Constraining the interior density profile of a Jovian planet from precision gravity field data
Abstract
The external gravity field of a planetary body is determined by the distribution of mass in its interior. Therefore, a measurement of the external field, properly interpreted, tells us about the interior density profile, ρ(r), which in turn can be used to constrain the composition in the interior and thereby learn about the formation mechanism of the planet. Planetary gravity fields are usually described by the coefficients in an expansion of the gravitational potential. Recently, high precision measurements of these coefficients for Jupiter and Saturn have been made by the radio science instruments on the Juno and Cassini spacecraft, respectively.The resulting coefficients come with an associated uncertainty. And while the task of matching a given density profile with a given set of gravity coefficients is relatively straightforward, the question of how best to account for the uncertainty is not. In essentially all prior work on matching models to gravity field data, inferences about planetary structure have rested on imperfect knowledge of the H/He equation of state and on the assumption of an adiabatic interior. Here we wish to vastly expand the phase space of such calculations. We present a framework for describing all the possible interior density structures of a Jovian planet, constrained only by a given set of gravity coefficients and their associated uncertainties. Our approach is statistical. We produce a random sample of ρ(a) curves drawn from the underlying (and unknown) probability distribution of all curves, where ρ is the density on an interior level surface with equatorial radius a. Since the resulting set of density curves is a random sample, that is, curves appear with frequency proportional to the likelihood of their being consistent with the measured gravity, we can compute probability distributions for any quantity that is a function of ρ, such as central pressure, oblateness, core mass and radius, etc. Our approach is also bayesian, in that it can utilize any prior assumptions about the planet's interior, as necessary, without being overly constrained by them.We demonstrate this approach with a sample of Jupiter interior models based on recent Juno data and discuss prospects for Saturn.
- Publication:
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AAS/Division for Planetary Sciences Meeting Abstracts #49
- Pub Date:
- October 2017
- Bibcode:
- 2017DPS....4930301M