Optimal estimation retrievals of the atmospheric structure and composition of HD 189733b from secondary eclipse spectroscopy

By Jae-Min Lee, L. Fletcher, P. Irwin. 2011

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Recent spectroscopic observations of transiting hot Jupit ers have permitted the derivation of the thermal structure and molecular abundances of H2O, CO2, CO, and CH4 in these extreme atmospheres. Here, for the first time, we apply the tech nique of optimal estimation to determine the thermal structure and composition of an exoplanet by solving the inverse problem. The development of a suite of radiative transfer and retrieval tools for exoplanet atmospheres is described, building upon a retrieval algori thm which is extensively used in the study of our own solar system. First, we discuss the plausibility of detection of different molecules in the dayside atmosphere of HD 189733b and the best-fitting spectrum retrieved from all publicly available sets of secondary eclipse obser vations between 1.45 and 24 µm. Additionally, we use contribution functions to assess the vertical sensitivity of the emission spectrum to temperatures and molecular composition. Over the altitudes probed by the contribution functions, the retrieved thermal structure show s an isothermal upper atmosphere overlying a deeper adiabatic layer (temperature decreasing with altitude), which is consistent with previously-reported dynamical and observational results. The formal uncertainties on retrieved parameters are estimated conservatively using an analysis of the cross-correlation functions and the degeneracy between different atmospheric properties. The formal solution of the inverse problem suggests that the uncertainties on retr ieved parameters are larger than suggested in previous studies, and that the presence of CO and CH4 is only marginally supported by the available data. Nevertheless, by including as broad a wavelength range as possible in the retrieval, we demonstrate that available spectra of HD 189733b can constrain a family of potential solutions for the atmospheric structure.

Subfields: Astronomy and Astrophysics, Instrumentation, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/12ecda01e36c15be3efcb0226bc59df583f5d5e9

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In Astronomy and Astrophysics

  1. N. Madhusudhan
  2. Jon Fortney
  3. A. Showman
  4. M. Line
  5. V. Parmentier
  6. D. Sing
  7. J. D'esert
  8. M. Marley

In Instrumentation

  1. N. Madhusudhan
  2. Jon Fortney
  3. M. Line
  4. A. Showman
  5. V. Parmentier
  6. D. Sing
  7. J. D'esert
  8. H. Knutson

In Statistical and Nonlinear Physics

  1. N. Madhusudhan
  2. M. Line
  3. Jon Fortney
  4. V. Parmentier
  5. H. Knutson
  6. M. Marley
  7. A. Showman
  8. Laura Kreidberg

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