A TEMPERATURE AND ABUNDANCE RETRIEVAL METHOD FOR EXOPLANET ATMOSPHERES

Abstract

We present a new method to retrieve molecular abundances and temperature profiles from exoplanet atmosphere photometry and spectroscopy. We run millions of one-dimensional (1D) atmosphere models in order to cover the large range of allowed parameter space. In order to run such a large number of models, we have developed a parametric pressure–temperature ( P – T ) profile coupled with line-by-line radiative transfer, hydrostatic equilibrium, and energy balance, along with prescriptions for non-equilibrium molecular composition and energy redistribution. The major difference from traditional 1D radiative transfer models is the parametric P – T profile, which essentially means adopting energy balance only at the top of the atmosphere and not in each layer. We see the parametric P – T model as a parallel approach to the traditional exoplanet atmosphere models that rely on several free parameters to encompass unknown absorbers and energy redistribution. The parametric P – T profile captures the basic physical features of temperature structures in planetary atmospheres (including temperature inversions), and fits a wide range of published P – T profiles, including those of solar system planets. We apply our temperature and abundance retrieval method to the atmospheres of two transiting exoplanets, HD 189733b and HD 209458b, which have the best Spitzer and Hubble Space Telescope data available. For HD 189733b, we find efficient day–night redistribution of energy in the atmosphere, and molecular abundance constraints confirming the presence of H 2 O, CO, CH 4 , and CO 2 . For HD 209458b, we confirm and constrain the dayside thermal inversion in an average 1D temperature profile. We also report independent detections of H 2 O, CO, CH 4 , and CO 2 on the dayside of HD 209458b, based on six-channel Spitzer photometry. We report constraints for HD 189733b due to individual data sets separately; a few key observations are variable in different data sets at similar wavelengths. Moreover, a noticeably strong CO 2 absorption in one data set is significantly weaker in another. We must, therefore, acknowledge the strong possibility that the atmosphere is variable, both in its energy redistribution state and in the chemical abundances.