Gravitational atmospheric tides as a probe of Titan's interior: Application to Dragonfly

Authors: Benjamin Charnay, Gabriel Tobie, Sébastien Lebonnois, Ralph D. Lorenz

A&A 658, A108 (2022)
arXiv: 2111.02199v1 - DOI (astro-ph.EP)
Accepted for publication in A&A. 10 pages, 8 figures, 1 table
License: CC BY 4.0

Abstract: Context: Saturn's massive gravity is expected to causes a tide in Titan's atmosphere, producing a surface pressure variation through the orbit of Titan and tidal winds in the troposphere. The future Dragonfly mission could analyse this exotic meteorological phenomenon. Aims: We analyse the effect of Saturn's tides on Titan's atmosphere and interior to determine how pressure measurements by Dragonfly could constrain Titan's interior. Methods: We model atmospheric tides with analytical calculations and with a 3D Global Climate Model (the IPSL-Titan GCM), including the tidal response of the interior. Results: We predict that the Love numbers of Titan's interior should verify 1 + Re(k2 - h2) ~ 0.02-0.1 and Im(k2 - h2) < 0.04. The deformation of Titan's interior should therefore strongly weaken gravitational atmospheric tides, yielding a residual surface pressure amplitude of only ~ 5 Pa, with a phase shift of 5-20 hours. Tidal winds are very weak, of the order of 3*10^-4 m/s in the lower troposphere. Finally, constraints from Dragonfly data may permit the real and the imaginary parts of k2 - h2 to be estimated with a precision of ~0.01-0.03. Conclusions: Measurements of pressure variations by Dragonfly over the whole mission could give valuable constraints on the thickness of Titan's ice shell, and via geophysical models, its heat flux and the density of Titan's internal ocean.

Submitted to arXiv on 03 Nov. 2021

Explore the paper tree

Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant

Also access our AI generated Summaries, or ask questions about this paper to our AI assistant.

Look for similar papers (in beta version)

By clicking on the button above, our algorithm will scan all papers in our database to find the closest based on the contents of the full papers and not just on metadata. Please note that it only works for papers that we have generated summaries for and you can rerun it from time to time to get a more accurate result while our database grows.