The atmospheric circulation of a nine-hot Jupiter sample: Probing circulation and chemistry over a wide phase space

TL;DR

This study models the atmospheric circulation and chemistry of nine hot Jupiters, revealing diverse cloud properties, temperature variations, and chemical abundances, with implications for future high-resolution spectroscopic observations.

Contribution

It provides a comprehensive circulation and chemistry model grid for nine hot Jupiters, linking observed spectral diversity to atmospheric dynamics and composition.

Findings

Model recovers equatorial superrotation trends.

Temperature differences can reach hundreds of Kelvin.

Models match many Spitzer eclipse observations.

Abstract

We present results from an atmospheric circulation study of nine hot Jupiters that comprise a large transmission spectral survey using the Hubble and Spitzer Space Telescopes. These observations exhibit a range of spectral behavior over optical and infrared wavelengths which suggest diverse cloud and haze properties in their atmospheres. By utilizing the specific system parameters for each planet, we naturally probe a wide phase space in planet radius, gravity, orbital period, and equilibrium temperature. First, we show that our model "grid" recovers trends shown in traditional parametric studies of hot Jupiters, particularly equatorial superrotation and increased day-night temperature contrast with increasing equilibrium temperature. We show how spatial temperature variations, particularly between the dayside and nightside and west and east terminators, can vary by hundreds of K, which could imply large variations in Na, K, CO and CH4 abundances in those regions. These chemical variations can be large enough to be observed in transmission with high-resolution spectrographs, such as ESPRESSO on VLT, METIS on the E-ELT, or with MIRI and NIRSpec aboard JWST. We also compare theoretical emission spectra generated from our models to available Spitzer eclipse depths for each planet, and find that the outputs from our solar-metallicity, cloud-free models generally provide a good match to many of the datasets, even without additional model tuning. Although these models are cloud-free, we can use their results to understand the chemistry and dynamics that drive cloud formation in their atmospheres.