The Copernicus programme brings a wealth of ocean colour data at medium and high spatial resolution with a full, free and open data access policy, allowing for unprecedented monitoring capabilities of the open ocean and coastal and inland waters. The POLYMER atmospheric correction algorithm, with its genericity and robustness to most atmospheric and surface perturbations (aerosols, sun glint, thin clouds, adjacency effect), allows to maximize these observation capabilities, in particular for Sentinel-2 MSI and Sentinel-3 OLCI. The algorithm is fully consistent between these sensors, which gives access to a unique product in terms of potential applications. The evolution of the POLYMER algorithm will be presented, with examples of applications and validation results for Sentinel-2 and Sentinel-3.
Algorithms to retrieve ocean color from space, deterministic or statistical, often use a simplified water reflectance model, specified by a few parameters (e.g., chlorophyll concentration, backscattering and absorption coefficients at a given wavelength). The model, however, may not be representative of the worldwide ocean conditions, since many variables affecting reflectance are fixed at some average values. In this context, the semi-analytical model of Park and Ruddick (2005), PR05, used in the spectral matching POLYMER algorithm (Steinmetz et al., 2011), is examined in terms of its ability to represent properly water reflectance. The PR05 model depends on chlorophyll-a concentration, a parameter specifying the contribution of algal and non-algal particles to the backscattering coefficient, and a parameter allowing different absorption coefficients for dissolved organic matter. Model estimates at MODIS wavelengths, obtained for a representative set of Case 1 and Case 2 waters, are compared with Hydrolight calculations that include fluorescence and Raman scattering and AERONET-OC measurements. The accuracy of retrieving inherent optical properties (IOPs) using the reconstructed reflectance is also evaluated. The model parameters that give the best fit with the simulated data are determined. Agreement is generally good between the two- or three-parameter model results and Hydrolight/AERONETOC values, even in optically complex waters, with discrepancies much smaller than typical atmospheric correction errors. Significant differences exist in some cases, but having a more intricate model (i.e., using more parameters) might not guarantee convergence of the inversion scheme. The trade-off is between efficiency/robustness and accuracy. Significant errors are observed when using the model estimates to retrieve IOPs. Importantly, the model parameters that best fit the input data, in particular chlorophyll-a concentration, may not represent adequately actual values. The reconstructed water reflectance, not the retrieved model parameters, should be used in bio-optical algorithms.
An algorithm is proposed to perform atmospheric correction of ocean-color imagery in the presence of semi-transparent
clouds. The atmospheric “path” reflectance, due to scattering by molecules, aerosols, and droplets, absorption by
aerosols, and reflection by the surface, including coupling terms, is modeled by a polynomial with three terms, i.e., three
unknown coefficients. The marine reflectance is modeled as a function of chlorophyll concentration and a backscattering
coefficient that accounts for scattering by non-algal particles (or deviation from the backscattering coefficient specified
for typical phytoplankton), i.e., two additional unknown variables. The cloud transmittance, assumed constant spectrally,
is estimated separately from top-of-atmosphere reflectance in the near infrared. The five unknowns are retrieved by an
iterative, spectral matching scheme. The methodology, including the decomposition of the top-of-atmosphere signal and
the modeling of the path reflectance, is evaluated theoretically and applied to actual MODIS imagery acquired over
relatively thin clouds. Chlorophyll concentration is retrieved adequately under the clouds, and continuity is good
between the cloudy and adjacent clear regions. Values are similar to those obtained with the SeaDAS algorithm in clear
sky conditions, but cloud coverage is increased considerably. The algorithm is applicable operationally, but needs to be
further evaluated in varied cloudy situations.
Atmospheric correction of ocean-color imagery in the Arctic brings some specific challenges that the standard
atmospheric correction algorithm does not address, namely low solar elevation, high cloud frequency, multi-layered
polar clouds, presence of ice in the field-of-view, and adjacency effects from highly reflecting surfaces covered by
snow and ice and from clouds. The challenges may be addressed using a flexible atmospheric correction algorithm,
referred to as POLYMER (Steinmetz and al., 2011). This algorithm does not use a specific aerosol model, but fits
the atmospheric reflectance by a polynomial with a non spectral term that accounts for any non spectral scattering
(clouds, coarse aerosol mode) or reflection (glitter, whitecaps, small ice surfaces within the instrument field of
view), a spectral term with a law in wavelength to the power -1 (fine aerosol mode), and a spectral term with a law
in wavelength to the power -4 (molecular scattering, adjacency effects from clouds and white surfaces). Tests are
performed on selected MERIS imagery acquired over Arctic Seas. The derived ocean properties, i.e., marine
reflectance and chlorophyll concentration, are compared with those obtained with the standard MEGS algorithm.
The POLYMER estimates are more realistic in regions affected by the ice environment, e.g., chlorophyll
concentration is higher near the ice edge, and spatial coverage is substantially increased. Good retrievals are
obtained in the presence of thin clouds, with ocean-color features exhibiting spatial continuity from clear to cloudy
regions. The POLYMER estimates of marine reflectance agree better with in situ measurements than the MEGS
estimates. Biases are 0.001 or less in magnitude, except at 412 and 443 nm, where they reach 0.005 and 0.002,
respectively, and root-mean-squared difference decreases from 0.006 at 412 nm to less than 0.001 at 620 and 665
nm. A first application to MODIS imagery is presented, revealing that the POLYMER algorithm is robust when
pixels are contaminated by sea ice.
Ocean color imagery, when viewed from space, is degraded due to scattering by the atmosphere. The effect, also known
as the adjacency effect, is especially important near the coast, sea-ice, and clouds, i.e., where the environment
reflectance is much different from the target reflectance. The adjacency effect, however, may not be negligible in the
open ocean. This is demonstrated by processing SeaWiFS imagery acquired over a typical upwelling system off the
coast of Namibia, Africa. Ignoring the atmospheric point-spread function in the atmospheric correction algorithm or,
equivalently, using a large-target formalism to describe the top-of-atmosphere reflectance, errors reaching over 10% are
made on chlorophyll concentration retrievals. The structure of the spatial field of chlorophyll concentration is changed
significantly after correction of the adjacency effect, with the influence of local processes comparatively decreased with
increased distance. Correcting systematically (i.e., not only near the coast) Level 1b ocean color imagery for the
adjacency effect is recommended. As a result, the accuracy, quality, and daily coverage of aerosol and ocean-color
products would be improved substantially over water surfaces contiguous to land surfaces, sea-ice, clouds, and generally
regions where spatial contrast is relatively large.
POLDER 3 is a multispectral and multidirectional imaging radiometer/polarimeter, the third instrument of the POLarization and Directionality of Earth Reflectances family. It is designed to collect global images of the earth/atmosphere reflectances with a wide field of view of 1600 km and a moderate spatial resolution of 6 km. It was developed and successfully launched onboard the PARASOL microsatellite by the Centre National d'Etudes Spatiales (the French Space Agency) on December 18, 2004, and the first images were acquired on January 7, 2005. The nominal acquisition phase has started on march 10, 2005 after a successful flight commissioning phase. The specificity of this instrument is to measure polarized reflectances for three out of the 10 spectral channels from 443 to 1020 nm, from 16 viewing directions during a single satellite pass.
The purpose of this paper is to present the preliminary ocean color scientific products: marine diffuse reflectances, amount and type of aerosols derived from the atmospheric correction scheme and concentration of chlorophyll pigments. The level 3 products will be compared to another ocean color instruments, MODIS.