Algorithm evaluation for polarimetric remote sensing of atmospheric aerosols

From a passive satellite remote sensing point of view, the richest set of information on aerosol properties can be obtained from instruments that measure both intensity and polarization of backscattered sunlight at multiple wavelengths and multiple viewing angles for one ground pixel. However, it is...

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Published in:Atmospheric Measurement Techniques
Main Authors: O. Hasekamp, P. Litvinov, G. Fu, C. Chen, O. Dubovik
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2024
Subjects:
Online Access:https://doi.org/10.5194/amt-17-1497-2024
https://doaj.org/article/e076ef5d7d1f4f048e0b5b715bcb306a
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author O. Hasekamp
P. Litvinov
G. Fu
C. Chen
O. Dubovik
author_facet O. Hasekamp
P. Litvinov
G. Fu
C. Chen
O. Dubovik
author_sort O. Hasekamp
collection Directory of Open Access Journals: DOAJ Articles
container_issue 5
container_start_page 1497
container_title Atmospheric Measurement Techniques
container_volume 17
description From a passive satellite remote sensing point of view, the richest set of information on aerosol properties can be obtained from instruments that measure both intensity and polarization of backscattered sunlight at multiple wavelengths and multiple viewing angles for one ground pixel. However, it is challenging to exploit this information at a global scale because complex algorithms are needed with many fit parameters (aerosol and land/ocean reflection), based on online radiative transfer models. So far, two such algorithms have demonstrated this capability at a global scale: the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm and the Remote sensing of Trace gas and Aerosol Products (RemoTAP) algorithm. In this paper, we present a detailed comparison of the most recent versions of RemoTAP and GRASP. We evaluate both algorithms for synthetic observations, for real PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar) observations against AERONET (Aerosol Robotic Network) for common pixels, and for global PARASOL retrievals for the year 2008. For the aerosol optical depth (AOD) over land, both algorithms show a root mean square error (RMSE) of 0.10 (at 550 nm). For single scattering albedo (SSA), both algorithms show a good performance in terms of RMSE (0.04), but RemoTAP has a smaller bias (0.002) compared to GRASP (0.021). For the Ångström exponent (AE), GRASP has a smaller RMSE (0.367) than RemoTAP (0.387), mainly caused by a small overestimate of AE at low values (large particles). Over ocean both algorithms perform very well. For AOD, RemoTAP has an RMSE of 0.057 and GRASP an even smaller RMSE of 0.047. For AE, the RMSEs of RemoTAP and GRASP are 0.285 and 0.224, respectively. Based on the AERONET comparison, we conclude that both algorithms show very similar overall performance, where both algorithms have stronger and weaker points. For the global data products, we find a root mean square difference (RMSD) between ...
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spelling ftdoajarticles:oai:doaj.org/article:e076ef5d7d1f4f048e0b5b715bcb306a 2025-01-16T18:39:07+00:00 Algorithm evaluation for polarimetric remote sensing of atmospheric aerosols O. Hasekamp P. Litvinov G. Fu C. Chen O. Dubovik 2024-03-01T00:00:00Z https://doi.org/10.5194/amt-17-1497-2024 https://doaj.org/article/e076ef5d7d1f4f048e0b5b715bcb306a EN eng Copernicus Publications https://amt.copernicus.org/articles/17/1497/2024/amt-17-1497-2024.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548 doi:10.5194/amt-17-1497-2024 1867-1381 1867-8548 https://doaj.org/article/e076ef5d7d1f4f048e0b5b715bcb306a Atmospheric Measurement Techniques, Vol 17, Pp 1497-1525 (2024) Environmental engineering TA170-171 Earthwork. Foundations TA715-787 article 2024 ftdoajarticles https://doi.org/10.5194/amt-17-1497-2024 2024-08-05T17:49:50Z From a passive satellite remote sensing point of view, the richest set of information on aerosol properties can be obtained from instruments that measure both intensity and polarization of backscattered sunlight at multiple wavelengths and multiple viewing angles for one ground pixel. However, it is challenging to exploit this information at a global scale because complex algorithms are needed with many fit parameters (aerosol and land/ocean reflection), based on online radiative transfer models. So far, two such algorithms have demonstrated this capability at a global scale: the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm and the Remote sensing of Trace gas and Aerosol Products (RemoTAP) algorithm. In this paper, we present a detailed comparison of the most recent versions of RemoTAP and GRASP. We evaluate both algorithms for synthetic observations, for real PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar) observations against AERONET (Aerosol Robotic Network) for common pixels, and for global PARASOL retrievals for the year 2008. For the aerosol optical depth (AOD) over land, both algorithms show a root mean square error (RMSE) of 0.10 (at 550 nm). For single scattering albedo (SSA), both algorithms show a good performance in terms of RMSE (0.04), but RemoTAP has a smaller bias (0.002) compared to GRASP (0.021). For the Ångström exponent (AE), GRASP has a smaller RMSE (0.367) than RemoTAP (0.387), mainly caused by a small overestimate of AE at low values (large particles). Over ocean both algorithms perform very well. For AOD, RemoTAP has an RMSE of 0.057 and GRASP an even smaller RMSE of 0.047. For AE, the RMSEs of RemoTAP and GRASP are 0.285 and 0.224, respectively. Based on the AERONET comparison, we conclude that both algorithms show very similar overall performance, where both algorithms have stronger and weaker points. For the global data products, we find a root mean square difference (RMSD) between ... Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Atmospheric Measurement Techniques 17 5 1497 1525
spellingShingle Environmental engineering
TA170-171
Earthwork. Foundations
TA715-787
O. Hasekamp
P. Litvinov
G. Fu
C. Chen
O. Dubovik
Algorithm evaluation for polarimetric remote sensing of atmospheric aerosols
title Algorithm evaluation for polarimetric remote sensing of atmospheric aerosols
title_full Algorithm evaluation for polarimetric remote sensing of atmospheric aerosols
title_fullStr Algorithm evaluation for polarimetric remote sensing of atmospheric aerosols
title_full_unstemmed Algorithm evaluation for polarimetric remote sensing of atmospheric aerosols
title_short Algorithm evaluation for polarimetric remote sensing of atmospheric aerosols
title_sort algorithm evaluation for polarimetric remote sensing of atmospheric aerosols
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-17-1497-2024
https://doaj.org/article/e076ef5d7d1f4f048e0b5b715bcb306a