Dr Jake Taylor (he/him)

Abstract:

Exoplanet emission spectra are often modelled assuming that the hemisphere observed is well represented by a horizontally homogenized atmosphere. However, this approximation will likely fail for planets with a large temperature contrast in the James Webb Space Telescope (JWST) era, potentially leading to erroneous interpretations of spectra. We first develop an analytic formulation to quantify the signal-to-noise ratio and wavelength coverage necessary to disentangle temperature inhomogeneities from a hemispherically averaged spectrum. We find that for a given signal-to-noise ratio, observations at shorter wavelengths are better at detecting the presence of inhomogeneities. We then determine why the presence of an inhomogeneous thermal structure can lead to spurious molecular detections when assuming a fully homogenized planet in the retrieval process. Finally, we quantify more precisely the potential biases by modelling a suite of hot Jupiter spectra, varying the spatial contributions of a hot and a cold region, as would be observed by the different instruments of JWST/NIRSpec. We then retrieve the abundances and temperature profiles from the synthetic observations. We find that in most cases, assuming a homogeneous thermal structure when retrieving the atmospheric chemistry leads to biased results, and spurious molecular detection. Explicitly modelling the data using two profiles avoids these biases, and is statistically supported provided the wavelength coverage is wide enough, and crucially also spanning shorter wavelengths. For the high contrast used here, a single profile with a dilution factor performs as well as the two-profile case, with only one additional parameter compared to the 1D approach.

Abstract:

The current sparse wavelength range coverage of exoplanet direct imaging observations, and the fact that models are defined using a finite wavelength range, lead both to uncertainties on effective temperature determination. We study these effects using blackbodies and atmospheric models and we detail how to infer this parameter. Through highlighting the key wavelength coverage that allows for a more accurate representation of the effective temperature, our analysis can be used to mitigate or manage extra uncertainties being added in the analysis from the models. We find that the wavelength range coverage will soon no longer be a problem. An effective temperature computed by integrating the spectroscopic observations of the James Webb Space Telescope will give uncertainties similar to, or better than, the current state–of–the–art, which is to fit models to data. Accurately calculating the effective temperature will help to improve current modelling approaches. Obtaining an independent and precise estimation of this crucial parameter will help the benchmarking process to identify the best practice to model exoplanet atmospheres.

Abstract:

Current observational data of exoplanets are providing increasing detail of their 3D atmospheric structures. As characterisation efforts expand in scope, the need to develop consistent 3D radiative-transfer methods becomes more pertinent as the complex atmospheric properties of exoplanets are required to be modelled together consistently. We aim to compare the transmission and emission spectra results of a 3D Monte Carlo Radiative Transfer (MCRT) model to contemporary radiative-transfer suites. We perform several benchmarking tests of a MCRT code, Cloudy Monte Carlo Radiative Transfer (CMCRT), to transmission and emission spectra model output. We add flexibility to the model through the use of k-distribution tables as input opacities. We present a hybrid MCRT and ray tracing methodology for the calculation of transmission spectra with a multiple scattering component. CMCRT compares well to the transmission spectra benchmarks at the 10s of ppm level. Emission spectra benchmarks are consistent to within 10% of the 1D models. We suggest that differences in the benchmark results are likely caused by geometric effects between plane-parallel and spherical models. In a practical application, we post-process a cloudy 3DHD 189733b GCM model and compare to available observational data. Our results suggest the core methodology and algorithms of CMCRT produce consistent results to contemporary radiative transfer suites. 3D MCRT methods are highly suitable for detailed post-processing of cloudy and non-cloudy 1D and 3D exoplanet atmosphere simulations in instances where atmospheric inhomogeneities, significant limb effects/geometry or multiple scattering components are important considerations.

Abstract:

Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. The Atmospheric Remote-sensing Infrared Exoplanet Large-survey (ARIEL) has been selected by the European Space Agency as the next mediumclass science mission, M4, to address these scientific questions. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25-7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10-100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.

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 the WASP-43b phase curve observations of HST/WFC3 and Spitzer/IRAC (Stevenson et al., 2017). 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.