The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future
International audience The Dark Target aerosol algorithm was developed to exploit the information content available from the observations of Moderate-Resolution Imaging Spectroradiometers (MODIS), to better characterize the global aerosol system. The algorithm is based on measurements of the light s...
Published in: | Remote Sensing |
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Format: | Article in Journal/Newspaper |
Language: | French |
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Online Access: | https://hal.univ-lille.fr/hal-04548762 https://hal.univ-lille.fr/hal-04548762/document https://hal.univ-lille.fr/hal-04548762/file/remotesensing-12-02900.pdf https://doi.org/10.3390/rs12182900 |
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ftinsu:oai:HAL:hal-04548762v1 2024-06-23T07:45:00+00:00 The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future Remer, Lorraine A. Levy, Robert C. Mattoo, Shana Tanre, Didier Gupta, Pawan Shi, Yingxi Sawyer, Virginia Munchak, Leigh A. Zhou, Yaping Kim, Mijin Ichoku, Charles Patadia, Falguni Li, Rong-Rong Gassó, Santiago Kleidman, Richard G. Holben, Brent N. 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) 2020-09-07 https://hal.univ-lille.fr/hal-04548762 https://hal.univ-lille.fr/hal-04548762/document https://hal.univ-lille.fr/hal-04548762/file/remotesensing-12-02900.pdf https://doi.org/10.3390/rs12182900 fr fre HAL CCSD MDPI info:eu-repo/semantics/altIdentifier/doi/10.3390/rs12182900 hal-04548762 https://hal.univ-lille.fr/hal-04548762 https://hal.univ-lille.fr/hal-04548762/document https://hal.univ-lille.fr/hal-04548762/file/remotesensing-12-02900.pdf doi:10.3390/rs12182900 http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess ISSN: 2072-4292 Remote Sensing https://hal.univ-lille.fr/hal-04548762 Remote Sensing, 2020, Remote Sensing, 12 (18), pp.2900. ⟨10.3390/rs12182900⟩ [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph] info:eu-repo/semantics/article Journal articles 2020 ftinsu https://doi.org/10.3390/rs12182900 2024-06-06T00:00:14Z International audience The Dark Target aerosol algorithm was developed to exploit the information content available from the observations of Moderate-Resolution Imaging Spectroradiometers (MODIS), to better characterize the global aerosol system. The algorithm is based on measurements of the light scattered by aerosols toward a space-borne sensor against the backdrop of relatively dark Earth scenes, thus giving rise to the name “Dark Target”. Development required nearly a decade of research that included application of MODIS airborne simulators to provide test beds for proto-algorithms and analysis of existing data to form realistic assumptions to constrain surface reflectance and aerosol optical properties. This research in itself played a significant role in expanding our understanding of aerosol properties, even before Terra MODIS launch. Contributing to that understanding were the observations and retrievals of the growing Aerosol Robotic Network (AERONET) of sun-sky radiometers, which has walked hand-in-hand with MODIS and the development of other aerosol algorithms, providing validation of the satellite-retrieved products after launch. The MODIS Dark Target products prompted advances in Earth science and applications across subdisciplines such as climate, transport of aerosols, air quality, and data assimilation systems. Then, as the Terra and Aqua MODIS sensors aged, the challenge was to monitor the effects of calibration drifts on the aerosol products and to differentiate physical trends in the aerosol system from artefacts introduced by instrument characterization. Our intention is to continue to adapt and apply the well-vetted Dark Target algorithms to new instruments, including both polar-orbiting and geosynchronous sensors. The goal is to produce an uninterrupted time series of an aerosol climate data record that begins at the dawn of the 21st century and continues indefinitely into the future. Article in Journal/Newspaper Aerosol Robotic Network Institut national des sciences de l'Univers: HAL-INSU Remote Sensing 12 18 2900 |
institution |
Open Polar |
collection |
Institut national des sciences de l'Univers: HAL-INSU |
op_collection_id |
ftinsu |
language |
French |
topic |
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph] |
spellingShingle |
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph] Remer, Lorraine A. Levy, Robert C. Mattoo, Shana Tanre, Didier Gupta, Pawan Shi, Yingxi Sawyer, Virginia Munchak, Leigh A. Zhou, Yaping Kim, Mijin Ichoku, Charles Patadia, Falguni Li, Rong-Rong Gassó, Santiago Kleidman, Richard G. Holben, Brent N. The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future |
topic_facet |
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph] |
description |
International audience The Dark Target aerosol algorithm was developed to exploit the information content available from the observations of Moderate-Resolution Imaging Spectroradiometers (MODIS), to better characterize the global aerosol system. The algorithm is based on measurements of the light scattered by aerosols toward a space-borne sensor against the backdrop of relatively dark Earth scenes, thus giving rise to the name “Dark Target”. Development required nearly a decade of research that included application of MODIS airborne simulators to provide test beds for proto-algorithms and analysis of existing data to form realistic assumptions to constrain surface reflectance and aerosol optical properties. This research in itself played a significant role in expanding our understanding of aerosol properties, even before Terra MODIS launch. Contributing to that understanding were the observations and retrievals of the growing Aerosol Robotic Network (AERONET) of sun-sky radiometers, which has walked hand-in-hand with MODIS and the development of other aerosol algorithms, providing validation of the satellite-retrieved products after launch. The MODIS Dark Target products prompted advances in Earth science and applications across subdisciplines such as climate, transport of aerosols, air quality, and data assimilation systems. Then, as the Terra and Aqua MODIS sensors aged, the challenge was to monitor the effects of calibration drifts on the aerosol products and to differentiate physical trends in the aerosol system from artefacts introduced by instrument characterization. Our intention is to continue to adapt and apply the well-vetted Dark Target algorithms to new instruments, including both polar-orbiting and geosynchronous sensors. The goal is to produce an uninterrupted time series of an aerosol climate data record that begins at the dawn of the 21st century and continues indefinitely into the future. |
author2 |
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 |
Remer, Lorraine A. Levy, Robert C. Mattoo, Shana Tanre, Didier Gupta, Pawan Shi, Yingxi Sawyer, Virginia Munchak, Leigh A. Zhou, Yaping Kim, Mijin Ichoku, Charles Patadia, Falguni Li, Rong-Rong Gassó, Santiago Kleidman, Richard G. Holben, Brent N. |
author_facet |
Remer, Lorraine A. Levy, Robert C. Mattoo, Shana Tanre, Didier Gupta, Pawan Shi, Yingxi Sawyer, Virginia Munchak, Leigh A. Zhou, Yaping Kim, Mijin Ichoku, Charles Patadia, Falguni Li, Rong-Rong Gassó, Santiago Kleidman, Richard G. Holben, Brent N. |
author_sort |
Remer, Lorraine A. |
title |
The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future |
title_short |
The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future |
title_full |
The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future |
title_fullStr |
The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future |
title_full_unstemmed |
The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future |
title_sort |
dark target algorithm for observing the global aerosol system: past, present, and future |
publisher |
HAL CCSD |
publishDate |
2020 |
url |
https://hal.univ-lille.fr/hal-04548762 https://hal.univ-lille.fr/hal-04548762/document https://hal.univ-lille.fr/hal-04548762/file/remotesensing-12-02900.pdf https://doi.org/10.3390/rs12182900 |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
ISSN: 2072-4292 Remote Sensing https://hal.univ-lille.fr/hal-04548762 Remote Sensing, 2020, Remote Sensing, 12 (18), pp.2900. ⟨10.3390/rs12182900⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.3390/rs12182900 hal-04548762 https://hal.univ-lille.fr/hal-04548762 https://hal.univ-lille.fr/hal-04548762/document https://hal.univ-lille.fr/hal-04548762/file/remotesensing-12-02900.pdf doi:10.3390/rs12182900 |
op_rights |
http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.3390/rs12182900 |
container_title |
Remote Sensing |
container_volume |
12 |
container_issue |
18 |
container_start_page |
2900 |
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1802645262776139776 |