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Aptly named, ice giants such as Uranus and Neptune contain significant amounts of water. While this water cannot be present near the cloud tops, it must be abundant in the deep interior. We investigate the likelihood of a liquid water ocean existing in the hydrogen-rich region between the cloud tops and deep interior. Starting from an assumed temperature at a given upper tropospheric pressure (the photosphere), we follow a moist adiabat downward. The mixing ratio of water to hydrogen in the gas phase is small in the photosphere and increases with depth. The mixing ratio in the condensed phase is near unity in the photosphere and decreases with depth; this gives two possible outcomes. If at some pressure level the mixing ratio of water in the gas phase is equal to that in the deep interior, then that level is the cloud base. Alternately, if the mixing ratio of water in the condensed phase reaches that in the deep interior, then the surface of a liquid ocean will occur. We find that Neptune is both too warm (photospheric temperature too high) and too dry (mixing ratio of water in the deep interior too low) for liquid oceans to exist at present. To have a liquid ocean, Neptunes deep interior water to gas ratio would have to be higher than current models allow, and the density at 19 kbar would have to be ~ 0.8 g/cm^3. Such a high density is inconsistent with gravitational data obtained during the Voyager flyby. As Neptune cools, the probability of a liquid ocean increases. Extrasolar hot Neptunes, which presumably migrate inward toward their parent stars, cannot harbor liquid water oceans unless they have lost almost all of the hydrogen and helium from their deep interiors.
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The water content of magma oceans is widely accepted as a key factor that determines whether a terrestrial planet is habitable. Water ocean mass is determined as a result not only of water delivery and loss, but also of water partitioning among several reservoirs. Here we review our current understanding of water partitioning among the atmosphere, magma ocean, and solid mantle of accreting planetary embryos and protoplanets just after giant collisions. Magma oceans are readily formed in planetary embryos and protoplanets in their accretion phase. Significant amounts of water are partitioned into magma oceans, provided the planetary building blocks are water-rich enough. Particularly important but still quite uncertain issues are how much water the planetary building blocks contain initially and how water goes out of the solidifying mantle and is finally degassed to the atmosphere. Constraints from both solar-system explorations and exoplanet observations and also from laboratory experiments are needed to resolve these issues.
We investigate the structural similarities between liquid water and 53 ices, including 20 knowncrystalline phases. We base such similarity comparison on the local environments that consist of atoms within a certain cutoff radius of a central atom. We reveal that liquid water explores the localenvironments of the diverse ice phases, by directly comparing the environments in these phases using general atomic descriptors, and also by demonstrating that a machine-learning potential trained on liquid water alone can predict the densities, the lattice energies, and vibrational properties of theices. The finding that the local environments characterising the different ice phases are found in water sheds light on water phase behaviors, and rationalizes the transferability of water models between different phases.
Future remote sensing of exoplanets will be enhanced by a thorough investigation of our solar system Ice Giants (Neptune-size planets). What can the configuration of the magnetic field tell us (remotely) about the interior, and what implications does that field have for the structure of the magnetosphere; energy input into the atmosphere, and surface geophysics (for example surface weathering of satellites that might harbour sub-surface oceans). How can monitoring of auroral emission help inform future remote observations of emission from exoplanets? Our Solar System provides the only laboratory in which we can perform in-situ experiments to understand exoplanet formation, dynamos, systems and magnetospheres.
Methanol and complex organic molecules have been found in cold starless cores, where a standard warm-up scenario would not work because of the absence of heat sources. A recent chemical model attributed the presence of methanol and large organics to the efficient chemical desorption and a class of neutral-neutral reactions that proceed fast at low temperatures in the gas phase. The model calls for a high abundance of methanol ice at the edge of the CO freeze-out zone in cold cloud cores. We performed medium resolution spectroscopy toward 3 field stars behind the starless core L1544 at 3 $mu$m to constrain the methanol ice abundance and compare it with the model predictions. One of the field stars shows a methanol-ice abundance of 11% with respect to water ice. This is higher than the typical methanol abundance previously found in cold cloud cores (4%), but is 4.5 times smaller than predicted. The reason for the disagreement between the observations and the model calculations is not yet understood.
One significant difference between the atmospheres of stars and exoplanets is the presence of condensed particles (clouds or hazes) in the atmosphere of the latter. The main goal of this paper is to develop a self-consistent microphysical cloud model for 1D atmospheric codes, which can reproduce some observed properties of Earth, such as the average albedo, surface temperature, and global energy budget. The cloud model is designed to be computationally efficient, simple to implement, and applicable for a wide range of atmospheric parameters for planets in the habitable zone. We use a 1D, cloud-free, radiative-convective, and photochemical equilibrium code originally developed by Kasting, Pavlov, Segura, and collaborators as basis for our cloudy atmosphere model. The cloud model is based on models used by the meteorology community for Earths clouds. The free parameters of the model are the relative humidity and number density of condensation nuclei, and the precipitation efficiency. In a 1D model, the cloud coverage cannot be self-consistently determined, thus we treat it as a free parameter. We apply this model to Earth (aerosol number density 100 cm^-3, relative humidity 77 %, liquid cloud fraction 40 %, and ice cloud fraction 25 %) and find that a precipitation efficiency of 0.8 is needed to reproduce the albedo, average surface temperature and global energy budget of Earth. We perform simulations to determine how the albedo and the climate of a planet is influenced by the free parameters of the cloud model. We find that the planetary climate is most sensitive to changes in the liquid water cloud fraction and precipitation efficiency. The advantage of our cloud model is that the cloud height and the droplet sizes are self-consistently calculated, both of which influence the climate and albedo of exoplanets.
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