The MSG model for cloudy sub-stellar atmospheres

Context . State-of-the-art JWST observations are unveiling unprecedented views into the atmospheres of sub-stellar objects in the infrared, further highlighting the importance of clouds. Current forward models struggle to fit the silicate clouds absorption feature at ∼10 µm observed in sub-stellar atmospheres. Aims . In the MSG model, we aim to couple the MARCS 1D radiative-convective equilibrium atmosphere model with the 1D kinetic, stationary, non-equilibrium cloud formation model DRIFT , also known as StaticWeather , to create a new grid of self-consistent cloudy sub-stellar atmosphere models with microphysical cloud formation. We aim to test if this new grid is able to reproduce the silicate cloud absorption feature at ∼10 µm. Methods . We modelled sub-stellar atmospheres with effective temperatures in the range T eff = 1200–2500 K and with log( ɡ ) = 4.0. We computed atmospheric structures that self-consistently account for condensate cloud opacities based on microphysical properties. We present an algorithm based on control theory to help converge such self-consistent models. Synthetic atmosphere spectra were computed for each model to explore the observable impact of the cloud microphysics. We additionally explored the impact of choosing different nucleation species (TiO 2 or SiO) and the effect of less efficient atmospheric mixing on these spectra. Results . The new MSG cloudy grid using TiO 2 nucleation shows spectra that are redder in the near-infrared compared to the currently known population of sub-stellar atmospheres. We find that the models with SiO nucleation and models with reduced mixing efficiency are less red in the near-infrared. Conclusions . We present a new grid of MSG models for cloudy sub-stellar atmospheres that include cloud radiative feedback from microphysical clouds. The grid is unable to reproduce silicate features similar to the ones found in recent JWST observations and Spitzer archival data. We thoroughly discuss further work that may better approximate the impact of convection in cloud-forming regions and steps that may help resolve the silicate cloud feature.