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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 ; Gasso, Santiago ; Kleidman, Richard G ; Holben, Brent N

Remote sensing (Basel, Switzerland), 2020-09, Vol.12 (18), p.2900 [Periódico revisado por pares]

Goddard Space Flight Center: MDPI

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Título:
The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present and Future
Autor: 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 ; Gasso, Santiago ; Kleidman, Richard G ; Holben, Brent N
Assuntos: aerosol ; Aerosol Robotic Network ; Aerosols ; Air quality ; Algorithms ; Atmosphere ; Atmospheric and Oceanic Physics ; Calibration ; Climatic data ; Computer Programming And Software ; Computer simulation ; Dark adaptation ; Data collection ; Earth ; Earth Resources And Remote Sensing ; Flight simulators ; Influence ; Meteorological satellites ; MODIS ; Optical properties ; Physics ; Radiometers ; Remote sensing ; Satellites ; Science ; Sensors ; Spectroradiometers ; VIIRS
É parte de: Remote sensing (Basel, Switzerland), 2020-09, Vol.12 (18), p.2900
Notas: GSFC
Goddard Space Flight Center
Descrição: 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.
Editor: Goddard Space Flight Center: MDPI
Idioma: Inglês;Francês

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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 ; Gasso, Santiago ; Kleidman, Richard G ; Holben, Brent N

Goddard Space Flight Center: MDPI

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