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The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present and FutureThe 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.
Document ID
20205007499
Acquisition Source
Goddard Space Flight Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Lorraine A Remer
(University of Maryland, Baltimore County Baltimore, Maryland, United States)
Robert C Levy ORCID
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Shana Mattoo
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Didier Tanre
(French National Centre for Scientific Research Paris, France)
Pawan Gupta
(Universities Space Research Association Columbia, Maryland, United States)
Yingxi Shi
(University of Maryland, Baltimore County Baltimore, Maryland, United States)
Virginia Sawyer
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Leigh A Munchak
(Maxar Technologies (United States) Westminster, Colorado, United States)
Yaping Zhou ORCID
(University of Maryland, Baltimore County Baltimore, Maryland, United States)
Mijin Kim
(Universities Space Research Association Columbia, Maryland, United States)
Charles Ichoku
(Howard University Washington D.C., District of Columbia, United States)
Falguni Patadia
(Universities Space Research Association Columbia, Maryland, United States)
Rong-Rong Li
(United States Naval Research Laboratory Washington D.C., District of Columbia, United States)
Santiago Gasso ORCID
(University of Maryland, College Park College Park, Maryland, United States)
Richard G Kleidman
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Brent N Holben
(Universities Space Research Association Columbia, Maryland, United States)
Date Acquired
September 11, 2020
Publication Date
September 7, 2020
Publication Information
Publication: Remote Sensing
Publisher: MDPI
Volume: 12
Issue: 18
Issue Publication Date: September 2, 2020
e-ISSN: 2072-4292
Subject Category
Computer Programming And Software
Earth Resources And Remote Sensing
Funding Number(s)
CONTRACT_GRANT: NNX15AT34A
CONTRACT_GRANT: NNG17HP01C
CONTRACT_GRANT: 80MSFC17M0022
CONTRACT_GRANT: NNH15CO48B
CONTRACT_GRANT: NNG11HP16A
CONTRACT_GRANT: NNX17AE79A
CONTRACT_GRANT: DOC NA16SEC4810006
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Technical Review
External Peer Committee
Keywords
Aerosol
Remote sensing
MODIS
VIIRS
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