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How are Jupiter’s belts and zones affected by deep convection: a parameterized numerical study

Presentation #326.06 in the session Origin and Evolution of Giant Planet Systems II (Poster)

Published onOct 23, 2023
How are Jupiter’s belts and zones affected by deep convection: a parameterized numerical study

Recent studies of the deep jovian atmosphere show that the atmospheric dynamics and composition below the visible cloud deck are highly variable. Observations made using Juno’s Microwave Radiometer (MWR; Janssen et al. 2017, Li et al. 2017, 2020) and the ground-based VLA observatory (de Pater et al. 2019, Moeckel et al. 2023) have provided valuable insight into the depletion of ammonia deep below the expected water cloud level, which have overturned conventional understanding of the structure and dynamics of deep atmosphere. To explain these observations, we need to better understand the role of fluid dynamics at these depths, which is inherently difficult to observe directly due to the opaque upper cloud layers. Particularly, the role of convection in shaping the atmospheric structure at the deeper level is poorly understood, as well as the large variation in convective activity between the cyclonic belts and the anti-cyclonic zones. This is compounded by poor constraints on the atmospheric lapse rate, which is strongly tied to the convective potential of the atmosphere, making it a key proxy for studying deep convective dynamics. However, since temperature is degenerate with molecular absorption in retrieval studies, this creates difficulties when obtaining precise gas abundance measurements at these depths. Therefore, we must use other techniques, such as numerical fluid dynamical simulations, in order to disentangle these degeneracies.

In an effort to interpret these results, and provide insight into the atmospheric dynamics at the deeper levels, we run 3D planetary-scale simulations of cloud formation using the Explicit Planetary hybrid-Isentropic Coordinate (EPIC) General Circulation Model (GCM). To parameterize the belt-zone diversity, we modify the convective potential using different values of Brunt-Vaisala frequencies for the belts and the zones, and observe the resulting variation in convective activity in our model. This parameterization directly allows us to test different lapse rates and their corresponding convective ability in our model. In this work, we present our preliminary results from varying these parameters in our model to diagnose the role and the diversity of deep convection in Jupiter’s tropospheric cloud layers.

REFERENCES

Janssen et al. (2017) DOI: 10.1007/s11214-017-0349-5

Li et al. (2017) DOI: 10.1002/2017GL073159

de Pater et al. (2019) DOI: 10.3847/1538-3881/ab3643

Li et al. (2020) DOI: 10.1038/s41550-020-1009-3

Moeckel et al. (2023) DOI: 10.3847/PSJ/acaf6b

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