Comparing atmospheric models of Jupiter, can we reduce the degeneracy of this problem?

The grand appearance of Jupiter’s banded atmosphere, coloured with many shades from white to red, whose cloud structure currently remains elusive with no clear single cloud model responsible for this varied appearance. With a general pattern of alternating bright cloudy zones and darker belts, as well as unique regions such as the Great Red Spot, finding a way to model all of these differing appearances with a single model has proven difficult. Jupiter’s atmosphere provides continual challenges when attempting to characterise its cloud structure due to its frequently varying appearance. This leads to differences between every observation meaning that models are constantly having to adapt to be explain these changes. Such changes can be seen in Figure 1, both of these spectra have been extracted for the same region of the Equatorial Zone (EZ) but are not identical due to the changes in appearance over the 3 years. 

Recent works [1,2,3,4] have all attempted to model Jupiter’s atmosphere using a universal chromophore (cloud colouring compound), combined with a deeper conservatively-scattering cloud and also a stratospheric haze layer. These works have all been able to model the atmosphere successfully but it has currently not been possible to determine between these differing solutions to find the most likely representation of the atmosphere. As all the different sets ups have several ways to vary cloud structure and chromophore properties among other parameters, they have been able to fit the changes in the observations. Therefore keeping each set up viable even as the atmosphere changes. The current inability to conclude on a favoured cloud structure highlights the highly degenerate nature of this problem.

Utilising new observations and techniques to analyse the data highlights the delicacy of these results as the previous set ups have to be altered in order to produce the desired fit to the new observations once the input have varied slightly. An unchanged fit is shown in Figure 1, where the ideal fit of the EZ in 2018 has been used for 2021 data and is unable to model the spectra as well as for the spectra which it was derived from. Furthermore introduction of a limb viewing technique, as used in [2], has been done for this data. Here we attempt to fit multiple viewing angles simultaneously, which also begins to question the robustness of these results, due to an inability of nadir derived set ups to reproduce the multiple observations as successfully. 

Therefore in this work we have begun to attempt to reduce the degeneracy of the problem before utilising the Non-linear optimal Estimator for Multi-variatE spectral analySIS (NEMESIS) radiative-transfer retrieval algorithm [5], to fit to our observations. From this we want to find a vertical cloud structure which is more reproducible using different observations and techniques. It is hoped that reducing one of the degenerate parameters before fitting will allow us to constrain the atmospheric structure more decisively. Furthermore combining this with the limb darkening technique will hopefully allow us to rule out some of the solutions to this highly degenerate problem to find more confidence in the proposed models. 

In this work we will present the preliminary results taken from the application of these methods to observations to derive a new atmospheric model which can be compared with past work. Additionally we will present the use of new techniques to determine the ability of previous models to adapt to new observations to see if they are still viable. 

Figure 1: Spectra of the Equatorial Zone in both 2018 and 2021 and the spectral fit using the model from [1] derived for the 2018 data. 

[1] Braude, A. S., Irwin, P. G., Orton, G. S., and Fletcher, L. N. (2020). Colour and tropospheric cloud structure of jupiter from muse/vlt: Retrieving a universal chromophore. Icarus, 338:113589. 

[2] Pérez-Hoyos, S., Sánchez-Lavega, A., Sanz-Requena, J., Barrado-Izagirre, N., Carrión-González, O., Anguiano-Arteaga, A., Irwin, P., and Braude, A. (2020). Color and aerosol changes in jupiter after a north temperate belt disturbance. Icarus, 352:114031.

[3] Dahl, E. K., Chanover, N. J., Orton, G. S., Baines, K. H., Sinclair, J. A., Voelz, D. G., Wijerathna, E. A., Strycker, P. D., and Irwin, P. G. J. (2021). Vertical structure and color of jovian latitudinal cloud bands during the juno era. The Planetary Science Journal, 2(1):16. 

[4] Baines, K., Sromovsky, L., Carlson, R., Momary, T., and Fry, P. (2019). The visual spectrum of jupiter’s great red spot accurately modeled with aerosols produced by photolyzed ammonia reacting with acetylene. Icarus, 330:217–229.

[5] Irwin, P. G. J., Teanby, N. A., de Kok, R., Fletcher, L. N., Howett, C. J. A., Tsang, C. C. C., Wilson, C. F., Calcutt, S. B., Nixon, C. A., and Parrish, P. D. (2008). The NEMESIS planetary atmosphere radiative transfer and retrieval tool. , 109:1136–1150