Abstract
ABSTRACT We present results of 3D hydrodynamical simulations of HD209458b including a coupled, radiatively active cloud model (eddysed). We investigate the role of the mixing by replacing the default convective treatment used in previous works with a more physically relevant mixing treatment (Kzz) based on global circulation. We find that uncertainty in the efficiency of sedimentation through the sedimentation factor fsed plays a larger role in shaping cloud thickness and its radiative feedback on the local gas temperatures – e.g. hotspot shift and day-to-night side temperature gradient – than the switch in mixing treatment. We demonstrate using our new mixing treatments that simulations with cloud scales that are a fraction of the pressure scale height improve agreement with the observed transmission spectra, the emission spectra, and the Spitzer 4.5 µm phase curve, although our models are still unable to reproduce the optical and ultraviolet transmission spectra. We also find that the inclusion of cloud increases the transit asymmetry in the optical between the east and west limbs, although the difference remains small ($\lesssim 1{{\ \rm per\ cent}}$).
Highlights
Clouds and hazes have been found to be common across the range of currently discovered exoplanets
We begin with a direct comparison of our P13 simulations with the hot deep interior model (HDI) GC85 simulations performed in Lines et al (2019)
In this work we have investigated the impact of a more physically accurate mixing treatment on the E S cloud model when applied to hot Jupiters
Summary
Clouds and hazes have been found to be common across the range of currently discovered exoplanets. The simulations of Lines et al (2018b) result in the presence of large quantities of small particles at high altitude, which require extremely long timescales to settle under gravity These models have, shown that the radiative feedback of the clouds themselves plays a significant role in shaping the thermal structure of the atmosphere and must be included We continue the work of Lines et al (2019) in building a more complex cloud model with a limited increase in computational overhead, substituting the default mixing treatment for a more physically relevant model based on mixing found via 3D simulations (Parmentier et al 2013) as well as further investigating the relative impact of the sedimentation efficiency on atmospheric structure and observational diagnostics.
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