2017/10/20 by Jasmina Blecic, Ian Dobbs-Dixon, Thomas Greene · 1 citation
Environmental Science · Physics and Astronomy · #Adaptive optics and wavefront sensing #Atmospheric aerosols and clouds #Atmospheric model #Radiative transfer #Radio Astronomy Observations and Technology #Range (aeronautics) #Space (punctuation) #Temperature measurement #Thermal #Thermal radiation #Wavelength #astro-ph.EP
paper · pdf · doi:10.3847/1538-4357/aa8171
published as The Astrophysical Journal, 848:127 (24pp), 2017 October 20 · 23 pages
openalex publication_date 2017/10/20 · openalex created_date 2017/11/10 · arxiv created 2018/03/18 · arxiv updated 2018/03/20 · openalex updated_date 2026/08/06
Abstract Using the atmospheric structure from a 3D global radiation-hydrodynamic simulation of HD 189733b and the open-source Bayesian Atmospheric Radiative Transfer (BART) code, we investigate the difference between the secondary-eclipse temperature structure produced with a 3D simulation and the best-fit 1D retrieved model. Synthetic data are generated by integrating the 3D models over the Spitzer , the Hubble Space Telescope ( HST ), and the James Web Space Telescope ( JWST ) bandpasses, covering the wavelength range between 1 and 11 μ m where most spectroscopically active species have pronounced features. Using the data from different observing instruments, we present detailed comparisons between the temperature–pressure profiles recovered by BART and those from the 3D simulations. We calculate several averages of the 3D thermal structure and explore which particular thermal profile matches the retrieved temperature structure. We implement two temperature parameterizations that are commonly used in retrieval to investigate different thermal profile shapes. To assess which part of the thermal structure is best constrained by the data, we generate contribution functions for our theoretical model and each of our retrieved models. Our conclusions are strongly affected by the spectral resolution of the instruments included, their wavelength coverage, and the number of data points combined. We also see some limitations in each of the temperature parametrizations, as they are not able to fully match the complex curvatures that are usually produced in hydrodynamic simulations. The results show that our 1D retrieval is recovering a temperature and pressure profile that most closely matches the arithmetic average of the 3D thermal structure. When we use a higher resolution, more data points, and a parametrized temperature profile that allows more flexibility in the middle part of the atmosphere, we find a better match between the retrieved temperature and pressure profile and the arithmetic average. The Spitzer and HST simulated observations sample deep parts of the planetary atmosphere and provide fewer constraints on the temperature and pressure profile, while the JWST observations sample the middle part of the atmosphere, providing a good match with the middle and most complex part of the arithmetic average of the 3D temperature structure.