TST-DREAMS: WASP-17b PICASO Model Grid

3.2. PICASO+Virga Grid of Forward Models (Grant et al. 2023) We computed radiative-convective thermochemical equilibrium (RCTE) atmospheric models for WASP-17b using the well-vetted open-source model PICASO v3.14 (Batalha et al. 2019; Mukherjee et al. 2023), which has heritage from Fortran codes developed to study Solar System giant planets (e.g., Marley & McKay 1999) and brown dwarfs (e.g., Marley & McKay 1999). We computed a grid of cloud-free models as a function of interior temperature of the planet (200 K & 300 K, Thorngren et al. 2019; Sarkis et al. 2021), atmospheric metallicity (9 values between 1–100×Solar), C/O ratio (5 values between 0.25–2×Solar), and the heat redistribution factor (0.5, 0.6, 0.7, 0.8). PICASO’s RCTE module utilizes correlated-k opacities that are detailed in Marley et al. (2021) and released by Lupu et al. (2021). We included the opacity sources for 29 species, but the most important for the JWST MIRI LRS wavelength region is the line list of H2O (Polyansky et al. 2018). The chemical equilibrium abundances are computed on a pressuretemperature-M/H-C/O grid of thermochemical equilibrium models presented in Marley et al. (2021) following the work of Gordon & McBride (1994), Fegley & Lodders (1994), Lodders (1999), Lodders (2002), Lodders & Fegley (2002), Visscher et al. (2006), and Visscher et al. (2010), using elemental abundances from Lodders (2010). From our WASP-17b climate models we computed transmission spectra using opacities resampled to R = 60, 000 (Batalha et al. 2020) from original R ∼ 106 line-by-line calculations detailed in Freedman et al. (2008) and Gharib-Nezhad et al. (2021). We fit the cloud-free grid to both the ExoTiC-MIRI and Eureka! JWST MIRI LRS reductions using the “MLFriends” nested sampling Algorithm (Buchner 2016, 2019) implemented in the open-source Ultranest code (Buchner 2021) and find agreement between the two, regardless of binning scheme. The best-fit model from the cloud-free grid has an internal temperature of 200 K, redistribution factor of 0.8, metallicity of 100×Solar, and super-solar C/O ratio (0.7). Reading xarray files import xarray as xr ds = xr.load_dataset(filename) You can also use PICASO's GridFitter. To see the tutorials that utilize these follow this link to the Retrieval tutorials: https://natashabatalha.github.io/picaso/tutorials.html#fitting-models-to-data