The Sonora Substellar Atmosphere Models. VII. Flame Skimmer: Cloudfree Atmospheric and Evolutionary Models for the Coldest Substellar Objects (Spectra, Evolution Models, Photometry Tables & Tools)

Overview

The Sonora Flame Skimmer Models are the successor to the Sonora Bobcat, Sonora Cholla, Sonora Diamondback, Sonora Elf Owl, Sonora Elf Owl v2, and Sonora Red Diamondback models. The Sonora Flame Skimmer model grid includes cloud-free radiative-convective equilibrium models for objects in chemical equilibrium and disequilibrium. The parameters included within this grid are effective temperature (Teff = 50 - 2400 K), gravity (log(g) = 2 - 5.5), vertical eddy diffusion coefficient (log(Kzz) = 2 - 9), atmospheric metallicity ([M/H] = -1.0 - +2.0), and Carbon-to-Oxygen ratio (C/O = 0.229 - 1.14). The atmospheric models have been computed using the open-source radiative-convective equilibrium model PICASO.

File types and how to use them

The spectra and atmospheric models have been presented in the Xarray format so that all the atmospheric properties, including the T(P) profile, atmospheric chemistry, and thermal emission spectra, can be accessed within the same files. For the evolution models and photometry tables, these are presented as plaintext files for ease of access.

Coding Tools

As part of our initiative to make these models (and previous Sonora models) as easily accessible, we have included a script (evolution_lookup_onefile.py) that helps with the interpolation of the evolution models to derive properties of objects based on our models. Please see the Jupyter notebook (Using Flame Skimmer.ipynb) on how to read in one of the spectral files, plot the P-T profile, chemical abundances, spectrum, and then how to use the interpolation functions to access the evolution models in addition to the photometry tables. Any feedback or suggestions for improvement for the evolution interpolation scheme or the notebook is welcome!

Spectra

The files below are zipped in groups of effective temperature and by chemistry. 'eq' files correspond to equilibrium chemistry, and 'deq' files correspond to disequilibrium chemistry models. The emission spectra for each atmospheric model have been computed between 0.5 and 30 microns at R = 30,000. If you require higher resolution spectra, please contact us. The reported flux is in the units of erg/s/cm²/cm. Note that these fluxes need to be multiplied with R²/D²  before comparing them with the typically observed flux of brown dwarfs/exoplanets. R is the radius of the object, and D is the distance here.

Quickstart

Since Sonora Flame Skimmer is such a large grid of models, the files do take up quite a lot of storage. If you are trying to explore the parameter space of Flame Skimmer, we have generated a file that has 'quickstart' in the filename that has a sparse set of models spanning the entire parameter space. The emission spectra for each atmospheric model have been computed between 0.5 and 30 microns at R = 3,000. This is to help you gauge a rough range of parameters before downloading the full set of models. This includes models with the following parameters: 

Teff =  [50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 600, 700, 800, 900, 1000, 1200, 1400, 1600, 1800, 2000, 2200, 2400]
log(g) = [2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5]
[M/H] = [-1.0, -0.5, +0.0, +0.5, +1.0, +1.5, +2.0]
C/O = 0.5, 1.0, 1.5, 2.5
chemistry: eq plus deq log(Kzz) = 2, 4, 7, 8, 9

Evolution & Photometry Tables

Evolution files connect mass, effective temperature, radius, age, gravity, and moment of inertia for these model sets. The evolution tracks themselves have been sorted into plain text files and compressed into the evolution_tables.zip file.

Each set of model spectra is complemented with tables of fluxes and of absolute magnitudes in a number of photometric systems commonly used in brown dwarf and exoplanet research, split into different directories including ground (e.g. MKO, SDSS), space (Spitzer, WISE, Roman), and JWST. These can be downloaded from the photometry_tables.zip file. 

Credits

If you use these models or tools in your research, please cite Mang et al. 2026