Enceladus surface properties using Cassini/VIMS hyperspectral data

Enceladus is one of the most intriguing icy moons of the solar system, exhibiting active cryovolcanism and continuous plume activity at its south pole [1]. The surface in this region is geologically young and frequently resurfaced by plume fallout and tectonic activity [2]. While numerous studies have mapped compositional variations using Cassini-VIMS data [3,4], few have quantified the microphysical properties of water ice—including grain size, crystallinity and surface roughness—over the full VIMS spectral range. Understanding these parameters is critical for interpreting the thermal and geological evolution of the surface and for tracing exchanges between the subsurface ocean and the surface.

Here, we present a comprehensive study in which we fit VIMS reflectance spectra across the 1.0–5 µm range to estimate key microphysical properties of Enceladus's surface. We apply a Hapke-based radiative transfer model [5,6] in a Bayesian Markov Chain Monte Carlo (MCMC) framework [7] to retrieve the posterior distributions of ice crystallinity, grain size and surface roughness for selected observations. We use the optical constants of Mastrapa et al. [8], which provide laboratory measurements of crystalline and amorphous water ice at temperatures from 20 to 150 K. The full-spectrum inversion enables robust fitting of broad and narrow features, including the diagnostic absorption band at 1.65 µm, which appears only in crystalline ice [9]. This band is not used as an isolated fitting constraint but is reproduced by the model if crystalline ice is present at the appropriate temperature. We find that its shape and central wavelength are well matched in many spectra, especially in the South terrains, where the inversion yields low temperatures (<80 K) and small grain sizes (≈100 µm), consistent with recent deposition from plume fallout [10]. In more distant terrains, the 1.65 µm feature is attenuated or absent, consistent with amorphous or thermally evolved ice.

The retrieved parameters show coherent spatial patterns: the active fractures exhibit cold, fine-grained, highly crystalline ice, while surrounding plains display warmer, more amorphous and coarser-grained surfaces. These gradients are consistent with a combination of deposition, thermal metamorphism, and radiation-induced amorphization [11]. This work demonstrates the potential of full-spectrum Bayesian inversion using physically grounded optical constants to extract detailed microphysical information from VIMS data. The methodology provides quantitative estimate of abundances, grain size, and crystallinity—key parameters for understanding the surface evolution of Enceladus. 

References


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