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Spacecraft magnetic field measurements are able to tell us much about the planets' interior dynamics, composition, and evolutionary timeline. Magnetic fields also serve as the source for passive magnetic sounding of moons. Time‐varying magnetic fields experienced by the moons, due to relative planetary motion, interact electrically with conductive layers within these bodies (including salty subsurface oceans) to produce induced magnetic fields that are measurable by nearby, magnetometer‐equipped spacecraft. Many factors influence the character of the induced field, including the precise amplitude and phase of the time‐varying field, known as the excitation or driving field and represented by excitation moments. In this work, we present an open‐source Matlab software package named PlanetMag that features calculation of planetary magnetic field models available in the literature at arbitrary positions and times. The implemented models enable simultaneous inversion of the excitation moments across a range of oscillation frequencies using linear least‐squares methods and ephemeris data with the SPICE toolkit. Here we summarize the available magnetic field models and their associated coordinate systems. Precisely determined excitation moments are a critical input to forward models of global induced fields. Our results serve as a prerequisite to any precise comparison to spacecraft data for magnetic sounding investigation of giant planet moons—connecting the induced magnetic field to a moon's interior requires accurate representation of the oscillating excitation field. We calculate complex excitation moments relative to the J2000 epoch and share the results as ASCII tables compatible with related software packages intended for induction response calculations. Plain Language Summary: Planetary magnetic fields tell us much about a planet's interior, composition, and history. Magnetic fields are also useful for remotely probing the interior of their moons, especially for finding and characterizing potential subsurface oceans. Liquid‐water oceans within the solar system are ideal places to search for habitable environments beyond Earth. Relating spacecraft magnetic measurements to the interior properties of the moons requires an understanding of various related components, including the manner in which the magnetic field applied to the moon changes with time. We have developed an open‐source software package called PlanetMag that uses published magnetic field models to estimate the magnetic field at any point in time and space. It also has the ability to precisely estimate the planetary field oscillations at the location of each large moon in the solar system, which is needed for prediction of the magnetic field response from the moon. Calculations of these magnetic oscillations are provided in text files compatible with existing software. Key Points: We developed an open‐source software package in Matlab called PlanetMag for evaluating planet magnetic field models from the literaturePlanetMag uses ephemeris data and least‐squares inversion methods to determine amplitudes and phases of magnetic excitations for moonsComplex excitation moments are determined for all outer planet large moons in support of magnetic sounding investigations [ABSTRACT FROM AUTHOR]

The open‐source PlanetProfile framework was developed to investigate the interior structure of icy moons based on collectively matching their observed properties and comparative planetology. The software relates observed and measured properties, assumptions such as the type of materials present, and laboratory equation‐of‐state (EOS) data through geophysical and thermodynamic models to evaluate radial profiles of mechanical, thermodynamic, and electrical properties, as self‐consistently as possible. We have created a Python version of PlanetProfile. In the process, we have made optimization improvements and added parallelization and parameter‐space search features to utilize fast operation for investigating unresolved questions in planetary geophysics, in which many model inputs are poorly constrained. The Python version links to other scientific software packages, including for evaluating EOS data, magnetic induction calculations, and seismic calculations. Physical models in PlanetProfile have been reconfigured to improve self‐consistency and generate the most realistic relationships between properties. In this work, we focus on the description of the software design and algorithms in detail, summarize model results for major moons across the outer solar system, and discuss new inferences about the interior structure of several bodies. The high values and narrow uncertainty ranges reported for the axial moments of inertia for Callisto, Titan, and Io are difficult to reconcile with the realistic physical and chemical approximations applied, requiring highly porous rock layers equivalent to incomplete differentiation for Callisto and Titan, and a high rock melt fraction for Io. Radial profiles for each model and comparison to prior work are provided as Zenodo archives. Plain Language Summary: The software package PlanetProfile was developed in order to connect measurable properties of planetary bodies to each other and determine how planetary interiors might be structured. We adapted the existing Matlab version of PlanetProfile to Python and improved it in many ways in the process, to better investigate scientific questions. Python is more widely available, and PlanetProfile now connects better to other scientific software packages capable of relating measurements and observations to the interior structure of planetary bodies such as large moons. PlanetProfile is now more adaptable for new scientific investigations and adding features, includes more realistic relationships between pressures, temperatures, and physical properties of materials, and is optimized for studies that require a wide variety of models to be run. These improvements make PlanetProfile a powerful tool that will become more useful as new features are added. We summarize our models for the major large moons in the outer solar system and provide output files detailing each model. In creating these models, we found that bulk properties for Io, Callisto, and Titan are difficult to combine together into realistic models, which suggests that the reported values may contain errors. Key Points: Radial models of planetary interiors are generated from bulk properties based on geophysical models, lab data, and minimal assumptionsBodies with a high moment of inertia such as Callisto require low‐density rocks, which we model with a high effective porosityModels are optimized for wide parameter‐space searches as needed for investigating unresolved questions about planetary interiors [ABSTRACT FROM AUTHOR]

The discovery of Europa's subsurface ocean has spawned a strong desire by the planetary community to return and assess the ocean's habitability using the magnetic induction signal that Europa generates. NASA has since formulated and developed the Europa Clipper mission with that same goal, anticipating its arrival in the Jovian system in the early 2030s. In parallel, ESA has developed the JUpiter Icy moons Explorer mission to further investigate the interior of Ganymede and other Jovian moons, scheduled to arrive approximately one year later. As a result, extensive work has now been devoted to developing and refining methods to analyse magnetic induction measurements with the goal of characterizing oceans within icy moons, including those in the Neptune and Uranus systems, which are ideal laboratories for such investigations. We present one such method, involving a distance-based inverse and forward modelling approach that leverages self-consistent interior models used to infer ocean and ice-shell properties of various moons that respond inductively to the dynamic magnetic environments in which they reside. We demonstrate the method on a hypothetical ocean within Umbriel, showing the ocean thickness and conductivity constraints that can be inferred from a Monte Carlo error analysis using a three-flyby mission concept. This article is part of the theme issue 'Magnetometric remote sensing of Earth and planetary oceans'. [ABSTRACT FROM AUTHOR]