How do habitable worlds and environments form and evolve?
Team members are exploring the possible outcomes of planet internal structure and oxidation states from N-body calculations, using thermal evolution models to include volatile cycles for C, N, and S. These simulations determine where planets can form, track the delivery and evolution of volatile content, and estimate bulk compositions of terrestrial planets. We are also computing outgassing fluxes of H2, H2O, CO, CO2, CH4, N2, NH3 that determine the atmospheres of simulated planets, and estimating magnetic field strengths as a function of planet age and rotation rate.
What is the diversity of biosignatures that we might expect for habitable exoplanets?
For this task, we are using 3D climate system models to explore the habitable conditions over a large parameter space of atmospheric properties. Our methods use a novel approach for sparse sampling and subsequent analysis of multi-variable parameter spaces, based on a Quasi-Monte Carlo (QMC) approach with iterative optimization.
How can we better understand the range of parameters that influence habitability?
Task members are studying how the radiation emitted from M-dwarf stars affects the chemistry and stability of exoplanetary atmospheres and the presence of biosignatures. We are computing semi-empirical non-LTE stellar spectra, guiding these models with existing UV measurements. These spectra are used as input for multiple planet models, including a 3-D coupled climate-chemistry model, to calculate upper and lower limits for atmospheric loss and to determine the evolutionary path of volatiles.
How can we best observe and characterize potentially-habitable exoplanets?
For this task, we are determining how current and future telescopes can best search for biosignatures in the atmospheres of a large number of planets orbiting nearby M dwarfs. This task utilizes a novel observational technique called Planetary Infrared Excess (PIE), where one can use stellar models to infer planetary infrared excess when measured simultaneously in the near-to-mid IR. We aim to enable and validate atmospheric characterization with the PIE technique by utilizing our team’s JWST Cycle 1 GO and GTO time-series data.