National Centre of Competence in Research PlanetS
Gesellschaftsstrasse 6 | CH-3012 Bern | Switzerland
  Tel. +41 (0)31 631 32 39

Project 4.2: Observational signatures of habitability

To assess the potential habitability of terrestrial exoplanets we will primarily rely on investigat- ing the objects’ atmosphere and surface via photometric or spectroscopic observations (see, Kaltenegger 2017 for a recent review). While prime targets in the immediate solar vicinity have already been detected (e.g., Proxima b, Ross 128 b), in-depth characterisation of these objects is not feasible with current technologies. However, the next generation of ground- and space- based observatories – or upgraded versions of existing facilities – will at least offer a first step in this direction (e.g., Quanz et al. 2015, Snellen et al. 2015, Lovis et al. 2017, Kasper et al. 2013, Kammerer & Quanz 2018, Morley et al. 2017) and the direct involvement of PlanetS members in future ELT instruments (METIS and HiRES) is a key asset. In addition to classical high-contrast thermal infrared imaging and spectroscopy, one of the most promising future techniques for atmospheric characterisation of habitable exoplanets is high-contrast, high-res- olution (HCHR) spectroscopy, which combines an (extreme) AO system with a high-resolution (R ~ 100 000) spectrograph. Thanks to AO, the planet is spatially separated from the star, the contrast is enhanced, and the relative Doppler shift between stellar and planetary light is used to measure the planet spectrum (Snellen et al. 2014, 2015). Exoplanets of all kinds (Jupiters to Earths, cold to warm) orbiting very nearby stars will be amenable to characterisation with the HCHR technique in reflected light.

To cross the observational frontier related to habitability and make a first step towards char- acterising nearby terrestrial planets with upcoming instruments, it is essential that technical developments and modelling efforts go hand in hand. Only then one can quantify what different observational approaches can deliver and which robust science requirements can be formulated. Hence, we propose two work packages linking models of terrestrial planet atmospheres with (future) instruments aiming at the direct detection of habitable exoplanets.

Work-package 1: High-resolution spectra of habitable exoplanets in reflected light

In this work package, we will simulate realistic high-resolution, reflected-light spectra of various kinds of temperate planets and study the detectability of their spectral features from an observational point of view. The parameter space to explore is vast and includes various molecular absorbers in the gas phase, different kinds of clouds and their impact on the planet albedo, and several surface compositions such as liquid water, rocks, and ice caps. Additional phenomena such as ocean glint and Raman scattering may be detectable in the reflected-light spectrum and will be studied as well.

Work-package 2: The information content of terrestrial planet spectra

We will implement a spectral retrieval code for terrestrial planets. While being the standard approach for the characterisation of Hot Jupiters (e.g., Line et al. 2016, Oreshenko et al. 2017), this technique has yet to be applied to terrestrial planets. Spectral retrieval allows us to constrain – in a statistical sense – the individual parameter of an underlying model by ‘letting the data speak’. Such an approach needs to be the basis for combining our knowledge (and ignorance) of individual parameters to arrive at a statistical quantitative conclusion regarding an exoplanet’s habitability. Using the Earth’s atmosphere as a starting point, but then varying (1) the spectral coverage, (2) the spectral resolution, (3) the signal-to-noise, (4) the cloud coverage, (5) the host star type, and (6) the composition, we will assess the impact of these parameters on the final conclusions from our retrieval code (see Figure SD1 for an example spectra of habitable planets). As such this work will deliver a key piece for a statistical framework assessing habitability (see Catling et al. 2017 for a recent proposal) and will also inform us about the knowledge to be gained from future observations with upcoming facilities.

Comments are closed.