Abstract

To assess the potential habitability of Jupiter’s moon Europa, it is important to understand its chemical composition (Hand et al., 2007). Young terrain features on Europa’s surface likely consist of material up-welled from the liquid water source below (Wilson et al., 1997; Pappalardo et al., 1998; McCord et al., 1999; Figueredo and Greeley, 2004; Mével and Mercier, 2007), encoding relevant compositional information. A major science objective of NASA’s Europa Clipper mission is to characterize the composition of young terrain features using data acquired on close flybys. The Surface Dust Analyzer (SUDA) is an in situ instrument that collects and analyzes the composition of individual grains (Kempf et al., 2012), which are ejected from Europa’s surface by a continuous bombardment of interplanetary impactors (Krüger et al., 1999, 2003; Goode et al., 2021). By applying a dynamical model of these particles, we compute the probability of SUDA’s detections originating from a given feature along the flyby trajectory based on Monte Carlo (MC) simulations. The time-of-flight (TOF) mass spectra that characterize the chemical composition of individual grains, results in a time series of various compositional types along the flyby. We present here a method to analyze a time series of compositional spectra recorded by SUDA that provides a robust estimate for the abundance of compositional types on the surface, spatially resolved for features along the ground track of the flyby. By demonstrating the association of compositional detections with geological sites of origin, data collected by SUDA can be used to infer the compositional ground truth for terrain features on Europa.