On the role of the seawater absorption-to-attenuation ratio in the radiance polarization above the southern Baltic surface

Abstract

Abstract. Information about polarization of light leaving the ocean surface has the potential to improve the quality of bio-optical parameter retrieval from ocean color remote sensing (OCRS). This improvement can be applied in numerous ways, such as limiting of Sun glints and obtaining information about atmospheric aerosol properties for atmospheric correction as well as increasing the accuracy of the algorithms based on the water-leaving signal. Polarization signals at the top of the atmosphere (ToA) that include the water-leaving signal are strongly influenced by atmospheric molecular scattering and by direct Sun and sky reflections from the sea surface. For these reasons, it is necessary to better understand the factors that change the polarization of light in the atmosphere–ocean system, especially in coastal zones affected by dynamic changes. In this paper, the influence of seasonal variability of light absorption and scattering coefficients (inherent optical properties; IOPs) of seawater, wind speed and solar zenith angle (SZA) on the polarization of upwelling radiance over the sea surface in the visible light bands is discussed. The results come from a polarized radiative transfer model based on the Monte Carlo code and applied to the atmosphere–ocean system using averaged IOPs as input data. The results, presented in the form of polar plots of the total upwelling radiance degree of polarization (DoP), indicate that regardless of the wavelength of light and type of water, the highest value of the above-water DoP is strongly correlated with the absorption-to-attenuation ratio. The correlation is a power function that depends on both the SZA and the wind speed. The correlation versatility for different wavelengths of light is very unusual in optics of the sea and is therefore worth emphasizing.

Reflection Spectra Coupling Analysis and Polarized Modeling of Optically Active Particles in Lakes

“…The state of this attribute will change due to the interaction with the medium when light propagates through the water. The time of depolarization in the transfer process is much longer than that of diffusion, which can well maintain the polarization state characteristics, so it is more effective in analyzing the coupling characteristics of different particles in the water and distinguishing different components of the water [11,12]. In recent years, researchers have used polarized spectroscopy to detect water, which shows the potential of polarization information.…”

Simulation of Parallel Polarization Radiance for Retrieving Chlorophyll a Concentrations in Open Oceans Based on Spaceborne Polarization Crossfire Strategy

“…Advances in polarimetric remote sensing (PRS) not only effectively improves the retrieval accuracy of aerosol and hydrosol particles [16][17][18], but it is also becoming increasingly important for understanding the microphysics and optical properties of particulates in the AOS [5,19,20]. From the radiative transfer simulations and field measurements, it has been proved that polarization information on the upwelling radiation can retrieve the inorganic particle concentrations [21,22], chlorophyll fluorescence [23], and IOPs [24][25][26]. For example, Chami and Platel [26] used a neural network (NN) to indicate that the polarization and directional variations of reflectance can significantly improve the retrieval of scattering coefficients by 75% and 60%, respectively.…”

Hydrosol Scattering Matrix Inversion Across a Fresnel Boundary

“…Despite these challenges, advances are being made in the use of polarimetry for ocean color remote sensing (Chowdhary et al, 2006;Harmel, 2016;Chowdhary et al, 2019;El-Habashi et al, 2021). Of particular interest are the survivability of the polarized underwater signal through the airsea interface (Mobley, 2015;Foster and Gilerson, 2016;Hieronymi, 2016;Dolin and Turlaev, 2020), correcting for reflected Sun and skylight (Avrahamy et al, 2019;Carrizo et al, 2019), and retrieval algorithms to estimate water parameters, such as the total attenuation coefficient (Ibrahim et al, 2016;Freda et al, 2019;Gilerson et al, 2020) and the chlorophyll-a concentration (Wang et al, 2017;El-Habashi, 2018).…”