Planetary atmosphere observation analysis

Abstract:

We present a novel retrieval technique that attempts to model phase curve observations of exoplanets more realistically and reliably, which we call the 2.5-dimension (2.5-D) approach. In our 2.5-D approach we retrieve the vertical temperature profile and mean gaseous abundance of a planet at all longitudes and latitudes \textbf{simultaneously}, assuming that the temperature or composition, $x$, at a particular longitude and latitude $(\Lambda,\Phi)$ is given by $x(\Lambda,\Phi) = \bar{x} + (x(\Lambda,0) - \bar{x})\cos^n\Phi$, where $\bar{x}$ is the mean of the morning and evening terminator values of $x(\Lambda,0)$, and $n$ is an assumed coefficient. We compare our new 2.5-D scheme with the more traditional 1-D approach, which assumes the same temperature profile and gaseous abundances at all points on the visible disc of a planet for each individual phase observation, using a set of synthetic phase curves generated from a GCM-based simulation. We find that our 2.5-D model fits these data more realistically than the 1-D approach, confining the hotter regions of the planet more closely to the dayside. We then apply both models to WASP-43b phase curve observations of HST/WFC3 and Spitzer/IRAC. We find that the dayside of WASP-43b is apparently much hotter than the nightside and show that this could be explained by the presence of a thick cloud on the nightside with a cloud top at pressure $< 0.2$ bar. We further show that while the mole fraction of water vapour is reasonably well constrained to $(1-10)\times10^{-4}$, the abundance of CO is very difficult to constrain with these data since it is degenerate with temperature and prone to possible systematic radiometric differences between the HST/WFC3 and Spitzer/IRAC observations. Hence, it is difficult to reliably constrain C/O.

Abstract:

This document is the EnVision Venus orbiter proposal, submitted in October 2016 in response to ESA's M5 call for Medium-size missions for its Science Programme, for launch in 2029. Why are the terrestrial planets so different? Venus should be the most Earth-like of all our planetary neighbours: its size, bulk composition and distance from the Sun are very similar to those of Earth. Its original atmosphere was probably similar to that of early Earth, with abundant water that would have been liquid under the young sun's fainter output. Even today, with its global cloud cover, the surface of Venus receives less solar energy than does Earth, so why did a moderate climate ensue here but a catastrophic runaway greenhouse on Venus? How and why did it all go wrong for Venus? What lessons can be learned about the life story of terrestrial planets in general, in this era of discovery of Earth-like exoplanets? Were the radically different evolutionary paths of Earth and Venus driven solely by distance from the Sun, or do internal dynamics, geological activity, volcanic outgassing and weathering also play an important part? Following the primarily atmospheric focus of Venus Express, we propose a new Venus orbiter named EnVision, to focus on Venus' geology and geochemical cycles, seeking evidence for present and past activity. The payload comprises a state-of-the-art S-band radar which will be able to return imagery at spatial resolutions of 1 - 30 m, and capable of measuring cm-scale deformation; this is complemented by subsurface radar, IR and UV spectrometers to map volcanic gases, and by geodetic investigations.

Abstract:

Observational studies of exoplanets are suggestive of an ubiquitous presence of clouds. The current modelling techniques used in emission to account for the clouds tend to require prior knowledge of the cloud condensing species and often do not consider the scattering effects of the cloud. We explore the effects that thermal scattering has on the emission spectra by modelling a suite of hot Jupiter atmospheres with varying cloud single-scattering albedos (SSAs) and temperature profiles. We examine cases ranging from simple isothermal conditions to more complex structures and physically driven cloud modelling. We show that scattering from nightside clouds would lead to brightness temperatures that are cooler than the real atmospheric temperature, if scattering is unaccounted for. We show that scattering can produce spectral signatures in the emission spectrum even for isothermal atmospheres. We identify the retrieval degeneracies and biases that arise in the context of simulated JWST spectra when the scattering from the clouds dominates the spectral shape. Finally, we propose a novel method of fitting the SSA spectrum of the cloud in emission retrievals, using a technique that does not require any prior knowledge of the cloud chemical or physical properties.