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Deep clouds on Jupiter

Presentation #415.06 in the session Giant Planet Atmospheres (iPosters).

Published onOct 20, 2022
Deep clouds on Jupiter

Deep clouds have been used to constrain the O/H abundance on Jupiter, because higher abundances are needed for cloud condensation at greater depth. But the mapping between cloud pressure level and O/H abundance is a function of the temperature structure, which varies horizontally and vertically on Jupiter and is not well constrained in the water condensation region. In this presentation, we explore how the full range of possible temperatures affects the mapping between cloud pressure level and O/H abundance.

The figure considers a wide range of temperatures at the 500-mbar level from 128 K to 142 K (y-axis), spanning values retrieved from Voyager IRIS, Cassini CIRS, and ground-based TEXES measurements (Simon-Miller++2006, Fletcher++2016). The temperature range encompasses Voyager radio occultation and Galileo Probe values (Gupta++2022, Seiff++1998). Contours give O/H abundances relative to protosolar (Asplund++2009) as a function of the water lifting condensation level (x-axis). The left panel is for a stable vertical profile consistent with Galileo Probe data and various models (Magalhães++2002, Wong++2011), and the right panel is for the adiabatic case. Calculations use the equilibrium cloud condensation model (Weidenschilling+Lewis1973, Atreya+Romani1985, Wong++2015).

We will apply this result to data from two sources capable of constraining the pressure level of deep clouds: high resolution 5-micron spectroscopic observations, and methane-band imaging at high spatial resolution. The spectral approach uses CH3D line widths, which increase with depth due to pressure broadening, unless truncated by an opaque cloud in the water condensation region (Bjoraker++2022). The imaging approach focuses on features visible in continuum images but not in the 727-nm weak methane-band filter, and it has been applied to remote sensing data from Galileo, Cassini, and Hubble Space Telescope (Banfield++1998,Porco++2003,Wong++2020).

REFERENCES (DOIs) Asplund++2009: 10.1146/annurev.astro.46.060407.145222 Atreya+Romani1985: ADS 1985rapm.book...17A Banfield++1998: 10.1006/icar.1998.5985 Bjoraker++2022: Same DPS session Fletcher++2016: 10.1016/j.icarus.2016.06.008 Gupta++2022: 10.3847/PSJ/ac6956 Magalhães++2002: 10.1006/icar.2002.6891 Porco++2003: 10.1126/science.1079462 Seiff++1998: 10.1029/98JE01766 Simon-Miller++2006: 10.1016/j.icarus.2005.07.019 Weidenschilling+Lewis1973: 10.1016/0019-1035(73)90019-5 Wong++2011: 10.1016/j.icarus.2011.06.032 Wong++2015: 10.1016/j.icarus.2014.09.042 Wong++2020: 10.3847/1538-4365/ab775f

Figure 1

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