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European Geosciences Union, Cryosphere Discussions, 5(9), p. 5137-5169, 2015

DOI: 10.5194/tcd-9-5137-2015

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Radiative transfer model for contaminated slabs: experimental validations

Journal article published in 2015 by F. Andrieu, F. Schmidt, B. Schmitt ORCID, S. Douté, O. Brissaud
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

This article presents a set of spectro-goniometric measurements of different water ice samples and the comparison with an approximated radiative transfer model. The experiments were done using the spectro-radiogoniometer described in Brissaud et al. (2004). The radiative transfer model assumes an isotropization of the flux after the second interface and is fully described in Andrieu et al. (2015). Two kinds of experiments were conducted. First, the specular spot was closely investigated, at high angular resolution, at the wavelength of 1.5 μm, where ice behaves as a very absorbing media. Second, the bidirectional reflectance was sampled at various geometries, including low phase angles on 61 wavelengths ranging from 0.8 to 2.0 μm. In order to validate the model, we made qualitative tests to demonstrate the relative isotropization of the flux. We also conducted quantitative assessments by using a Bayesian inversion method in order to estimate the parameters (e.g., sample thickness, surface roughness) from the radiative measurements only. A simple comparison between the retrieved parameters and the direct independent measurements allowed us to validate the model. We developed an innovative Bayesian inversion approach to quantitatively estimate the uncertainties in the parameters avoiding the usual slow Monte Carlo approach. First we built lookup tables, and then we searched the best fits and calculated a posteriori density probability functions. The results show that the model is able to reproduce the geometrical energy distribution in the specular spot, as well as the spectral behavior of water ice slabs. In addition, the different parameters of the model are compatible with independent measurements.

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