Journal of Geophysical Research: Oceans

Estimation of the sunglint radiance field from optical satellite imagery over open ocean: Multidirectional approach and polarization aspects

Authors

  • Tristan Harmel,

    Corresponding author
    1. CNRS, Laboratoire Océanographie de Villefranche Villefranche sur Mer, France
    • Université Pierre et Marie Curie, Laboratoire Océanographie de Villefranche, Villefranche sur Mer, France
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  • Malik Chami

    1. Université Pierre et Marie Curie, Laboratoire Océanographie de Villefranche, Villefranche sur Mer, France
    2. CNRS, Laboratoire Océanographie de Villefranche Villefranche sur Mer, France
    3. Institut Universitaire de France
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Corresponding author: T. Harmel, Université Pierre et Marie Curie, Laboratoire Océanographie de Villefranche, 06230 Villefranche sur Mer, France. (harmel@obs-vlfr.fr)

Abstract

[1] Radiometric satellite measurements over the ocean are greatly affected by the contribution of the direct sunlight reflected on the ruffled ocean (so-called sunglint). Sunglint produces radiance that can far exceed the radiance scattered by both the atmosphere and ocean layers. Knowledge of the sunglint radiance is required in many remote sensing applications using radiance and polarization information (e.g., retrieval of aerosol or hydrosol optical properties, sensor calibration). The Cox and Munk model is currently used for estimating sunglint signal, but its accuracy is mainly limited by the mandatory use of wind speed data sets. An algorithm (so-called polarization-based atmospheric correction glint) was developed based on the original multidirectional and polarization radiometric measurements of the Polarization and Anisotropy of Reflectances for Atmospheric Sciences Coupled with Observations from a Lidar satellite mission. The method enables to accurately estimate the radiance and the polarization terms of the sunglint signal. The strength of the algorithm is to quantify the sunglint radiation using the Polarization and Anisotropy of Reflectances for Atmospheric Sciences Coupled with Observations from a Lidar data without any a priori information on the actual sea state A relevant application of the algorithm is proposed to better detect the pixels influenced by clouds provided that ancillary data of wind speed are used.