ExoReL : A Bayesian Inverse Retrieval Framework For Exoplanetary Re ected Light Spectra

The high-contrast imaging technique is meant to provide insight into those planets orbiting severalastronomical units from their host star. Space missions such as WFIRST, HabEx, and LUVOIR willmeasure reected light spectra of cold gaseous and rocky planets.To interpret these observations we introduce ExoReL (Exoplanetary Reected Light Retrieval),a novel Bayesian retrieval framework to retrieve cloud properties and atmospheric structures fromexoplanetary reected light spectra. As a unique feature, it assumes a vertically non-uniform volumemixing ratio prole of water and ammonia, and use it to construct cloud densities. In this way, cloudsand molecular mixture ratios are consistent.We apply ExoReL on three test cases: two exoplanets ( And e and 47 Uma b) and Jupiter.We show that we are able to retrieve the concentration of methane in the atmosphere, and estimatethe position of clouds when the S/N of the spectrum is higher than 15, in line with previous works.Moreover, we described the ability of our model of giving a chemical identity to clouds, and wediscussed whether or not we can observe this dierence in the planetary reection spectrum. Finally, wedemonstrate how it could be possible to retrieve molecular concentrations (water and ammonia in thiswork) below the clouds by linking the non-uniform volume mixing ratio prole to the cloud presence.This will help to constrain the concentration of water and ammonia unseen in direct measurements.