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Determining the Primary Sources of Uncertainty in Retrieval of Marine Remote Sensing Reflectance From Satellite Ocean Color SensorsUncertainties in the retrieval of the remote sensing reflectance, R_rs, from Ocean Color (OC) satellite sensors have a strong impact on the performance of algorithms for the estimation of chlorophyll-a, mineral concentrations, and inherent optical properties (IOPs). The uncertainties are highest in the blue bands. The total radiance measured at the top of the atmosphere captures the instantaneous state of the atmosphere-ocean system: the in-water conditions, sky and Sun glint reflected from the wind-roughened ocean surface, as well as light scattered from molecules and aerosols in the atmosphere. Each of these components has associated uncertainties, and when combined with the additional uncertainties from the instrument noise and the atmospheric correction process, they contribute to the total uncertainty budget for the retrieved R_rs. We analyzed the contribution of each component uncertainties to the total R_rs uncertainties in SNPP-VIIRS level 2 products, taking advantage of the spectral differences between the components. We examined multiple scenes in the open ocean and coastal waters at spatial resolutions ranging from 2250 to 5250 m by comparing the retrieved R_rs to in situ measurements made at several AERONET-OC sites and at the MOBY site. It was shown that uncertainties associated with the molecular (Rayleigh) scattering play the most significant role, while the contributions of other components are usually smaller. Uncertainties in Rayleigh scattering are primarily attributed to the variability of Rayleigh optical thickness (ROT) with a standard deviation of approximately 1.5% of ROT, which can largely explain the frequency of negative R_rs retrievals as observed using the current standard atmospheric correction process employed by NASA. Variability of the sky light reflected from the ocean surface in some conditions also contributed to uncertainties in the blue; water variability proportional to R_rs had a very pronounced peak in the green at coastal sites.
Document ID
20220006580
Acquisition Source
Goddard Space Flight Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Alexander Gilerson
(City College of New York New York, New York, United States)
Eder Herrera-Estrella
(City College of New York New York, New York, United States)
Robert Foster
(United States Naval Research Laboratory Washington D.C., District of Columbia, United States)
Jacopo Agagliate
(City College of New York New York, New York, United States)
Chuanmin Hu
(University of South Florida St. Petersburg St. Petersburg, Florida, United States)
Amir Ibrahim
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Bryan Franz
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Date Acquired
April 28, 2022
Publication Date
April 27, 2022
Publication Information
Publication: Frontiers in Remote Sensing
Publisher: Frontiers Media
Volume: 3
Issue Publication Date: April 27, 2022
e-ISSN: 2673-6187
Subject Category
Earth Resources And Remote Sensing
Funding Number(s)
CONTRACT_GRANT: 80NSSC21K0562
CONTRACT_GRANT: NA16SEC4810008
CONTRACT_GRANT: 80NSSC21D0002
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Technical Review
External Peer Committee
Keywords
remote sensing reflectance
uncertainties
Rayleigh scattering
Rayleigh optical thickness
atmospheric correction
AERONET-OC
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