Microphysics of KCl and ZnS Clouds on GJ 1214 b

Abstract

Clouds in the atmospheres of exoplanets confound characterization efforts by reducing, eliminating, and distorting spectral signatures of molecular abundances. As such, interpretations of exoplanet spectra strongly depend on the choice of cloud model, many of which are highly simplified and lack predictive power. In this work, we use a cloud model that treat microphysical processes to simulate potassium chloride (KCl) and zinc sulfide (ZnS) clouds in the atmosphere of the super Earth GJ 1214 b and how they vary as a function of the strength of vertical mixing and the atmospheric metallicity. Microphysical processes control the size and spatial distribution of cloud particles, allowing for the computation of more physical cloud distributions than simpler models. We find that the mass and opacity of KCl clouds increase with mixing strength and metallicity, with the particle size and spatial distribution defined by nucleation, condensation, evaporation, and transport timescales. ZnS clouds cannot form without the presence of condensation nuclei, while heterogeneous nucleation of ZnS on KCl reduces particle sizes compared to pure KCl cases. In order to explain the flat transmission spectrum of GJ 1214b with homogeneously nucleated KCl clouds, the atmospheric metallicity must be at least 1000 × solar, and the eddy diffusivity must be at least 10 10 cm 2 s −1 . We predict that JWST observations of GJ 1214 b may reveal the presence of methane, carbon monoxide, and water, allowing for constraints to be placed on atmospheric metallicity and C/O ratio.

Clouds of Fluffy Aggregates: How They Form in Exoplanetary Atmospheres and Influence Transmission Spectra

“…Before showing the synthetic spectra, we investigate the cloud-top pressure, defined as the pressure level at which the cloud becomes optically thick along the line of sight of an observer (i.e., τ s = 1). The cloud-top pressure clarifies the ob-servable region of atmospheres and was examined by previous studies (Ohno & Okuzumi 2018;Powell et al 2018;Gao & Benneke 2018;Helling et al 2019). Figure 5 shows the cloud-top pressure of fluffy-aggregate clouds as a function of wavelength for different monomer sizes and the atmospheric metallicities.…”

“…The monomer size is presumably controlled by the formation of condensation nuclei, namely the nucleation, and subsequent condensation growth that keeps a spherical shape (Lavvas et al 2011). If one adopts the classical nucleation theory, the homogeneous nucleation followed by condensation yields KCl particles with the effective size of ∼10 µm (Gao & Benneke 2018). This is substantially larger than the required monomer size.…”

“…We have adopted this assumption since our cloud microphysical model assumes the narrowly peaked size distribution, for which the equal-sized collision is a dominant growth process. However, the cloud particles could have different shape of size distributions (Powell et al 2018;Gao & Benneke 2018), and the monomer-aggregate collision might be dominant. In that case, CPAs grow into more spherical shapes (e.g., D f ≈ 3), and the cloud vertical extent would be small as compared to the case of D f = 2.…”

“…In this study, we have assumed that saturated vapor is instantaneously incorporated into the condensation nuclei at the cloud base. This assumption would be reasonable since the condensation timescale is much shorter than the vertical mixing timescale near at the cloud base (Ohno & Okuzumi 2018;Powell et al 2018;Gao & Benneke 2018). Additional condensation could transform the CPAs to sphere-like particles if the surface growth rate via condensation dominates over the coagulation rate (Lavvas et al 2011).…”

“…They found that the cloud particles grow too large to ascend to a height of 0.01 mbar, needed to explain the transmission spectrum of GJ1214 b. Gao & Benneke (2018) also attempted to reproduce the cloud structure of GJ1214 b using a microphysical model that fully solves the evolution of size distribution. However, they concluded the high-altitude cloud of GJ1214 b can only be explained when the eddy diffusion coefficient in the atmospheres is assumed to be at least an order of magnitude higher than predicted from the general circulation model (GCM) with passive tracers (Charnay et al 2015a).…”