Variability in the Uranian atmosphere: Uranus' north polar hood

Uranus’ atmosphere, once thought to be bland and static, has, in recent years, been shown to be anything but that. Radiative transfer retrieval analysis of high-resolution telescope observations has uncovered a dynamic atmosphere, displaying seasonal change and latitudinal variability. Uranus’ atmosphere is enshrouded in a global cloud/haze, meaning a robust aerosol layer model is required to probe any variability observed in its discrete features. One such example is its north polar hood, a bright ‘cap-like’ feature enshrouding the polar region northwards of ~45°N latitude (Fig. 1). Figure 1: A false colour HST/WFC3 image of Uranus taken in 2018 displaying the north polar hood at the top right of the disc. However, using remotely-sensed observations leads to a highly degenerate problem, resulting in competing aerosol models. Here we employ one such holistic aerosol model, derived by Prof. Patrick Irwin, in combination with the NEMESIS radiative transfer retrieval code. We utilise both space-based and ground-based observations to analyse the development of this hood over time, using the Minnaert approximation (Eqn. 1) to carry out a limb-darkening analysis of our observations to provide further constraint on our retrievals (demonstrated by Irwin et al., 2021). I/F = (I/F)0μ0kµk-1 (1) We demonstrate latitudinal variability in the methane volume mixing ratio via retrievals on HST/STIS and VLT/MUSE data. We then provide definitive evidence that a change in aerosol layers is a direct cause of brightening observed in the hood over time, and we display retrieval results on HST/WFC3 data spanning 2014 - 2021 to reveal what we find this change to be. This change is currently hypothesised as an increase in opacity of the middle (~1 - 2 bar) haze layer in the holistic model. These results strengthen the case for the holistic aerosol model and provide important context for the upcoming orbiter-probe mission to Uranus. Further scrutiny of this holistic aerosol model by employing it to the modelling of other discrete features will be valuable future work.