Deciphering surface properties of the Jovian moons using radiative transfer modelling and NIR data

The Galilean moons are witnesses to unique physical processes and exhibit active phenomena over a wide range of timescales. They are therefore central targets of upcoming exploration missions, notably Europa through NASA’s Europa Clipper mission and Ganymede through ESA’s JUICE mission. These moons are strongly influenced by the intense electromagnetic environment generated by Jupiter and display strong coupling between their surfaces, exospheres, and the Jovian magnetosphere. The surface morphologies observed appear to result from a competition between external processes, such as space weathering [1] and micrometeorite bombardment, and internal processes, such as the upwelling of deep material [2]. The presence of subsurface water reservoirs may enable material exchange between the interiors of these moons and their external environments. This also reinforces their strong exobiological potential and raises important questions regarding their habitability. An improved understanding of the physicochemical properties of their surfaces is therefore a key step in characterising the endogenic and exogenic processes that have governed the evolution of these moons over geological timescales.

The study of surface properties is facilitated by the large volume of data obtained from both ground-based observations and spacecraft missions that have explored the Jovian system. In particular, near-infrared data (1–5 µm) are available at a range of spatial and spectral resolutions. In this study, we focus on observations acquired by JWST/NIRSpec and Galileo/NIMS. Many compounds have already been detected and mapped on these moons [3,4,5], but little is known regarding other properties, such as their grain size and porosity. To robustly estimate the microphysical surface properties, realistic radiative transfer models are required to account for the highly nonlinear scattering interactions occurring within complex surfaces. Here, we present results obtained using the Hapke model [6], considering two distinct cases: (i) a semi-infinite, single-layer granular mixture with a fixed porosity of 50%, and (ii) a two-layer model consisting of a granular medium of variable thickness and porosity overlying a semi-infinite granular substrate. To retrieve volumetric abundances, grain sizes, porosity, and the thickness of the upper layer, we employ a Bayesian inversion approach that has demonstrated its effectiveness in previous surface characterisation studies [7,8].

We present results obtained from several distinct observations of Europa’s trailing hemisphere, as well as multiple spectroscopic inversions performed on JWST observations of Europa and Ganymede. The derived results enable the production of maps of surface microphysical properties. 

[1] Carlson et al., 2005; [2] Pappalardo et al., 1999; [3] Ligier et al., 2016; [4] King et al., 2022; [5] Villanueva et al., 2023; [6] Hapke et al., 2012; [7] Cruz-Mermy et al., 2022; [8] Cruz-Mermy et al., 2025.