First images from Sentinel-3B

Spectral matching Atmospheric Correction for Sentinel Ocean colour measurements (SACSO)

First images from Sentinel-3B
First images from Sentinel-3B

This study focuses on developing a new atmospheric correction prototype to improve the quality of the OLCI water reflectance level 2 product.

Last Updated

05 March 2021

Published on

17 July 2019

Atmospheric correction is a critical step for estimating the water reflectance spectrum — also commonly referred to as water colour — from space-borne observations dedicated to ocean-colour purposes. It estimates the water signal of interest by removing the dominating and variable influence of the atmosphere and non-water colour elements at the surface (e.g. sunglint, white caps) from top of atmosphere (TOA) observations. Among many challenges, aerosol correction remains the most critical one due to the variability of particles in terms of types, their diverse horizontal and vertical distribution in the atmosphere, their complex interactions with the solar light in the whole VIS-NIR-SWIR spectrum, and the resulting impacts on the satellite measurements at the TOA.

Currently, the water reflectance level 2 product from OLCI on Sentinel-3, processed at EUMETSAT, is based on the historical (also called 'standard') aerosol correction approach. As a legacy from developments for the past ENVISAT MERIS sensor, it exclusively relies on the near-infrared (NIR) spectral range. The SACSO project focuses on developing a new atmospheric correction prototype to improve the quality of the OLCI water reflectance level 2 product. The SACSO strategy is based on an 'alternative' and innovative approach, using a spectral matching technique, to address several known issues with the standard approach: e.g. the high sensitivity to strong aerosol contamination, in particular absorbing ones, and thin or subpixel clouds, which lead to reduced performance and spatial coverage, hence usefulness of the products. The ability to correct for sun glint and adjacency effects, although not the primary target of this study, would also significantly improve the usefulness of the products.

The SACSO team employs the Polymer atmospheric correction algorithm, which uses the iterative spectral optimisation method, relying on the full solar light spectrum, as a baseline for this alternative processor. The goals are to study and improve several of its aspects and propose a consolidated version for OLCI, but also applicable for other similar sensors.


The objectives of this study are to:

  • review the state of the art and the requirements on atmospheric correction algorithms;
  • perform scientific tests, based on simulated datasets, in-situ data or specific areas of interest, to investigate and consolidate specific aspects of an atmospheric correction scheme based on Polymer;
  • develop a software prototype for OLCI implementing these algorithmic evolutions, and including an uncertainty propagation scheme, to be interfaced with the EUMETSAT study 'Multi-mission Ocean Colour algorithm prototype';
  • generate a diagnostic dataset and validate the prototype;
  • establish an active communication with relevant expert groups.


Five activities are carried out in this project:

  1. The state of the art of atmospheric correction will be reviewed and classified to list the strengths and weaknesses of the existing algorithms, using either the historical approach in which the aerosol properties are estimated in the near infrared and extrapolated in the visible bands, or coupled methods relying on the full spectrum. The assumptions and models, for both the atmospheric and oceanic signals, will also be reviewed, as well as the uncertainty estimation methods. This review will be used to address the requirements on the algorithm and provide guidelines for its development.
  2. Scientific investigations will be carried out, to better understand the assumptions and adequacy of the models to the actual variability of the atmospheric and oceanic signals. The impact of atmospheric transmittance, and the numeric optimisation method, will also be studied. These investigations will rely on radiative transfer simulations using the SMART-G code and on the diagnostic dataset. They will lead to the implementation of a prototype mostly based on the current implementation of Polymer.
  3. A diagnostic dataset will be established, containing OLCI scenes with various oceanic and atmospheric features: clear, coastal, turbid and absorbing waters, diverse aerosol events, sun glint, adjacency effects, and observations at high latitudes. This dataset will also contain global data and time series over specific regions, and will be processed to investigate and illustrate the behaviour of the prototype in different conditions.
  4. The prototype will be validated using in-situ data and further characterised using the diagnostic dataset.
  5. The study team will communicate with experts at EUMETSAT and with external atmospheric correction experts (S3VT, S3MPC), in order to integrate the most recent developments from the community, in terms of sensor characteristics (especially radiometric characterisation and system vicarious calibration) and in terms of algorithms developments.

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