On the Inference of Thermal Inversions in Hot Jupiter Atmospheres

Abstract

Several studies in the recent past have inferred the existence of thermal inversions in some transiting hot Jupiter atmospheres. Given the limited data available, the inference of a thermal inversion depends critically on the chemical composition assumed for the atmosphere. In this study, we explore the degeneracies between thermal inversions and molecular abundances in four highly irradiated hot Jupiter atmospheres, dayside observations of which were previously reported to be consistent with thermal inversions based on Spitzer photometry. The four systems are HD 209458b, HAT-P-7b, TrES-4, and TrES-2. We model the exoplanet atmospheres using a one-dimensional line-by-line radiative transfer code with parameterized abundances and temperature structure, and with constraints of energy balance and hydrostatic equilibrium. For each system, we explore the model parameter space with ~10[superscrip 6] models using a Markov chain Monte Carlo routine. Our results primarily suggest that a thorough exploration of the model parameter space is necessary to identify thermal inversions in hot Jupiter atmospheres. We find that existing observations of TrES-4 and TrES-2 can both be fit very precisely with models with and without thermal inversions, and with a wide range in chemical composition. On the other hand, observations of HD 209458b and HAT-P-7b are better fit with thermal inversions than without, as has been reported previously. Physically plausible non-inversion models of HD 209458b and HAT-P-7b fit the data only at the 1.7σ observational errors; better fits require substantial enhancement of methane and depletion of CO, which seems implausible in the very hot atmospheres considered here. Second, in the sample under consideration here, we do not see a correlation between irradiation levels and thermal inversions, given current data. Before JWST becomes available, near-IR observations from the ground and with the Hubble Space Telescope, along with existing Spitzer observations, can potentially resolve thermal inversions in some systems. Observations with only two channels of Warm Spitzer photometry and good signal-to-noise ratio can likely identify or rule out thermal inversions if the difference between the fluxes in the 3.6 and 4.5 μm channels is very high.