Callisto: Signatures of plasma interaction, induction, and energetic particle dynamics at the Galilean moon
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Liuzzo, Lucas
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Abstract
Beneath the icy crust of Jupiter’s moon Callisto lies a putative liquid saltwater ocean. Properties of this ocean can be constrained through electromagnetic sounding: the 9.6° tilt between Jupiter's magnetic and rotational axes generates a time-varying magnetic field at Callisto, inducing currents within its ocean that manifest as a dipolar magnetic field outside of the moon. During the first two Callisto flybys of the Galileo mission to Jupiter, a clear induction signature was detected, but could be used to only weakly constrain properties of the subsurface ocean. However, these first encounters occurred under special conditions: Callisto's magnetic environment was only weakly perturbed by currents in the ambient plasma. In general, however, Callisto's magnetic environment is strongly disturbed by the interaction between the moon and Jupiter's magnetospheric plasma. Thus, even though Galileo performed seven flybys of Callisto while the magnetometer instrument was operational, none of the five remaining encounters detected Callisto's inductive response in isolation from magnetic perturbations generated by this plasma interaction. Callisto’s orbital period is forty times larger than Jupiter’s rotational period, so the moon is constantly overtaken by plasma that corotates with the planet and interacts with Callisto’s induced dipole, its atmosphere, and its ionosphere. The resulting interaction causes the magnetospheric field to pile up and drape around Callisto, and generates perturbations in the plasma flow patterns and electromagnetic fields near the moon. As a result, Callisto's induced field becomes partially obscured by these plasma effects. Identifying Callisto’s inductive response and further characterizing its interior is not possible without accounting for this plasma interaction. However, accurately representing these effects is particularly challenging: the large gyroradii of pickup ions from Callisto's ionosphere generate substantial asymmetries in the plasma flow and magnetic field that are omnipresent near the moon. Thus, unlike at the other Galilean moons, a kinetic representation of these ions is mandatory to characterize Callisto’s plasma environment. Yet before this project, no studies had attempted to account for this interaction nor search unexamined Galileo magnetometer data for signatures of the subsurface ocean, despite its poorly constrained properties. To close this gap in our understanding of Callisto, we have developed a three-dimensional hybrid (kinetic ions, fluid electrons) model of the moon’s interaction that accurately represents the highly asymmetric plasma environment. This model is applied to examine magnetometer data from all seven Galileo flybys of Callisto. We develop a coherent strategy that pinpoints regions near Callisto where its induced field locally dominates the magnetic perturbations, despite the complex admixture of effects that shape the magnetic environment. In addition, we investigate whether Callisto's inductive signature will be detectable in isolation from plasma effects during flybys of the upcoming JUpiter ICy moons Explorer (JUICE) mission to be launched in 2022. These results are imperative for the successful planning of magnetic field and plasma observations during JUICE and the search for habitable niches in the Jovian system. Due to challenges associated with identifying Callisto's induced dipole in magnetic field data, we explore the possibility of applying plasma particle data as an auxiliary tool to constrain the moon's subsurface ocean. For this purpose, we combine electromagnetic field output from the hybrid simulations with a particle tracing model for energetic ions. With this approach, we show that Callisto's induced dipole indeed leaves a distinct imprint in the dynamics of energetic ions from Jupiter's magnetosphere, thus providing a framework for future missions that aids detection of Callisto's inductive response in energetic ion data.
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2018-10-23
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Dissertation