Forward Modeling of the Phobos Tides and applications to the InSight Mission

By using the VBB seismometer as a gravimeter on the surface of Mars, the InSight mission will provide long-period data suited to tidal analysis (Lognonne et al. 1996, 2019). The tidal response of Mars, due to the Sun and the Martian moons, Phobos and Deimos, provides information about the interior structure of Mars, notably on the state and size of its core: most notably, the proximity of Phobos means that degree-2, -3 -4 and further tides are all present and will be sensitive to the elastic properties of different depth ranges within Mars (Van Hoolst et al. 2003). Solar tides are larger but have the same period as major noise sources such as temperature variations. In contrast, although smaller, the Phobos tides occupy a range of frequencies separate from these major noise peaks (Pou et al. 2018).

We build a forward model of the expected acceleration recorded by InSight due to the Phobos tides using ephemerides from the JPL Horizons website to take into account all the physical parameters of Phobos' orbit, such as eccentricity, inclination, obliquity and apsidal precession. The amplitudes of these tidal variations are modeled using a viscoelastic Mars model, taking into account the potential temperature of the Martian mantle; the mean lithospheric thickness; and the core state, radius and thermodynamic modeling (Rivoldini et al. 2011, Nimmo and Faul 2013, Khan et al. 2018).

This model has two uses: combined with a noise model (Pou et al. 2016), it evaluates how well data processing methods such as stacking work, and how uncertain the retrieved tidal parameters are. Then, it provides a template which can be compared with the actual observations from InSight to infer the tidal amplitudes and phase lags. In order to resolve the state of the core, the tidal amplitudes will need to be measured with an uncertainty of 1% or better. The effect on the phase lag Q of the core state is different to that of varying the mantle temperature; a measurement of degree 3 Q3 and/or degree 4 Q4 to a precision of about 10% would allow these two effects to be disentangled.

In addition, a status on the reduction of the data noise coming from the external sources such as thermal instrument noise (Mimoun et al. 2016, Pou et al. 2018) will be presented.