Bayesian analysis of Juno/JIRAM's NIR observations of Europa
Ishan Mishra, Nikole Lewis, Jonathan Lunine, Paul Helfenstein, Ryan J., MacDonald, Gianrico Filacchione, Mauro Ciarniello

TL;DR
This paper introduces a Bayesian spectral inversion framework to analyze Juno/JIRAM's NIR observations of Europa, revealing the coexistence of amorphous and crystalline water ice with detailed grain size estimates.
Contribution
The paper presents a novel Bayesian spectral inversion method validated with simulations and laboratory data, applied to Europa's NIR spectra to distinguish ice phases and quantify grain sizes.
Findings
Both amorphous and crystalline ice are present on Europa.
The amorphous ice dominates with over 99% volume fraction.
The model spectrum shows tension around specific wavelengths, suggesting additional non-ice components.
Abstract
Juno spacecraft's spectrometer JIRAM recently observed the moon Europa in the 2-5 {\mu}m wavelength region. Here we present analysis of the average spectrum of a set of observations near 20{\deg}N and 40{\deg}W, focusing on the two forms of water-ice - amorphous and crystalline. We also take this as an opportunity to present a novel Bayesian spectral inversion framework for reflectance spectroscopy. We first validate this framework using simulated spectra of amorphous and crystalline ice mixtures and a laboratory spectrum of crystalline ice. We next analyze the JIRAM data and, through Bayesian model comparisons, find that a two-component intimately mixed model (TC-IM model) of amorphous and crystalline ice is strongly preferred (at 26{\sigma} confidence) over a two-component model of the same species but where their spectra are areally/linearly mixed. We also find that the TC-IM model…
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Taxonomy
TopicsAstro and Planetary Science · Space Exploration and Technology · Spacecraft and Cryogenic Technologies
