Dynamic mineral clouds on HD 189733b

Abstract

Context. Observations of exoplanet atmospheres have revealed the presence of cloud particles in their atmospheres. 3D modelling of cloud formation in atmospheres of extrasolar planets coupled to the atmospheric dynamics has long been a challenge. Aims. We investigate the thermo-hydrodynamic properties of cloud formation processes in the atmospheres of hot Jupiter exoplanets. Methods. We simulate the dynamic atmosphere of HD 189733b with a 3D model that couples 3D radiative-hydrodynamics with a kinetic, microphysical mineral cloud formation module designed for RHD/GCM exoplanet atmosphere simulations. Our simulation includes the feedback effects of cloud advection and settling, gas phase element advection and depletion/replenishment and the radiative effects of cloud opacity. We model the cloud particles as a mix of mineral materials which change in size and composition as they travel through atmospheric thermo-chemical environments. All local cloud properties such as number density, grain size and material composition are time-dependently calculated. Gas phase element depletion as a result of cloud formation is included in the model. In situ effective medium theory and Mie theory is applied to calculate the wavelength dependent opacity of the cloud component. Results. We present a 3D cloud structure of a chemically complex, gaseous atmosphere of the hot Jupiter HD 189733b. Mean cloud particle sizes are typically sub-micron (0.01−0.5 µm) at pressures less than 1 bar with hotter equatorial regions containing the smallest grains. Denser cloud structures occur near terminator regions and deeper (∼1 bar) atmospheric layers. Silicate materials such as MgSiO 3 [s] are found to be abundant at mid-high latitudes, while TiO 2 [s] and SiO 2 [s] dominate the equatorial regions. Elements involved in the cloud formation can be depleted by several orders of magnitude. Conclusions. The interplay between radiative-hydrodynamics and cloud kinetics leads to an inhomogeneous, wavelength dependent opacity cloud structure with properties differing in longitude, latitude and depth. This suggests that transit spectroscopy would sample a variety of cloud particles properties (sizes, composition, densities).

Dynamic mineral clouds on HD 189733b

“…Although in this postprocessing study we use k-distribution tables, the cloud properties derived from the RHD model may be affected by this choice of opacity scheme. We suggest in Lee et al (2016) that the use of the correlated-k approximation would alter the depth of the seed particle regions on the dayside of the RHD model, dependent on whether the dayside atmosphere is cooler or warmer because of this opacity change. This would alter the cloud opacity structure; the effect on the MCRT would most likely be an increased or decreased luminosity escaping from the next-event estimator scheme, depending on whether the main scattering regions were higher or lower in atmospheric optical depth.…”

“…We note that the amount of porosity is not known a priori, however. Our current study depends on the 3D cloud forming HD 189733b RHD model results of Lee et al (2016). We summarise the limitations of that study and the possible effects on the MCRT results presented here.…”

“…In Lee et al (2016;Paper I in this series) we simulated the atmosphere of HD 189733b using a 3D radiative-hydrodynamic (RHD) model coupled with a self-consistent cloud formation module. In the present paper, we post-process our cloud forming RHD results using the MCRT model to compare our simulation to available observational data and make observational predictions for the TESS and CHEOPS photometric bands.…”

Results from a set of three-dimensional numerical experiments of a hot Jupiter atmosphere

“…Three-dimensional (3D) general circulation models (GCMs) have become established tools used both to interpret current observations of exoplanets, and to predict those to be made by future instruments (see Kataria et al 2016;Lee et al 2016, for recent examples). Given the complex, non-linear and interacting physical mechanisms acting within a planetary atmosphere, combined with the incomplete nature of our observational access to exoplanets, GCMs are likely to become increasingly important in this field.…”

“…Therefore, although much progress has been made (and much more can yet be made) using 1D models, 3D models are required to truly unpick the observations, and extract robust physical meaning. E-mail: nathan@astro.ex.ac.uk Several GCMs (or similar models) with varying levels of sophistication have been applied to hot Jupiters (see for example Cooper & Showman 2005;Cho et al 2008;Menou & Rauscher 2009;Rauscher & Menou 2010;Heng et al 2011;Dobbs-Dixon & Agol 2013;Parmentier et al 2013;Showman et al 2015;Helling et al 2016;Kataria et al 2016;Lee et al 2016), including our own adaptation of the Met Office GCM termed the Unified Model (UM) (Mayne et al 2014a,b;Amundsen et al 2014;Helling et al 2016;Amundsen et al 2016Amundsen et al , 2017Boutle et al 2017). However, much of the progress has been driven by application of a single GCM, the SPARC/MITgcm.…”