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...

Full description

Bibliographic Details
Published in:Remote Sensing
Main Authors: 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.
Other Authors: 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
Language:French
Published: HAL CCSD 2020
Subjects:
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
id ftinsu:oai:HAL:hal-04548762v1
record_format openpolar
spelling 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
_version_ 1802645262776139776