Presentation #102.39 in the session Poster Session.
The hot Jupiter exoplanet population is extremely diverse, spanning more than an order of magnitude in instellation, atmospheric metallicity, gravity and rotation period. With the James Webb Space telescope and, later, Ariel mission providing wide wavelength coverage and ground-based telescopes supplying high resolution data, hot Jupiters will continue to be the best targets for atmospheric characterisation as we enter a new era of high-quality exoplanet observation. A hierarchy of atmospheric models have been used to model these planets, often trading modelling complexity for computational speed and cost. Yet, most of these planets are tidally locked and their atmospheres are intrinsically 3D, meaning they cannot be fully understood using a lower-dimensionality approach.
Calculated using the state-of-the-art non-grey global circulation model SPARC/MiTgcm, we here create the largest library of 3D hot Jupiter models yet. This consists of 149 models spanning a wide range of instellation, metallicity, gravity and rotation periods typical for Hot Jupiters. Additional models including the strong photo-absorbing molecules TiO and VO are also calculated for higher instellations. In addition to systematically varying these parameters, we also vary them jointly, something which has not been incorporated in any previous studies to date. From these simulations, we calculate secondary eclipse spectra and phase curves to investigate how day-to-night heat redistribution and spectral properties vary with planetary parameters and identify any resulting qualitative trends. From this analysis we observe large variations in the observable properties of hot Jupiter atmospheres. For example, at a given equilibrium temperature we find that the heat redistribution can vary by a factor 2 when the joint effects of metallicity, rotation period and gravity are taken into account. This means that, when working in synergy, intrinsic planetary parameters may cause divergence from previously computed models by a factor greater than any other additional processes such as nightside clouds, chemistry or MHD effects.
Through further analysis of this grid, we are able to calculate the direct impact on observable features for each of our model parameters. Then, by interpolating the results, we compare the expected population trends between the observed and model population and discuss whether the scatter seen around these trends comes naturally from variations in planet parameters, or if additional effects need to be considered.