Presentation #102.342 in the session Poster Session.
One of the key goals of exoplanetary science is to measure exoplanet compositions, which can reveal their formation mechanisms and evolution. Retrieving atmospheric properties from spectra is the only method through which properties of substellar atmospheres can be determined since in situ measurements are impossible at astronomical distances. However, our ability to characterize these atmospheres is complicated by the degeneracies produced between the thermal structure, chemical abundances, and the presence of clouds in many substellar atmospheres. Incorporating the complex physics that governs cloudy brown dwarf and planetary atmospheres into retrieval frameworks necessitates making assumptions, many of which are not yet robustly verified for accuracy. We test two key assumptions using state-of-the-art cloud-free models (the Sonora model grid) to create mock data sets. First, brown dwarf and exoplanet retrievals typically assume that the abundance of each species is uniform throughout the atmosphere, but this assumption does not match physical models of hot atmospheres, which have molecular abundances that differ by many orders of magnitude between the deep hot atmosphere and cool upper atmosphere. We test to see if an additional level of complexity in the abundances is warranted for each species across a range of brown dwarf and exoplanet temperatures. Second, many brown dwarf retrievals have allowed the temperature profile to vary freely, which can provide unphysical (i.e. unstable) resulting profiles, especially for cloudy objects. We test two physically-motivated parameterizations for the temperature profile. We use the CHIMERA retrieval framework to test these assumptions over a wide temperature range of cloud-free Sonora spectra for which ground truth values are known. These tests reveal under what conditions these assumptions break down and which assumptions are valid in the hot temperature regime.