Vivien Parmentier

Abstract:

Phase curves are the best technique to probe the three dimensional structure of exoplanets' atmospheres. In this chapter we first review current exoplanets phase curve observations and the particular challenges they face. We then describe the different physical mechanisms shaping the atmospheric phase curves of highly irradiated tidally locked exoplanets. Finally, we discuss the potential for future missions to further advance our understanding of these new worlds.

Abstract:

ABSTRACT The determination of atmospheric structure and molecular abundances of planetary atmospheres via spectroscopy involves direct comparisons between models and data. While varying in sophistication, most model spectra comparisons fundamentally assume one-dimensional (1D) model physics. However, knowledge from general circulation models and of solar system planets suggests that planetary atmospheres are inherently three-dimensional in their structure and composition. We explore the potential biases resulting from standard “1D” assumptions within a Bayesian atmospheric retrieval framework. Specifically, we show how the assumption of a single 1D thermal profile can bias our interpretation of the thermal emission spectrum of a hot Jupiter atmosphere that is composed of two thermal profiles. We retrieve spectra of unresolved model planets as observed with a combination of the Hubble Space Telescope Wide Field Camera 3 (WFC3)+Spitzer Infrared Array Camera (IRAC) as well as the James Webb Space Telescope (JWST) under varying differences in the two thermal profiles. For WFC3+IRAC, there is a significantly biased estimate of CH4 abundance using a 1D model when the contrast is 80%. For JWST, two thermal profiles are required to adequately interpret the data and estimate the abundances when contrast is greater than 40%. We also apply this preliminary concept to the recent WFC3+IRAC phase curve data of the hot Jupiter WASP-43b. We see similar behavior as present in our simulated data: while the abundance determination is robust, CH4 is artificially well-constrained to incorrect values under the 1D assumption. Our work demonstrates the need to evaluate model assumptions in order to extract meaningful constraints from atmospheric spectra and motivates exploration of optimal observational setups.