HST HOT-JUPITER TRANSMISSION SPECTRAL SURVEY: CLEAR SKIES FOR COOL SATURN WASP-39b
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HST HOT-JUPITER TRANSMISSION SPECTRAL SURVEY: CLEAR SKIES FOR COOL SATURN WASP-39b

  • Author(s): Fischer, Patrick D
  • Knutson, Heather A
  • Sing, David K
  • Henry, Gregory W
  • Williamson, Michael W
  • Fortney, Jonathan J
  • Burrows, Adam S
  • Kataria, Tiffany
  • Nikolov, Nikolay
  • Showman, Adam P
  • Ballester, Gilda E
  • Desert, Jean-Michel
  • Aigrain, Suzanne
  • Deming, Drake
  • des Etangs, Alain Lecavelier
  • Vidal-Madjar, Alfred
  • et al.

Published Web Location

https://arxiv.org/abs/1601.04761
No data is associated with this publication.
Abstract

We present HST STIS optical transmission spectroscopy of the cool Saturn-mass exoplanet WASP-39b from 0.29-1.025 micron, along with complementary transit observations from Spitzer IRAC at 3.6 and 4.5 micron. The low density and large atmospheric pressure scale height ofWASP-39b make it particularly amenable to atmospheric characterization using this technique. We detect a Rayleigh scattering slope as well as sodium and potassium absorption features; this is the first exoplanet in which both alkali features are clearly detected with the extended wings predicted by cloud-free atmosphere models. The full transmission spectrum is well matched by a clear, H2-dominated atmosphere or one containing a weak contribution from haze, in good agreement with the preliminary reduction of these data presented in Sing et al. (2016). WASP-39b is predicted to have a pressure-temperature profile comparable to that of HD 189733b and WASP-6b, making it one of the coolest transiting gas giants observed in our HST STIS survey. Despite this similarity, WASP-39b appears to be largely cloud-free while the transmission spectra of HD 189733b and WASP-6b both indicate the presence of high altitude clouds or hazes. These observations further emphasize the surprising diversity of cloudy and cloud-free gas giant planets in short-period orbits and the corresponding challenges associated with developing predictive cloud models for these atmospheres.

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