ). As the DT retrieval algorithm is being ported to new sensors to continue and expand the aerosol data record, we assess whether the MODIS-assumed SRP can be used for these sensors. Here, we specifically assess SRP for the Advanced Baseline Imager (ABI) aboard the Geostationary Operational Environmental Satellite (GOES)-16/East (ABIE). First, we find that using MODIS-based SRP leads to higher biases and artificial diurnal signatures in aerosol optical depth (AOD) retrievals from ABIE. The primary reason appears to be that the geostationary orbit (GEO) encounters an entirely different set of observation geometry than does LEO, primarily with regard to solar angles coupled with fixed-view angles. Therefore, we have developed a new SRP for GEO that draws the angular shape of the surface bidirectional reflectance. We also introduce modifications to the parameterization of both red–SWIR and blue–red spectral relationships to include additional information. The revised red–SWIR SRP includes the solar zenith angle, NDVI SWIR , and land-type percentage from an ancillary database. The blue–red SRP adds dependencies on the scattering angle and NDVI SWIR . The new SRPs improve the AOD retrieval of ABIE in terms of overall less bias and mitigation of the overestimation around local noon. The average bias of the DT AOD compared to the Aerosol Robotic Network (AERONET) AOD ... Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Atmospheric Measurement Techniques 17 7 1913 1939
spellingShingle Environmental engineering
TA170-171
Earthwork. Foundations
TA715-787
M. Kim
R. C. Levy
L. A. Remer
S. Mattoo
P. Gupta
Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager
title Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager
title_full Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager
title_fullStr Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager
title_full_unstemmed Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager
title_short Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager
title_sort parameterizing spectral surface reflectance relationships for the dark target aerosol algorithm applied to a geostationary imager
topic Environmental engineering
TA170-171
Earthwork. Foundations
TA715-787
topic_facet Environmental engineering
TA170-171
Earthwork. Foundations
TA715-787
url https://doi.org/10.5194/amt-17-1913-2024
https://doaj.org/article/d6b2c4aa03ec4bd0bc90e4aaf591ea1a