Abstract

Abstract. We processed daily ocean-color satellite observations to construct a monthly climatology of phytoplankton pigment concentrations in the Senegalo–Mauritanian region. Our proposed new method primarily consists of associating, in well-identified clusters, similar pixels in terms of ocean-color parameters and in situ pigment concentrations taken from a global ocean database. The association is carried out using a new self-organizing map (2S-SOM). Its major advantage is allowing the specificity of the optical properties of the water to be taken into account by adding specific weights to the different ocean-color parameters and the in situ measurements. In the retrieval phase, the pigment concentration of a pixel is estimated by taking the pigment concentration values associated with the 2S-SOM cluster presenting the ocean-color satellite spectral measurements that are the closest to those of the pixel under study according to some distance. The method was validated by using a cross-validation procedure. We focused our study on the fucoxanthin concentration, which is related to the abundance of diatoms. We showed that the fucoxanthin starts to develop in December, presents its maximum intensity in March when the upwelling intensity is maximum, extends up to the coast of Guinea in April and begins to decrease in May. The results are in agreement with previous observations and recent in situ measurements. The method is very general and can be applied in every oceanic region.

Highlights

  • Phytoplankton are the basis of the ocean food web and drive ocean productivity

  • We propose the retrieval of the major pigment concentrations from satellite ocean-color multispectral sensors in the Senegalo–Mauritanian upwelling, which is an oceanic region off the coast of West Africa where a strong seasonal upwelling occurs (Fig. 1)

  • As in the self-organizing maps (SOMs), we defined clusters that assemble vectors that are close together in terms of a specified distance. This classifier was learned from a worldwide database (DPIG) whose vectors are ocean-color parameters observed by satellite multispectral sensors and associated pigment concentrations measured in situ

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Summary

Introduction

Phytoplankton are the basis of the ocean food web and drive ocean productivity. The light transmitted to the satellite depends on the phytoplankton cell shape (backscattering), its pigments (absorption) and the dissolved matter (e.g., CDOM) This upwelling radiation, the so-called remotely sensed reflectance ρw(λ), is determined by the spectral absorption a and backscattering (bb; m−1) coefficients of the ocean (pure water and various particulate and dissolved matter) using the simplified formulation (Morel and Gentili, 1996). We propose the retrieval of the major pigment concentrations from satellite ocean-color multispectral sensors in the Senegalo–Mauritanian upwelling, which is an oceanic region off the coast of West Africa where a strong seasonal upwelling occurs (Fig. 1).

Materials
The UPSEN database
The SOM clustering
The 2S-SOM classifier
The calibration phase
The pigment retrieval
Statistical validation of the method
Analysis of the topology of the 2S-SOM
Geophysical results
Analysis of the UPSEN campaigns
Discussion
Conclusions
Cost function of the SOM
Findings
Definition of the algorithm 2S-SOM
How the 2S-SOM algorithm works
Full Text
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