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System Vicarious Calibration for Ocean Color Climate Change Applications: Requirements for In Situ Data
Published
Author(s)
Giuseppe Zibordi, Frederic Melin, Kenneth Voss, B. Carol Johnson, Bryan Franz, Ewa Kwiatkowska, J. P. Huot, Menghua Wang, David Antoine
Abstract
System Vicarious Calibration (SVC) ensures a relative radiometric calibration to satellite ocean color sensors that minimizes uncertainties in the water-leaving radiance Lw derived from the top of atmosphere radiance LT. This is achieved through the application of adjustment factors, g-factors, to pre-launch absolute radiometric calibration coefficients of the satellite sensor corrected for temporal changes in radiometric sensitivity. The g-factors are determined by the ratio of simulated to measured spectral LT values where the former are computed using: i. highly accurate in situ Lw reference measurements and ii. the same atmospheric model and algorithms applied for the atmospheric correction of satellite data. By analyzing basic relations between relative uncertainties of Lw and LT, and g-factors consistently determined for the same satellite missions using different in situ data sources, this work suggests creation of ocean color CDRs by ideally relying on: i. one main long-term in situ calibration system (site and radiometry) established and sustained with the objective to maximize accuracy and precision over time of g-factors and thus minimize possible biases among satellite data products from different missions; and additionally ii. unique (i.e., standardized) atmospheric model and algorithms for atmospheric correction to maximize cross-mission consistency of data products at locations different from that supporting SVC. Finally, accounting for results from the study and elements already provided in literature, requirements for SVC sites and field radiometers are streamlined.
Zibordi, G.
, Melin, F.
, Voss, K.
, Johnson, B.
, Franz, B.
, Kwiatkowska, E.
, Huot, J.
, Wang, M.
and Antoine, D.
(2015),
System Vicarious Calibration for Ocean Color Climate Change Applications: Requirements for In Situ Data, Remote Sensing of Environment, [online], https://doi.org/10.1016/j.rse.2014.12.015
(Accessed October 14, 2025)