The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future
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 to...
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doaj-7bb05f429fcd4d6299b383e71b4f31252020-11-25T01:58:55ZengMDPI AGRemote Sensing2072-42922020-09-01122900290010.3390/rs12182900The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and FutureLorraine A. Remer0Robert C. Levy1Shana Mattoo2Didier Tanré3Pawan Gupta4Yingxi Shi5Virginia Sawyer6Leigh A. Munchak7Yaping Zhou8Mijin Kim9Charles Ichoku10Falguni Patadia11Rong-Rong Li12Santiago Gassó13Richard G. Kleidman14Brent N. Holben15Joint Center for Earth Systems Technology-UMBC, Baltimore, MD 21250, USANASA-Goddard Space Flight Center (GSFC), Greenbelt, MD 20771-0001, USANASA-Goddard Space Flight Center (GSFC), Greenbelt, MD 20771-0001, USACNRS, UMR 8518-LOA-Laboratoire d’Optique Atmosphérique, University of Lille, F-59000 Lille, FranceScience and Technology Institute, Universities Space Research Association (USRA), Huntsville, AL 35806, USAJoint Center for Earth Systems Technology-UMBC, Baltimore, MD 21250, USANASA-Goddard Space Flight Center (GSFC), Greenbelt, MD 20771-0001, USANASA-Goddard Space Flight Center (GSFC), Greenbelt, MD 20771-0001, USAJoint Center for Earth Systems Technology-UMBC, Baltimore, MD 21250, USANASA-Goddard Space Flight Center (GSFC), Greenbelt, MD 20771-0001, USACollege of Arts & Sciences, Howard University, Washington, DC 20059, USANASA-Goddard Space Flight Center (GSFC), Greenbelt, MD 20771-0001, USANaval Research Laboratory, Code 7231, Washington, DC 20375, USANASA-Goddard Space Flight Center (GSFC), Greenbelt, MD 20771-0001, USANASA-Goddard Space Flight Center (GSFC), Greenbelt, MD 20771-0001, USANASA-Goddard Space Flight Center (GSFC), Greenbelt, MD 20771-0001, USAThe 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.https://www.mdpi.com/2072-4292/12/18/2900aerosolremote sensingMODISVIIRS |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lorraine A. Remer Robert C. Levy Shana Mattoo Didier Tanré Pawan Gupta Yingxi Shi Virginia Sawyer Leigh A. Munchak Yaping Zhou Mijin Kim Charles Ichoku Falguni Patadia Rong-Rong Li Santiago Gassó Richard G. Kleidman Brent N. Holben |
spellingShingle |
Lorraine A. Remer Robert C. Levy Shana Mattoo Didier Tanré Pawan Gupta Yingxi Shi Virginia Sawyer Leigh A. Munchak Yaping Zhou Mijin Kim Charles Ichoku Falguni Patadia Rong-Rong Li Santiago Gassó Richard G. Kleidman Brent N. Holben The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future Remote Sensing aerosol remote sensing MODIS VIIRS |
author_facet |
Lorraine A. Remer Robert C. Levy Shana Mattoo Didier Tanré Pawan Gupta Yingxi Shi Virginia Sawyer Leigh A. Munchak Yaping Zhou Mijin Kim Charles Ichoku Falguni Patadia Rong-Rong Li Santiago Gassó Richard G. Kleidman Brent N. Holben |
author_sort |
Lorraine A. Remer |
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 |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2020-09-01 |
description |
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. |
topic |
aerosol remote sensing MODIS VIIRS |
url |
https://www.mdpi.com/2072-4292/12/18/2900 |
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