Oral presentations and abstracts
Session assets
The sodium doublet is one of the most powerful probes of exoplanet atmospheric properties when observed in transmission spectroscopy during transits. Recent high-spectral resolution observations of the sodium doublet in hot gas giants allowed us to resolve the line shape, opening the way for extracting atmospheric properties using line-profile fitting.
Using the MERC code (Seidel et al. 2020a), a retrieval tool to determine temperature-pressure profiles and high-altitude winds in exoplanet thermospheres, we have studied the curiously broadened sodium signatures of various hot Jupiters. We have updated the MERC code to a quasi 3D treatment of the atmosphere (Seidel et al. 2020c, in prep.) and analysed three hot Jupiters, spanning a wide range of this class of exoplanets (see figure). Using the sodium signature of three examples - WASP-76b (a highly irradiated ultra-hot Jupiter, Seidel et al. 2019), KELT-11b (a puffy hot Jupiter, Mounzer et al. 2020, in prep.), and lastly HD189733b (one of the most studied hot Jupiters to date, Wyttenbach et al. 2015) - we explore possible trends in the atmospheric structure of hot Jupiters.
We will first introduce the new quasi 3D retrieval of MERC, and proceed to show that high-velocity winds in the thermosphere are one possible explanation of the broadened sodium features seen in hot Jupiters. We plan to highlight various caveats and present likely origin scenarios for the observed wind patterns. We will then put these results in the context of past studies using global circulation models (GCMs) on hot Jupiters.
How to cite: Seidel, J., Ehrenreich, D., Bourrier, V., Pino, L., Wyttenbach, A., Allart, R., Lavie, B., Mounzer, D., and Lovis, C.: Wind of Change: Atmospheric wind retrieval and its implications for hot Jupiters, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-273, https://doi.org/10.5194/epsc2020-273, 2020.
Motivation
The transmission spectra of many hot Jupiters show signatures of high-altitude aerosols [e.g., 1,2]. One hypothesized formation mechanism for these aerosols is that photochemical processes generate hazes on the dayside. All previous studies of photochemical hazes on tidally locked giant planets used one-dimensional models [e.g., 3,4]. However, one-dimensional models have to make strongly simplifying assumptions about the strength of vertical mixing. Furthermore, they ignore that the strong day-night contrast on hot Jupiters and atmospheric circulation can lead to inhomogeneous aerosol distributions. For condensate clouds, it has been shown that inhomogeneous aerosol distributions are to be expected [5-7] and can lead to biases in the interpretation of observations [e.g., 8]. The same is likely to be true for photochemical hazes. Further, it has been suggested differences between the morning and evening terminator in ingress and egress transmission spectra could provide a diagnostic for distinguishing between condensate clouds and photochemical hazes [9]. Three-dimensional general circulation models (GCMs) are needed to study how atmospheric circulation shapes the distribution of photochemical hazes to guide future observations and models.
Methods
We present simulations of hot Jupiter HD 189733b using the MITgcm [10]. We use passive tracers representing photochemical hazes to study how hazes are transported by atmospheric circulation. Haze particles in our model have a constant size and are spherical.
Results
The results show that the haze mass mixing ratio varies horizontally by at least an order of magnitude for all particle sizes considered and over the entire simulated pressure range. Depending on the particle size, the resulting 3D haze distribution falls into one of two regimes: small (<30 nm) and large (>30 nm) particles.
For small particles (< 30 nm), the timescale for gravitational settling is longer than the timescale for horizontal and vertical advection. The 3D distribution is thus controlled by advection and looks similar for all particle sizes in this regime. At low pressures, small particle hazes accumulate on the night side in two large midlatitude vortices centered east of the antistellar point (Fig. 1). Because the night side vortices span across the morning terminator, there are higher mass mixing ratios at the morning terminator compared to the evening terminator.
For large particles (>30 nm), the 3D haze distribution is strongly influenced by settling. At very low pressures, where the settling timescale is much shorter than the advection timescale, the horizontal pattern closely mirrors the haze production function. At somewhat higher pressures, where both timescales are within an order of magnitude from each other, hazes are concentrated on the dayside and the hemisphere east of the substellar point (Fig. 2). This results in higher mass mixing ratios at the evening terminator compared to the morning terminator. Because the distribution of hazes is dependent on where in the atmosphere these timescales become equal, the 3D size distributions look much less similar between different particle sizes within this regime compared to the small particle regime.
At pressures > 1 mbar, the advection time scale is shorter than the settling time scale for all particle sizes considered in our simulations. In this region, the equatorial jet dominates the atmospheric circulation and hazes of all sizes develop a more banded pattern (Fig. 3). Differences between morning and evening terminator become smaller in this pressure range.
Our model does not include particle growth and thus does not make predictions about the particle size distribution. To estimate whether terminator differences could be observable, we tried using a constant particle size as well as a size distribution from a 1D microphysics model [3]. In either case, one obtains a relatively small difference in transit depth between leading and trailing limb (Fig. 4). We note that the simulated spectral slope at short wavelengths is too flat to match the observational data. There could be multiple factors explaining why our model does not reproduce the slope of the data, including that a fully coupled three-dimensional microphysics and circulation model might be needed to reproduce the observational data. Furthermore, part of the slope could arise from unaccounted star spots. Another possibility is that mixing from small-scale turbulence not resolved by the GCM could be much more important than expected. In that case, the haze mass mixing ratio would decline more rapidly with increasing pressure, resulting in a steeper spectral slope.
References:
[1] Pont, F., Sing, D. K., Gibson, N. P., et al.: The prevalence of dust on the exoplanet HD 189733b from Hubble and Spitzer observations, Monthly Notices of the Royal Astronomical Society, 432, 4, 2917-2944, 2013.
[2] Sing, D. K., Fortney, J. J., Nikolov, N., et al.: A continuum from clear to cloudy hot-Jupiter exoplanets without primordial water depletion, Nature, 529, 7584, 59-62, 2016.
[3] Lavvas, P. and Koskinen, T.: Aerosol Properties of the Atmospheres of Extrasolar Giant Planets, The Astrophysical Journal, 847, 1, 32, 2017.
[4] Ohno, K. and Kawashima, Y.: Super-Rayleigh Slopes in Transmission Spectra of Exoplanets Generated by Photochemical Haze, The Astrophysical Journal Letters, 895, 2, L47, 2020.
[5] Parmentier, V., Showman, A. P. and Lian, Y.: 3D mixing in hot Jupiters atmospheres I . Application to the day / night cold trap in HD 209458b, Astronomy & Astrophysics, 558, A91, 2013.
[6] Lee, G., Dobbs-Dixon, I., Helling, Ch., et al.: Dynamic mineral clouds on HD 189733b. I. 3D RHD with kinetic, non-equilibrium cloud formation, Astronomy & Astrophysics, 594, A48, 2016.
[7] Lines, S., Mayne, N. J., Boutle, I. A., et al.: Simulating the cloudy atmospheres of HD 209458 b and HD 189733 b with the 3D Met Office Unified Model, Astronomy & Astrophysics, 615, A97, 2018.
[8] Line, M. and Parmentier, V.: The Influence of Nonuniform Cloud Cover on Transit Transmission Spectra, The Astrophysical Journal, 820, 1, 78, 2016.
[9] Kempton E. M. R., Bean J. L., Parmentier V.: An Observational Diagnostic for Distinguishing between Clouds and Haze in Hot Exoplanet Atmospheres, The Astrophysical Journal, 845, 2, L20, 2017.
[10] Adcroft A., Campin J.-M., Hill C., Marshall J.: Implementation of an Atmosphere Ocean General Circulation Model on the Expanded Spherical Cube, Monthly WeatherReview, 132, 2845, 2004.
How to cite: Steinrueck, M., Showman, A., Lavvas, P., Koskinen, T., Zhang, X., and Tan, X.: Three-dimensional Simulations of Photochemical Hazes in the Atmosphere of Hot Jupiter HD 189733b, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-768, https://doi.org/10.5194/epsc2020-768, 2020.
Thanks to the advances in modern instrumentation we learned about many exoplanets that spawn a wide range of masses and composition. Studying their atmospheres provides insight into planetary diversity, origin, evolution, dynamics, and habitability. Present and future observing facilities will address these important topics in very detail by using more precise observations, high-resolution spectroscopy, improved analysis methods, etc. In this contribution we focus on the analysis of temperature and disequilibrium chemical processes in hot Jupiter atmospheres. In particular, we investigate the impact of photochemistry and vertical transport processes on mixing ratio profiles and on the simulated spectra of a hot Jupiters that orbits stars of various spectral types. We additionally address the impact of stellar activity that should be present in all stars with convective envelopes. Finally, we estimate the characterization of these processes using space and ground-based observations that will be carried out with near-future instruments and missions.
How to cite: Shulyak, D., Rengel, M., Lara, L., and Nemec, N.: Studying physics and chemistry in atmospheres of hot Jupiters from future ground-based and space facilities, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-236, https://doi.org/10.5194/epsc2020-236, 2020.
Abstract
Direct-imaging observations of exoplanets in reflected starlight are expected to be available this decade. This will improve our knowledge about cold and temperate exoplanets and their atmospheres. Current theoretical efforts related to such planets aim to understand the effects that planet and atmospheric properties have on the spectra to be measured. This will help predict the science outcome of direct-imaging missions and identify the key needs for models used in the interpretarion of future measurements. In this work, we have investigated the information contained in reflected-light exoplanetary spectra and the role played by the planet radius in the atmospheric characterization.
Introduction
Long-period exoplanets are a population that remains substantially unexplored because of the biases introduced by the technology currently available. These planets have small transit probabilities due to their large orbital distances and hence the direct-imaging technique will be key to analyse their atmospheres. Space missions such as NGRST (formerly WFIRST), LUVOIR or HabEx will allow us to study this population of long-period exoplanets, providing a more complete picture of exoplanet diversity.
Model
We set up an atmospheric model with hydrogen and helium as the main components. We include methane, in a volume-mixing-ratio fCH4, as the only absorbing gaseous species. We add a cloud layer, described by its optical thickness (τc), its geometrical extension and the position of the cloud top. The aerosols are modelled by their single-scattering albedo and their effective radius, which determines the scattering phase function through Mie theory. This model is motivated by previous modelling of the atmospheres of Solar System gas giants. Apart from the six atmospheric parameters, we include the planet radius (Rp) as another model parameter. We apply our analysis to a particular target, Barnard's Star b candidate super-Earth[1], although our conclusions are generally planet-independent.
Retrieval
We built a grid of ~300,000 synthetic reflected-light spectra for a range of possible atmospheric configurations. The spectra were computed at phase angle α=0º (that is, with the exoplanet fully illuminated). The wavelength interval under study is 500-900 nm and the spectral resolution, R~125-225. The multiple-scattering radiative-transfer problem was solved with a previously validated code[2].
Observations were simulated by adding wavelength-independent noise at S/N=10. Three atmospheric configurations were considered to simulate observations and carry out retrievals: a cloud-free one (τc=0.05), one with a thin-cloud (τc=1.0) and one with a thick-cloud (τc=20.0). We developed an MCMC-based retrieval package achieving a continuous sampling of the parameter space by interpolating within the pre-computed grid of spectra.
The retrievals were carried out for cases where the planet radius was either known (and hence there were only 6 free parameters) or completely unconstrained (7 free parameters). We also analysed intermediate scenarios in which estimates of Rp with different uncertainties were assumed.
Results
The retrievals of atmospheric properties degrade as the uncertainties in the value of Rp increase. Indeed, the correlations between model parameters triggered by adding Rp as a free parameter make it challenging to distinguish between cloudy- and cloud-free atmospheres. Fig. 1 shows that, even if the atmosphere contains a thick-cloud, the evidence for the cloud disappears as the uncertainties in Rp grow. When the planet radius is a priori unconstrained, the retrieval of τc shows a nearly-flat posterior probability distribution. This indicates that the evidence is equal for both thick clouds or cloud-free atmospheres. On the other hand, if Rp is known we can generally distinguish between cloudy or cloud-free atmospheres in all of the scenarios analysed in this work. The retrieval results for other parameters such as the methane abundance also improve if the planet radius is known.
Fig. 1 also shows that a priori estimates on the value of Rp improve the retrievals. This result encourages the development of synergies between direct-imaging and other techniques in order to reduce the uncertainties in the mass and radius of long-period exoplanets.
Besides, we find that, if Rp is completely unconstrained, direct-imaging observations can constrain its value to within a factor of ~2 for all the cases explored. This might help start addressing the bulk composition of an exoplanet.
Several works have addressed the possible science return of future direct-imaging observations[3]-[5]. Since the exoplanets observed in direct-imaging will generally lack a measurement of Rp, we conclude that this parameter will play an important role in the retrievals and therefore should be included in this type of retrieval exercises.
References
[1] Ribas et al. (2018), Nature, 563, 365
[2] García Muñoz & Mills (2015), A&A, 573, A72
[3] Lupu et al. (2016), AJ, 152, 217
[4] Nayak et al. (2017), PASP, 129, 973
[5] Damiano & Hu (2019), AJ, 159, 175
How to cite: Carrión-González, Ó., García Muñoz, A., Cabrera, J., Csizmadia, S., Santos, N. C., and Rauer, H.: Directly imaged exoplanets in reflected starlight. The importance of knowing the planet radius, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-674, https://doi.org/10.5194/epsc2020-674, 2020.
A substantial fraction of transiting exoplanets have some form of aerosol present in their atmospheres. Transit spectroscopy, especially of hot Jupiters, has provided evidence for this, in the form of steep downward slopes from blue to red in the optical part of the spectrum, and muted gas absorption features throughout. Studies analysing the atmospheres of these planets must therefore consider the presence of aerosol.
However, clouds and hazes are complex, and the transit spectra that are currently available allow us to constrain only limited properties of cloud and haze. Retrieval models – fast, parametric radiative transfer models coupled with an inversion algorithm – are typically used to analyse transit spectra, but these rely on minimising the number of variables to ensure rapid convergence. Optimising aerosol parameters to maximise constraints on cloud structure, whilst avoiding overfitting, is therefore a necessary step.
In this presentation, I investigate a range of aerosol parameterisations from the literature (Figure 1), and examine their effects on retrievals from transmission spectra of hot Jupiters HD 189733b (Figure 2) and HD 209458b. Regardless of the parameterisation used, results qualitatively agree for the cloud/haze itself, and using multiple approaches provides a more holistic picture. The retrieved H2O abundance is also robust to assumptions about aerosols. Additionally, strong evidence emerges that aerosol on HD 209458b covers less than half of the terminator region, but the situation for HD 189733b is less clear (Barstow 2020).
References:
Barstow J. K., Aigrain S., Irwin P. G. J., Sing D. K., 2017, ApJ, 834, 50
Barstow J. K., 2020, arxiv:2002.02945
Fisher C., Heng K., 2018, MNRAS, 481, 4698
Pinhas A., Madhusudhan N., Gandhi S., MacDonald R., 2019, MNRAS, 482, 1485
Sing D. K., et al., 2016, Nature, 529, 59
Tsiaras A., et al., 2018, AJ, 155, 156
How to cite: Barstow, J.: Unveiling cloudy exoplanets: the influence of cloud model choices on retrieval solutions, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-132, https://doi.org/10.5194/epsc2020-132, 2020.
The planetary multi-dimensional nature poses many challenges to their atmospheric modeling. However, as targets and data quality improve with the TESS and CHEOPS missions and soon to be launched JWST, PLATO and ARIEL missions, so too must our modeling approach if we would like to assess a truly 3D picture of planetary atmospheres. We present a physically-consistent GCM-motivated multi-dimensional temperature model, that utilizes the dominant dynamical property of short-period tidally-locked planets, the planetary jet, and accounts, for the first time, for the advection of energy around the planet. In our approach, we utilize a tractable set of parameters efficient enough to enable Bayesian analysis and return physical insights not yet retrieved for exoplanets. By fundamentally linking the planetary longitudes and retrieving spectra at all orbital phases simultaneously, we recover three essential properties of the planetary jet (phase offset, amplitude, and pressure where the jet is located) together with the self-consistent temperature structure.
Figure 1: Two examples of our parameterized advective temperature component at the equator.
How to cite: Blecic, J.: Physically-Consistent Multi-Dimensional Temperature Structure for Retrieval, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-890, https://doi.org/10.5194/epsc2020-890, 2020.
Abstract
TauREx 3.1 is the next version of the open-source python retrieval framework TauREx 3[1], which is backward-compatible with the previous version but offers a swathe of improvements and optimizations to the overall architecture. This version upgrade includes support for k-tables, non-uniform priors, and H- opacities. The most major inclusion in this version of TauREx is the plugin system, which allows any developer to imbue TauREx 3 with new features without touching the main codebase. Plugins are installable additions that TauREx 3 will detect and automatically include in its Bayesian retrieval pipeline. They can be installed from PyPI through pip install or directly from a git repository. They can consist of collections of new chemistries, temperature profiles, contribution functions, stellar and planetary models, non-uniform prior functions, opacity formats, and forward models, to name a few. Anyone can host and develop them, and they are designed so that all are interoperable with each other. Presented are the CUDA and OpenCL plugins, which provide GPU accelerated forward models. Fastchem[2], GGchem[3], and disequilibrium[4] chemical plugins and petitRADTRANS[5] and phase curve forward model plugins. Presented are Forward models and retrievals that exploit the plugins
Introduction
Exoplanetary atmospheres are multi-faceted physical phenomena that touch many scientific fields. Chemical modeling, cloud physics, fluid dynamics, orbital mechanics and molecular spectroscopy are some of the physical processes that need to be appropriately handled in a retrieval framework to characterize these complex environments correctly. With the upcoming JWST and Ariel telescope expected to bring a higher density of information, it is vital that the many codes and contributions of a wide variety of fields can be exploited for characterization.
Plugins
TauREx 3 allowed for the inclusion of custom codes in the pipeline. TauREx 3.1 provides a means for which a developer can develop and distribute their custom codes through plugins. Plugins exploit the python packaging system to allow developers to make their codes installable and easily used in retrievals without modification of the main TauREx 3 codebase. The installation is an essential aspect as this allows many FORTRAN and C++ codes to be automatically compiled or binaries distributed. TauREx will then automatically detect these plugins and integrate them into its retrieval pipeline. Plugins can provide replacements for all components in the TauREx 3 framework. For example, if a user wishes to use the GGchem chemistry code in atmospheric retrievals, they can simply write pip install taurex_ggchem, which will automatically download a precompiled GGchem library and its data files and install it alongside a new TauREx chemistry component. A user can then immediately include GGchem for both forward models and retrievals in input files or python scripts. A single plugin can consist of any number of new replacement atmospheric components and can make use of FORTRAN, C++, and python codes/libraries.
TauREx-CUDA/OpenCL
TauREx-CUDA and TauREx-OpenCL are plugins that, when installed, provide replacement forward models that take advantage of heterogeneous computing. These replacement forward models allow the optical depth calculation to execute on hardware accelerators such as Nvidia, AMD, and Intel GPUs to be easily exploited for a 25--50x speed up in both forward models and retrievals.
TauREx-GGchem/Fastchem/ACE/Disequilibrium
The four plugins TauREx-ACE, TauREx-Fastchem, and TauREx-GGchem, are installable components that provide the ACE[6], Fastchem[2] and GGchem[3] equilibrium codes for use in both forward modeling and retrievals. These can be easily installed and used in Windows, Mac, and Linux through PyPi and provide their full capabilities for both forward modeling (Figure 1) and retrievals (Figure 2). Also included is a new plugin for a photochemical kinetic solver[4] that provides disequilibrium chemistry with retrieval capabilities (Figure 3).
Figure 1. Plots of simulated JWST transmission spectra from different chemistry schemes.
Figure 2. Posteriors of ACE (blue), Fastchem (red), GGchem (green) and GGchem with condensation (orange)
Figure 3. Active molecular profiles using a photochemical kinetic solver[4] with retrieval sampling uncertainties.
Forward Model plugins
Plugins can include entirely new forward models. The TauREx-petitRADTRANS plugin that utilizes petitRADTRANS[5] code to compute the transmission and emission spectra. It demonstrates the interoperable nature of plugins. Running petitRADTRANS under the TauREx 3.1 framework gives it the ability to use all available chemistries, including ACE, Fastchem, GGchem, and disequilibrium codes, as well as retrievals utilizing nested sampling with non-uniform priors. The TauREx-phase plugin implements a phase curve forward model for retrievals and can exploit all plugins, including the equilibrium chemistry and CUDA, for self-consistent accelerated optimizations.
Summary
The plugin system in TauREx 3.1 aims to simplify the inclusion of new atmospheric parameters and external codes. TauREx 3.1 is available at http://github.com/ucl-exoplanets/TauREx3_public or through PyPi. Each plugin is also available through both in the ucl-exoplanets GitHub page and PyPi.
References
[1] Ahmed F. Al-Refaie, Quentin Changeat, Ingo P. Waldmann, and Giovanna Tinetti. Taurex III: A fast, dynamic and extendable framework for retrievals, 2019.
[2] Joachim W Stock, Daniel Kitzmann, A Beate C Patzer, and Erwin Sedlmayr. FastChem: A computer program for efficient complex chemical equilibrium calculations in the neutral/ionized gas phase with applications to stellar and planetary atmospheres .Monthly Notices of the Royal Astronomical Society,479(1):865–874, 06 2018.
[3] Woitke, P., Helling, Ch., Hunter, G. H., Millard, J. D., Turner, G. E.,Worters, M., Blecic, J., and Stock, J. W. Equilibrium chemistry down to 100 k - impact of silicates and phyllosilicates on the carbon to oxygen ratio..A&A, 614:A1, 2018.
[4] Venot, O., Hebrard, E., Agundez, M., Dobrijevic, M., Selsis, F., Hersant,F., Iro, N., and Bounaceur, R. A chemical model for the atmosphere of hot jupiters. A&A, 546:A43, 2012.
[5] Molliere, P., Wardenier, J. P., van Boekel, R., Henning, Th., Molaverdikhani, K., and Snellen, I. A. G. petitRADTRANS - a python radiative transfer package for exoplanet characterization and retrieval.A&A, 627:A67, 2019.
[6] M. Agundez, O. Venot, N. Iro, F. Selsis, F. Hersant, E. Hebrard, and M. Do-brijevic. The impact of atmospheric circulation on the chemistry of the hotJupiter HD 209458b.A&A, 548:A73, Dec 2012.
How to cite: Al-Refaie, A., Changeat, Q., Venot, O., Waldmann, I., and Tinetti, G.: TauREx 3.1 - Extending atmospheric retrieval with plugins., Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-669, https://doi.org/10.5194/epsc2020-669, 2020.
The aeronomy hydrodynamic simulation Salz et al. (2016) has shown that the warm Neptune GJ 3470b should have one of the largest mass loss rates due to its low mass, close orbit and relatively high activity of the host star. The Lyα observation of GJ 3470b reported in Bourrier et al. (2018) revealed large absorption depths of ~35 % in the blue wing [-94; -41] km/s of the line. Different to similar warm Neptune GJ 436b, significant absorption depth of ~23 % was detected also in the red wing [23; 76] km/s, as well as a relatively short transit duration of ~2 hours without any distinct early ingress and extended egress phases.
Thus, GJ 3470b appears to be the second hot exoplanet with a large hydrogen envelope extending far beyond the Roche lobe. Moreover, besides of the hydrogen related Lyα, also the absorption in line 10830 Å of metastable helium has been detected for this planet. Ninan et al. (2019) reported about 1% absorption averaged over the line width of 1.2 Å taking place mostly at the blue wing [-36; 9] km/s of the line. The simulation, based on 1D profiles of helium atoms and ions performed in Salz et al. (2016) assuming standard abundance He/H=0.1, yielded the column density of He(23S) atoms one order of magnitude larger than that inferred from the observations. Very recently new three transits at the 10830 Å line have been reported by Palle et al. (2020). The spectro-photometric light curve has been obtained, which shows that absorption by He(23S) atoms coincides with the expected ingress and egress times. The spectrally resolved absorption at transit shows the depth of 1.5% around the line center restricted by the interval [-30; 20] km/s, while the half width interval is [-22; 10] km/s.
In the present paper we use a 3D global hydrodynamic multifluid code which allows fully self-consistent calculation of the formation of the escaping planetary wind (PW) of hot exoplanets and its interaction with the stellar wind (SW). Previously we employed this code to interpret the Lyα absorption at GJ 436b Khodachenko et al. (2019) and the absorption in HI, OI, CII, SiIII resonant lines at hot Jupiter HD209458b Shaikhislamov et al. (2020). For the GJ 3470b, we calculate the absorption in both, Lyα and He 10830 Å lines. A number of simulation runs with different modelling parameter sets has been performed, assuming slow and fast SW conditions and using the estimated XUV and Lya fluxes of the star.
The obtained results show that, similar to findings in Khodachenko et al. (2019) regarding GJ436b, the Lyα transit for GJ3470b is produced by ENAs formed in course of the interaction between the escaping PW and surrounding SW. As in the case of our previous studies of HD20458b and GJ436b, the role of the radiation pressure has been found to be insignificant. The simulation runs with different modelling parameter sets revealed that the observed fast decay of the Lyα absorption in the egress part of the transit light-curve can be the result of sufficiently high ram pressure of fast SW, which rapidly blows away from the orbital line the trailing tail of escaping planetary atmospheric material. The applied model is able to reproduce, within the measurements error margins, the 10% Lyα absorption at the red-shifted velocities of about 80 km/s, as well as 20% absorption, averaged over the whole red wing of the line. The red-shifted Lyα absorption is produced in the shocked region by ENAs, which have sufficiently high velocity dispersion to provide absorption in the blue and red parts of the line. The best fit parameters of the SW correspond in the temperature and velocity to the fast Solar wind and imply for the parent star of GJ3470b the total mass loss rate of 0.1 of the Solar value, which is compatible with the smaller than the Sun size of the star.
Similarly to 1D modeling of Ninan et al. (2019) and Palle et al. (2020), we found that He(23S) atoms produced by GJ3470b outflow extend to the distances of at least 10 planet radii. To fit the He(23S) absorption at the same parameters, as those derived to fit the Lyα absorption, the helium abundance in the upper atmosphere of GJ3470b should be He/H≈0.015, i.e. about an order of magnitude lower than the Solar value. At the same time, a good agreement of the simulated absorption profile with the measurements was found.
The comparative study of various pumping and depopulation processes of He(23S) state has shown that the interpretation of the measured absorption in 10830 Å line can be quite intricate, because in different regions of the escaping planetary material, as well as in the shocked region, different processes are responsible for the production of absorbing agent. Altogether, the performed 3D self-consistent multi-fluid simulations of the expanding and escaping upper atmosphere of GJ3470b and the related spectral absorption features and transit light-curves have shown that the available observational data can be relatively well interpreted within the range of reasonable values of physically justifiable parameters related with the planetary atmospheric composition, stellar XUV flux and SW plasma flow.
Acknowledgements:
This work was supported by grant № 18-12-00080 of the Russian Science Foundation. Parallel computing simulations, key for this study, have been performed at Computation Center of Novosibirsk State University and SB RAS Siberian Supercomputer Center.
References
Bourrier V. et al. (2018). A&A, 620, A147
Khodachenko M. L. et al. (2019). ApJ, 885(1), 67
Ninan J. P. et al. (2019). preprint arXiv:1910.02070
Palle E. et al. (2020). A&A, 638, A61
Salz M. et al. (2016). A&A, 586, A75
Shaikhislamov I. F. et al (2020). MNRAS, 491(3), 3435
How to cite: Shaikhislamov, I. F. and Khodachenko, M. L.: Global 3D hydrodynamic modeling of GJ3470b and transit absorption in Lyα and He 10830 A lines, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-147, https://doi.org/10.5194/epsc2020-147, 2020.
The TRAPPIST-1 system is one of the most prominent targets for characterizing the atmospheres of terrestrial planets in the near future. We model potential atmospheres of planet e, which lies well in the habitable zone of the star and could hold liquid water. However, during the extended pre-main sequence phase of TRAPPIST-1, the planets may have experienced extreme water loss, leading to a desiccated mantle.
We simulate dry and wet atmospheres of TRAPPIST-1 e using a newly developed photochemical model for planetary atmospheres, coupled to a radiative-convective model then calculate theoretical spectra to determine how distinguishable these scenarios could be.
The resulting atmospheric composition is used to compute cloud-free transmission spectra. From this we calculate the detectability of molecular features using the Extremely Large Telescope (ELT) and the James Webb Space Telescope (JWST).
1. Introduction
The nearby terrestrial planet TRAPPIST-1 e, orbiting the cool host star TRAPPIST-1, offers the opportunity for studying its atmosphere with next generation telescopes.
The stellar luminosity evolution of such cools stars is quite different to that of e.g. the Sun.
In particular the active pre-main sequence phase of the star can be extended and the stellar Ultra Violet (UV) radiation is high for about a billion years [1].
This could lead to a runaway greenhouse state on an ocean-bearing terrestrial planet and a loss of substantial amounts of planetary water vapour before the star enters the main sequence phase [2]. This study aims to determine whether it is feasible to distinguish between wet and dry surface conditions of TRAPPIST-1 e from atmospheric observations using low resolution spectroscopy with the JWST and high resolution cross-correlation spectroscopy with the ELT.
2. Methods
We use the 1D climate-photochemistry model 1D-TERRA [3, 4] in order to simulate the climate and photochemical response from wet and dry surface conditions. The TRAPPIST-1 input spectrum is taken from [5].
For wet conditions we assume a relative humidity of 80% and calculate dry as well as wet deposition for all species considered in the model. We consider in total three scenarios. The first two scenarios assume a liquid ocean at the surface. Scenario 1 is a dead case with only volcanic fluxes. Scenario 2 is an alive case with volcanic and Earth-like biogenic fluxes. Scenarios 3 is without a surface ocean using a relative humidity of 1%, no wet deposition and weaker dry deposition for CO and O2 compared to the wet scenarios 1 and 2. For all scenarios we then simulate N2 atmospheres with different amounts of CO2 ranging from 0.001 bar to 1 bar.
The simulated atmospheric composition and temperature profiles are used to predict potential transmission spectra of TRAPPIST-1~e. These spectra are then used to estimate the number of transits required to detect molecular features with JWST NIRSpec and ELT HIRES.
3. Results
For dry CO2-rich atmospheres a significant amount of O2 and O3 is produced abiotically [6, 7], due to the
low FUV/NUV ratio of TRAPPIST-1 [8]. However, the abundances of abiotic O2 and O3 are one order of magnitude lower than in those
runs with biogenic emissions. A detection of O2 or O3 will be challenging with JWST NIRSpec or ELT HIRES (see Fig. 1).
Figure 1: Number of transits required to reach a S/N of 5 for CO2 at 4.3 µm, O3 at 9.6 µm, CO at 2.35 µm and H2O at 1.4 µm with JWST NIRSpec (upper and middle panel) and CH4 from 2.1 to 2.5 µm and O2 from 1.24 to 1.3 µm with ELT HIRES (lower panel) in the atmosphere of TRAPPIST-1 e. Full filled bars: required number of transits is below or equal 30. Semi transparent bars: required number of transits is larger than 30. Figure from [4].
CO can be an indirect marker of an ocean, having concentrations enhanced by ~100 times on an ocean-less world with a CO2-rich atmosphere (see also [9, 10, 11]).
The detection of CO in the K-band might be feasible with JWST NIRSpec and ELT HIRES for dry surface conditions and CO2 partial pressure above 0.01 bar by co-adding several tens of transits.
Significant amounts of CH4 are only present in the simulated atmospheres with Earth-like biogenic flux. It has been shown that for planets around cool host stars, weaker destruction of CH4 leads to stronger spectral features of CH4 compared to the Earth around the Sun [12].
About 30 transit observation in the K-band are needed to detect CH4 with ELT HIRES for the wet & alive case.
In conclusion, the three scenarios considered for TRAPPIST-1 e might be distinguishable by combining ~30 transit observations with JWST NIRSpec and ELT HIRES in the K-band. The alive scenario, assuming Earth-like biogenic emissions, could be identified by the detection of CH4. The non-detection of CO would suggest the existence of a surface ocean. In turn, the detection of CO would suggest dry surface conditions (see more details in [4]).
References
[1] Baraffe, I., Homeier, D., Allard, F., & Chabrier, G. 2015, A&A, 577, A42.
[2] Luger, R., & Barnes, R. 2015, AsBio, 15, 119.
[3] Scheucher, M., Wunderlich, F., Grenfell, J. L., et al. accepted, ApJ.
[4] Wunderlich, F., Scheucher, M., Godolt, M., et al. accepted, ApJ.
[5] Wilson, D. J., Froning, C. S., Duvvuri, G. M., et al. submitted, ApJ.
[6] Selsis, F., Despois, D., & Parisot, J.-P. 2002, A&A, 388, 985.
[7] Harman, C. E., Schwieterman, E. W., Schottelkotte, J. C., & Kasting, J. F. 2015, ApJ, 812, 137.
[8] Tian, F., France, K., Linsky, J. L., Mauas, P. J., & Vieytes, M. C. 2014, EPSL, 385, 22.
[9] Gao, P., Hu, R., Robinson, T. D., Li, C., & Yung, Y. L. 2015, ApJ, 806, 249.
[10] Schwieterman, E. W., Reinhard, C. T., Olson, S. L., et al. 2019, ApJ, 874, 9.
[11] Hu, R., Peterson, L., & Wolf, E. T. 2020, ApJ, 888, 122.
[12] Wunderlich, F., Godolt, M., Grenfell, J. L., et al. 2019, A&A, 624, A49.
How to cite: Wunderlich, F., Scheucher, M., Godolt, M., Grenfell, J. L., Schreier, F., Schneider, P. C., Wilson, D. J., Sánchez López, A., López Puertas, M., and Rauer, H.: Characterization of the atmosphere of TRAPPIST-1 e with JWST and ELT, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-692, https://doi.org/10.5194/epsc2020-692, 2020.
Introduction
Lava planets orbit close enough to their star that parts of their surface are molten. Temperatures on the dayside are often hot enough to vaporise rocks, which create a thin mineral vapour atmosphere. Lava planets are currently one of the best targets to observe rocky worlds outside the solar system.
We simulate the steady-state vapour-pressure driven flow of the recently discovered exoplanet K2-141b via a 1D hydrodynamical model. This model produces the atmospheric pressure, temperature, and wind velocity as well as evaporation and condensation rates. We then infer the magma ocean circulation required for mass balance and simulate how our results would affect photometric and spectroscopic observation.
Methods
The hydrodynamical model that we used was first developed by Ingersoll et al. (1985) to model the thin atmosphere of Io. The model was subsequently adapted by Castan and Menou (2011) to model lava planets such as Kepler 10-b and 55 Cnc-e. Although greatly idealized, these calculations are robust to the supersonic winds and atmospheric collapse that result from the extreme day-to-night temperature contrast.
Before introducing the system of equations that makes up the 1D model, it is important to list the assumptions and limitations of our idealized case. First, we assume a hydrostatically bound atmosphere that is thin enough to not absorb any radiation. Second, we assume a turbulent and well-mixed atmosphere, which leads to a vertically constant wind profile. Third, we assume only a single constituent which allows us to ignore chemical processes that greatly complicates our problem. Another idealization is the neglect of the planet’s rotation, which allows for symmetry about the subsolar/antisolar axis making the problem 1D.
The system of equations below describes the conservation of mass (1), momentum (2), and energy (3) which are solved for state variable pressure, P, temperature, T, and wind velocity, V; P and T are evaluated at the top of the turbulent boundary layer. The angular distance from the subsolar point, θ is the only independent variable.
In equation (1)-(3), the important flux variables are E, the surface mass flux, τ , the surface drag, and Q, the surface energy flux. Detailed derivation along with calculations of the surface fluxes can be found in Ingersoll et al. (1985).
Results
We simulate the atmosphere of K2-141b for atmospheric constituent SiO2 (due to abundance) or Na (due to volatility). The solution strongly depends on the saturated vapour pressure relation with temperature which is provided by Schaefer and Fegley (2009). Figures (1) and (2) below show the state variables solution for SiO2 and Na atmospheres, respectively.
Figure 1: solution to SiO2 atmosphere. Top panel: atmospheric boundary-layer pressure (left) and scale height (right). Middle panel: wind velocity (left) and Mach number (right). Bottom panel: atmospheric and surface temperature.
Figure 2: solution to Na atmosphere. The format is exactly the same as Fig. (1).
Since Na is much more volatile than SiO2, the Na atmosphere is much thicker, as expected. The Na atmosphere also extends further than SiO2 atmosphere. However, the SiO2 atmosphere retains heat better which makes it much warmer than its Na counterpart.
If we presume a pure SiO2 atmosphere, then we can infer the magma ocean circulation that balances out the mass transport by the atmosphere. The inferred ocean circulation depends on the ocean depth and the horizontal mass transport. The magma ocean depth can be approximated by first assuming a vertically constant temperature profile for the surface and determine the pressure at which liquid SiO2 change phase. The horizontal mass flux transported by the atmosphere can be approximated by integrating the precipitation rate. The figure below shows the magma ocean properties for the SiO2 case.
Figure 3. Left: velocity of magma ocean return flow. Negative values denote mass flow towards the subsolar point. Right: ocean depth.
We do the same analysis for the Na case where the ocean is set to have the same Na to SiO2 ratio as the Bulk Silicate Earth composition. This yields an ocean velocity that is 104 times the speed of the SiO2 case. This suggests that maintaining mass balance for SiO2 is much easier than for Na.
We do the same analysis for the Na case where the ocean is set to have the same Na to SiO2 ratio as the Bulk Silicate Earth composition. This yields an ocean velocity that is 104 times the speed of the SiO2 case. This suggests that the slow return flow may prohibit a steady-state Na atmosphere.
To simulate observations of K2-141b’s atmosphere, we calculate the radiative flux emitted at a given wavelength corresponding to spectral features of SiO2 and Na. We then integrate the flux of the visible hemisphere of K2-141b to obtain its orbital phase curve.
Figure 4. Top panel: predicted phase curve of K2-141b for a Na atmosphere (black lines) or for a SiO2 atmosphere (purple lines). The chosen wavelengths are near spectral features of SiO2 at 3.4 m and of Na at 589 nm. Bottom: Disk-integrated planetary brightness temperature for the two scenarios.
Discussion
Idealized 1D models provide important insights for future observations of K2-141b and likewise of many other lava planets. Our results show that the atmosphere will fully condense before reaching the nightside for both cases. We also show that a steady-state Na atmosphere is difficult to achieve given the slow return flow through a SiO2 ocean. Finally, the thinner and hotter SiO2 atmosphere may be easier to observe due to its greater terminator at the limb of the planet as seen during transit.
Acknowledgement
We would like to thank R. Pierrehumbert for his guidance. This work was made possible by the Natural Science and Engineering Research Council (NSERC) of Canada’s Collaborative Research and Training Experience (CREATE) Program for Technology for Exo-planetary Sciences (TEPS).
References
Castan and Menou, 2011, APJ, 743, L36
Ingersoll, Summers, and Schlipf, 1985, Icarus, 64, 375
Schaefer and Fegley, 2009, APJ, 703, L113
How to cite: Nguyen, T. G., Cowan, N., Banerjee, A., and Moores, J.: Modelling the atmosphere of lava planet K2-141b: implications for photometry and spectroscopy, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-500, https://doi.org/10.5194/epsc2020-500, 2020.
We investigate possible driving mechanisms of volcanic activity on large rocky super-Earths with masses exceeding four Earth masses. Due to high pressures in the mantles of these planets, melting in deep mantle layers can be suppressed, even if the energy release due to tidal heating and radioactive decay is substantial in these areas of the mantles. We investigate if a newly identified heating mechanism, namely induction heating by the star’s magnetic field, can drive volcanic activity on these planets due to its unusual heating pattern close to the planet’s surface, which leads to heat production in the very upper part of the mantle. In this region the pressure is not yet high enough to preclude the melt formation. We use a model for induction heating we developed and apply it to the super-Earth HD 3167b, which has a mass of approximately seven Earth masses. We calculate induction heating in the planet’s interiors assuming an electrical conductivity profile of a hot rocky planet and a moderate stellar magnetic field typical of an old inactive star, which one can expect for HD 3167. Then, we use a mantle convection code (CHIC) to simulate the evolution of volcanic outgassing with time.
Fig. 1. Total outgassing of CO2 , CO, H2O, and H2 from HD 3167b assuming the magnetic field of the star of 0, 1, and 5 G. Induction heating leads to a much earlier onset of volcanism on the planet and increases the outgassing by several tens of bar. The mantle viscosity is 10 times the mantle viscosity of the Earth.
According to our results, in most cases volcanic outgassing on HD 3167b is not very significant in the absence of induction heating, however, including this heating mechanism changes the picture and leads to a substantial increase in the outgassing from the planet’s mantle. Evolution of volcanic outgassing is illustrated in Fig. 1. Induction heating also leads to a much earlier onset of volcanic activity on this planet. This result shows that induction heating combined with a high surface temperature is capable of driving volcanism on massive super-Earths, which has very important observational implications.
How to cite: Kislyakova, K. and Noack, L.: Interior heating by stellar magnetic fields as a driver of volcanic activity on massive rocky planets, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-852, https://doi.org/10.5194/epsc2020-852, 2020.
