Algorithm evaluation for polarimetric remote sensing of atmospheric aerosols
International audience 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 groun...
Published in: | Atmospheric Measurement Techniques |
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ftinsu:oai:HAL:hal-04591819v1 2024-06-23T07:45:00+00:00 Algorithm evaluation for polarimetric remote sensing of atmospheric aerosols Hasekamp, Otto Litvinov, Pavel Fu, Guangliang Chen, Cheng Doubovik, Oleg SRON Netherlands Institute for Space Research (SRON) Université de Lille Laboratoire d’Optique Atmosphérique - UMR 8518 (LOA) Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS) 2024-04-19 https://hal.univ-lille.fr/hal-04591819 https://hal.univ-lille.fr/hal-04591819/document https://hal.univ-lille.fr/hal-04591819/file/amt-17-1497-2024.pdf https://doi.org/10.5194/amt-17-1497-2024 en eng HAL CCSD European Geosciences Union info:eu-repo/semantics/altIdentifier/doi/10.5194/amt-17-1497-2024 hal-04591819 https://hal.univ-lille.fr/hal-04591819 https://hal.univ-lille.fr/hal-04591819/document https://hal.univ-lille.fr/hal-04591819/file/amt-17-1497-2024.pdf doi:10.5194/amt-17-1497-2024 http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess ISSN: 1867-1381 EISSN: 1867-8548 Atmospheric Measurement Techniques https://hal.univ-lille.fr/hal-04591819 Atmospheric Measurement Techniques, 2024, Atmos. Meas. Tech., 17, ⟨10.5194/amt-17-1497-2024⟩ [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere info:eu-repo/semantics/article Journal articles 2024 ftinsu https://doi.org/10.5194/amt-17-1497-2024 2024-06-06T00:00:14Z International audience 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 ... Article in Journal/Newspaper Aerosol Robotic Network Institut national des sciences de l'Univers: HAL-INSU Atmospheric Measurement Techniques 17 5 1497 1525 |
institution |
Open Polar |
collection |
Institut national des sciences de l'Univers: HAL-INSU |
op_collection_id |
ftinsu |
language |
English |
topic |
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere |
spellingShingle |
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere Hasekamp, Otto Litvinov, Pavel Fu, Guangliang Chen, Cheng Doubovik, Oleg Algorithm evaluation for polarimetric remote sensing of atmospheric aerosols |
topic_facet |
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere |
description |
International audience 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 ... |
author2 |
SRON Netherlands Institute for Space Research (SRON) Université de Lille Laboratoire d’Optique Atmosphérique - UMR 8518 (LOA) Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS) |
format |
Article in Journal/Newspaper |
author |
Hasekamp, Otto Litvinov, Pavel Fu, Guangliang Chen, Cheng Doubovik, Oleg |
author_facet |
Hasekamp, Otto Litvinov, Pavel Fu, Guangliang Chen, Cheng Doubovik, Oleg |
author_sort |
Hasekamp, Otto |
title |
Algorithm evaluation for polarimetric remote sensing of atmospheric aerosols |
title_short |
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_sort |
algorithm evaluation for polarimetric remote sensing of atmospheric aerosols |
publisher |
HAL CCSD |
publishDate |
2024 |
url |
https://hal.univ-lille.fr/hal-04591819 https://hal.univ-lille.fr/hal-04591819/document https://hal.univ-lille.fr/hal-04591819/file/amt-17-1497-2024.pdf https://doi.org/10.5194/amt-17-1497-2024 |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
ISSN: 1867-1381 EISSN: 1867-8548 Atmospheric Measurement Techniques https://hal.univ-lille.fr/hal-04591819 Atmospheric Measurement Techniques, 2024, Atmos. Meas. Tech., 17, ⟨10.5194/amt-17-1497-2024⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.5194/amt-17-1497-2024 hal-04591819 https://hal.univ-lille.fr/hal-04591819 https://hal.univ-lille.fr/hal-04591819/document https://hal.univ-lille.fr/hal-04591819/file/amt-17-1497-2024.pdf doi:10.5194/amt-17-1497-2024 |
op_rights |
http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.5194/amt-17-1497-2024 |
container_title |
Atmospheric Measurement Techniques |
container_volume |
17 |
container_issue |
5 |
container_start_page |
1497 |
op_container_end_page |
1525 |
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1802645306645413888 |