Spectral correlation in MODIS water-leaving reflectance retrieval uncertainty
Optics Express
|February 1, 2024
Summary
This study introduces a new method to calculate uncertainty in ocean color data, improving accuracy for chlorophyll-a and light attenuation estimates. Accounting for spectral error covariance reduces uncertainty in key oceanographic products.
Area of Science:
- Oceanography and Remote Sensing
- Bio-optical and Biogeochemical Ocean Properties
Background:
- Spectral remote sensing reflectance (Rrs) is crucial for deriving water column properties from satellite ocean color measurements.
- Accurate estimation of uncertainty in derived geophysical products necessitates understanding the uncertainty in Rrs and its spectral error covariance.
Purpose of the Study:
- To establish a derivative-based approach for propagating uncertainties into Rrs, generating pixel-level error covariance.
- To apply this approach to Moderate Resolution Imaging Spectroradiometer (MODIS) data and assess its impact on chlorophyll-a and diffuse attenuation coefficient (Kd(490)) uncertainty.
Main Methods:
- Developed a derivative-based method to propagate instrument noise, systematic uncertainty, and forward model uncertainty into Rrs.
- Applied the method to MODIS Aqua data using the Multiple-Scattering Epsilon (MSEPS) atmospheric correction algorithm.
- Verified the approach using Monte Carlo (MC) analysis and compared propagated uncertainty with observed differences using in situ Rrs.
Main Results:
- The derivative-based approach successfully generated pixel-level error covariance in Rrs.
- Accounting for Rrs error covariance generally reduced estimated relative uncertainty in chlorophyll-a (chl_a) by 1-10% and in Kd(490) by approximately 2%, with higher reductions in specific regions.
- An 8-day global composite demonstrated that the goal of 35% uncertainty in chl_a can be achieved over deep ocean waters.
Conclusions:
- The derivative-based approach provides a reasonable estimation of Rrs error covariance, enhancing the accuracy of derived oceanographic products.
- The method effectively reduces uncertainty in chlorophyll-a and Kd(490) estimations, contributing to more reliable ocean color data.
- Future improvements should focus on refining assumptions regarding inter-band error correlation and uncertainties in calibration and ancillary data.
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