The new MISR research aerosol retrieval algorithm: a multi-angle, multi-spectral, bounded-variable least squares retrieval of aerosol particle properties over both land and water

Launched in December 1999, NASA's Multi-angle Imaging SpectroRadiometer (MISR) has given researchers the ability to observe the Earth from nine different views for the last 22 years. Among the many advancements that have since resulted from the launch of MISR is progress in the retrieval of aer...

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Published in:Atmospheric Measurement Techniques
Main Authors: J. A. Limbacher, R. A. Kahn, J. Lee
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2022
Subjects:
Online Access:https://doi.org/10.5194/amt-15-6865-2022
https://doaj.org/article/2a5a0fc5d4774c4899b10db62bf7d01d
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spelling ftdoajarticles:oai:doaj.org/article:2a5a0fc5d4774c4899b10db62bf7d01d 2023-05-15T13:06:59+02:00 The new MISR research aerosol retrieval algorithm: a multi-angle, multi-spectral, bounded-variable least squares retrieval of aerosol particle properties over both land and water J. A. Limbacher R. A. Kahn J. Lee 2022-11-01T00:00:00Z https://doi.org/10.5194/amt-15-6865-2022 https://doaj.org/article/2a5a0fc5d4774c4899b10db62bf7d01d EN eng Copernicus Publications https://amt.copernicus.org/articles/15/6865/2022/amt-15-6865-2022.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548 doi:10.5194/amt-15-6865-2022 1867-1381 1867-8548 https://doaj.org/article/2a5a0fc5d4774c4899b10db62bf7d01d Atmospheric Measurement Techniques, Vol 15, Pp 6865-6887 (2022) Environmental engineering TA170-171 Earthwork. Foundations TA715-787 article 2022 ftdoajarticles https://doi.org/10.5194/amt-15-6865-2022 2022-12-30T19:37:52Z Launched in December 1999, NASA's Multi-angle Imaging SpectroRadiometer (MISR) has given researchers the ability to observe the Earth from nine different views for the last 22 years. Among the many advancements that have since resulted from the launch of MISR is progress in the retrieval of aerosols from passive space-based remote sensing. The MISR operational standard aerosol (SA) retrieval algorithm has been refined several times over the last 20 years, resulting in significant improvements to spatial resolution (now 4.4 km) and aerosol particle properties. However, the MISR SA still suffers from large biases in retrieved aerosol optical depth (AOD) as aerosol loading increases. Here, we present a new MISR research aerosol (RA) retrieval algorithm that utilizes over-land surface reflectance data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) to address these biases. This new over-land and over-water algorithm produces a self-consistent aerosol and surface retrieval when aerosol loading is low (AOD <0.75 ); this is combined with a prescribed surface algorithm using a bounded-variable least squares solver when aerosol loading is elevated (AOD >1.5 ). The two algorithms (prescribed + retrieved surface) are then merged as part of our combined surface retrieval algorithm. Results are compared with AErosol RObotic NETwork (AERONET) validation sun-photometer direct-sun + almucantar inversion retrievals. Over land, with AERONET AOD (550 nm) direct-sun observations as the standard, the root mean squared error (RMSE) of the MISR RA combined retrieval ( n =11563 ) is 0.084, with a correlation coefficient ( r ) of 0.935 and expected error of <math xmlns="http://www.w3.org/1998/Math/MathML" id="M7" display="inline" overflow="scroll" dspmath="mathml"><mrow><mo>±</mo><mo>(</mo><mn mathvariant="normal">0.20</mn><mo>×</mo><mo>[</mo><mi mathvariant="normal">MISR</mi><mspace linebreak="nobreak" ... Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Atmospheric Measurement Techniques 15 22 6865 6887
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Environmental engineering
TA170-171
Earthwork. Foundations
TA715-787
spellingShingle Environmental engineering
TA170-171
Earthwork. Foundations
TA715-787
J. A. Limbacher
R. A. Kahn
J. Lee
The new MISR research aerosol retrieval algorithm: a multi-angle, multi-spectral, bounded-variable least squares retrieval of aerosol particle properties over both land and water
topic_facet Environmental engineering
TA170-171
Earthwork. Foundations
TA715-787
description Launched in December 1999, NASA's Multi-angle Imaging SpectroRadiometer (MISR) has given researchers the ability to observe the Earth from nine different views for the last 22 years. Among the many advancements that have since resulted from the launch of MISR is progress in the retrieval of aerosols from passive space-based remote sensing. The MISR operational standard aerosol (SA) retrieval algorithm has been refined several times over the last 20 years, resulting in significant improvements to spatial resolution (now 4.4 km) and aerosol particle properties. However, the MISR SA still suffers from large biases in retrieved aerosol optical depth (AOD) as aerosol loading increases. Here, we present a new MISR research aerosol (RA) retrieval algorithm that utilizes over-land surface reflectance data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) to address these biases. This new over-land and over-water algorithm produces a self-consistent aerosol and surface retrieval when aerosol loading is low (AOD <0.75 ); this is combined with a prescribed surface algorithm using a bounded-variable least squares solver when aerosol loading is elevated (AOD >1.5 ). The two algorithms (prescribed + retrieved surface) are then merged as part of our combined surface retrieval algorithm. Results are compared with AErosol RObotic NETwork (AERONET) validation sun-photometer direct-sun + almucantar inversion retrievals. Over land, with AERONET AOD (550 nm) direct-sun observations as the standard, the root mean squared error (RMSE) of the MISR RA combined retrieval ( n =11563 ) is 0.084, with a correlation coefficient ( r ) of 0.935 and expected error of <math xmlns="http://www.w3.org/1998/Math/MathML" id="M7" display="inline" overflow="scroll" dspmath="mathml"><mrow><mo>±</mo><mo>(</mo><mn mathvariant="normal">0.20</mn><mo>×</mo><mo>[</mo><mi mathvariant="normal">MISR</mi><mspace linebreak="nobreak" ...
format Article in Journal/Newspaper
author J. A. Limbacher
R. A. Kahn
J. Lee
author_facet J. A. Limbacher
R. A. Kahn
J. Lee
author_sort J. A. Limbacher
title The new MISR research aerosol retrieval algorithm: a multi-angle, multi-spectral, bounded-variable least squares retrieval of aerosol particle properties over both land and water
title_short The new MISR research aerosol retrieval algorithm: a multi-angle, multi-spectral, bounded-variable least squares retrieval of aerosol particle properties over both land and water
title_full The new MISR research aerosol retrieval algorithm: a multi-angle, multi-spectral, bounded-variable least squares retrieval of aerosol particle properties over both land and water
title_fullStr The new MISR research aerosol retrieval algorithm: a multi-angle, multi-spectral, bounded-variable least squares retrieval of aerosol particle properties over both land and water
title_full_unstemmed The new MISR research aerosol retrieval algorithm: a multi-angle, multi-spectral, bounded-variable least squares retrieval of aerosol particle properties over both land and water
title_sort new misr research aerosol retrieval algorithm: a multi-angle, multi-spectral, bounded-variable least squares retrieval of aerosol particle properties over both land and water
publisher Copernicus Publications
publishDate 2022
url https://doi.org/10.5194/amt-15-6865-2022
https://doaj.org/article/2a5a0fc5d4774c4899b10db62bf7d01d
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source Atmospheric Measurement Techniques, Vol 15, Pp 6865-6887 (2022)
op_relation https://amt.copernicus.org/articles/15/6865/2022/amt-15-6865-2022.pdf
https://doaj.org/toc/1867-1381
https://doaj.org/toc/1867-8548
doi:10.5194/amt-15-6865-2022
1867-1381
1867-8548
https://doaj.org/article/2a5a0fc5d4774c4899b10db62bf7d01d
op_doi https://doi.org/10.5194/amt-15-6865-2022
container_title Atmospheric Measurement Techniques
container_volume 15
container_issue 22
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