The Planetary Science Journal (Jan 2023)

Revealing the Interior Structure of Icy Moons with a Bayesian Approach to Magnetic Induction Measurements

  • John B. Biersteker,
  • Benjamin P. Weiss,
  • Corey J. Cochrane,
  • Camilla D. K. Harris,
  • Xianzhe Jia,
  • Krishan K. Khurana,
  • Jiang Liu,
  • Neil Murphy,
  • Carol A. Raymond

DOI
https://doi.org/10.3847/PSJ/acc331
Journal volume & issue
Vol. 4, no. 4
p. 62

Abstract

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Some icy moons and small bodies in the solar system are believed to host subsurface liquid water oceans. The interaction of these saline, electrically conductive oceans with time-varying external magnetic fields generates induced magnetic fields. Magnetometry observations of these induced fields in turn enable the detection and characterization of these oceans. We present a framework for characterizing the interiors of icy moons using multifrequency induction and Bayesian inference applied to magnetometry measurements anticipated from the upcoming Europa Clipper mission. Using simulated data from the Europa Clipper Magnetometer, our approach can accurately retrieve a wide range of plausible internal structures for Europa. In particular, the ocean conductivity is recovered to within ±50% for all internal structure scenarios considered, and the ocean thickness can be retrieved to within ±25 km for five out of seven scenarios. Characterization of the ice shell thickness to ±50% is possible for six of seven scenarios. Our recovery of the ice shell thickness is highly contingent on accurate modeling of magnetic fields arising from the interaction of Europa with the ambient magnetospheric plasma, while the ocean thickness is more modestly affected and the ocean conductivity retrieval is largely unchanged. Furthermore, we find that the addition of a priori constraints (e.g., static gravity measurements) can yield improved ocean characterization compared to magnetometry alone, suggesting that multi-instrument techniques can play a key role in revealing the interiors of Europa and other ocean worlds.

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