Vicarious Calibration of Satellite Ocean Color Sensors
Summary
Vicarious calibration is the process of adjusting satellite ocean colour sensors post-launch through comparison with precise in situ measurements of ocean radiance. It addresses the systematic errors that arise from pre-launch calibration drift, instrument ageing and uncertainties in atmospheric correction. By deploying well-characterised reference sites or buoy-mounted radiometers in clear open-ocean waters, radiometric biases in top-of-atmosphere measurements can be quantified and corrected. This approach ensures that derived biogeochemical parameters—such as chlorophyll concentration, water clarity and suspended particulate matter—remain accurate throughout the lifetime of a mission. Vicarious calibration underpins the long-term consistency of multi-decadal records, enabling reliable assessment of climate-driven changes in marine ecosystems and support for operational services such as fisheries management, pollution monitoring and carbon cycle studies.
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Vicarious Calibration of Satellite Ocean Color Sensors publication trend
The graph below shows the total number of articles in vicarious calibration of satellite ocean color sensors across all publications each year (not limited to Nature Index journals).
Technical terms
Vicarious calibration: Post-launch adjustment of satellite sensor measurements through comparison with precise in situ radiance data.
Top-of-atmosphere (TOA) radiance: The radiometric signal measured by a satellite sensor after atmospheric path effects.
Radiometric bias: Systematic offset between measured and true radiance values, often expressed as a percentage.
Homogenisation: Correction of spatial and spectral differences between two or more sensors to allow direct comparison.
Harmonisation: Adjustment of one sensor’s output to match a reference sensor, reducing inter-sensor bias.
References
- The Ocean Color Instrument (OCI) on the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) Mission: System Design and Prelaunch Radiometric Performance. IEEE Transactions on Geoscience and Remote Sensing (2024).
- OLCI A/B Tandem Phase Analysis, Part 1: Level 1 Homogenisation and Harmonisation. Remote Sensing (2020).
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