DEVELOPING ATMOSPHERIC RETRIEVAL METHODS for DIRECT IMAGING SPECTROSCOPY of GAS GIANTS in REFLECTED LIGHT. I. METHANE ABUNDANCES and BASIC CLOUD PROPERTIES

Roxana E. Lupu, Mark S. Marley, Nikole Lewis, Michael Line, Wesley A. Traub, Kevin Zahnle

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Upcoming space-based coronagraphic instruments in the next decade will perform reflected light spectroscopy and photometry of cool directly imaged extrasolar giant planets. We are developing a new atmospheric retrieval methodology to help assess the science return and inform the instrument design for such future missions, and ultimately interpret the resulting observations. Our retrieval technique employs a geometric albedo model coupled with both a Markov chain Monte Carlo Ensemble Sampler (emcee) and a multimodal nested sampling algorithm (MultiNest) to map the posterior distribution. This combination makes the global evidence calculation more robust for any given model and highlights possible discrepancies in the likelihood maps. As a proof of concept, our current atmospheric model contains one or two cloud layers, methane as a major absorber, and a H2-He background gas. This 6-to-9 parameter model is appropriate for Jupiter-like planets and can be easily expanded in the future. In addition to deriving the marginal likelihood distribution and confidence intervals for the model parameters, we perform model selection to determine the significance of methane and cloud detection as a function of expected signal-to-noise ratio in the presence of spectral noise correlations. After internal validation, the method is applied to realistic spectra of Jupiter, Saturn, and HD 99492c, a model observing target. We find that the presence or absence of clouds and methane can be determined with high confidence, while parameter uncertainties are model dependent and correlated. Such general methods will also be applicable to the interpretation of direct imaging spectra of cloudy terrestrial planets.

Original languageEnglish (US)
Article number217
JournalAstronomical Journal
Volume152
Issue number6
DOIs
StatePublished - Dec 1 2016
Externally publishedYes

Fingerprint

BASIC (programming language)
retrieval
methane
planet
Jupiter (planet)
Jupiter
confidence
samplers
terrestrial planets
atmospheric models
Markov chains
Saturn
Markov chain
method
white noise
albedo
signal-to-noise ratio
confidence interval
sampler
photometry

Keywords

  • methods: statistical
  • planets and satellites: atmospheres
  • planets and satellites: composition
  • techniques: spectroscopic

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science

Cite this

DEVELOPING ATMOSPHERIC RETRIEVAL METHODS for DIRECT IMAGING SPECTROSCOPY of GAS GIANTS in REFLECTED LIGHT. I. METHANE ABUNDANCES and BASIC CLOUD PROPERTIES. / Lupu, Roxana E.; Marley, Mark S.; Lewis, Nikole; Line, Michael; Traub, Wesley A.; Zahnle, Kevin.

In: Astronomical Journal, Vol. 152, No. 6, 217, 01.12.2016.

Research output: Contribution to journalArticle

@article{155ff55ac2c34b87b12d6e95d048f826,
title = "DEVELOPING ATMOSPHERIC RETRIEVAL METHODS for DIRECT IMAGING SPECTROSCOPY of GAS GIANTS in REFLECTED LIGHT. I. METHANE ABUNDANCES and BASIC CLOUD PROPERTIES",
abstract = "Upcoming space-based coronagraphic instruments in the next decade will perform reflected light spectroscopy and photometry of cool directly imaged extrasolar giant planets. We are developing a new atmospheric retrieval methodology to help assess the science return and inform the instrument design for such future missions, and ultimately interpret the resulting observations. Our retrieval technique employs a geometric albedo model coupled with both a Markov chain Monte Carlo Ensemble Sampler (emcee) and a multimodal nested sampling algorithm (MultiNest) to map the posterior distribution. This combination makes the global evidence calculation more robust for any given model and highlights possible discrepancies in the likelihood maps. As a proof of concept, our current atmospheric model contains one or two cloud layers, methane as a major absorber, and a H2-He background gas. This 6-to-9 parameter model is appropriate for Jupiter-like planets and can be easily expanded in the future. In addition to deriving the marginal likelihood distribution and confidence intervals for the model parameters, we perform model selection to determine the significance of methane and cloud detection as a function of expected signal-to-noise ratio in the presence of spectral noise correlations. After internal validation, the method is applied to realistic spectra of Jupiter, Saturn, and HD 99492c, a model observing target. We find that the presence or absence of clouds and methane can be determined with high confidence, while parameter uncertainties are model dependent and correlated. Such general methods will also be applicable to the interpretation of direct imaging spectra of cloudy terrestrial planets.",
keywords = "methods: statistical, planets and satellites: atmospheres, planets and satellites: composition, techniques: spectroscopic",
author = "Lupu, {Roxana E.} and Marley, {Mark S.} and Nikole Lewis and Michael Line and Traub, {Wesley A.} and Kevin Zahnle",
year = "2016",
month = "12",
day = "1",
doi = "10.3847/0004-6256/152/6/217",
language = "English (US)",
volume = "152",
journal = "Astronomical Journal",
issn = "0004-6256",
publisher = "IOP Publishing Ltd.",
number = "6",

}

TY - JOUR

T1 - DEVELOPING ATMOSPHERIC RETRIEVAL METHODS for DIRECT IMAGING SPECTROSCOPY of GAS GIANTS in REFLECTED LIGHT. I. METHANE ABUNDANCES and BASIC CLOUD PROPERTIES

AU - Lupu, Roxana E.

AU - Marley, Mark S.

AU - Lewis, Nikole

AU - Line, Michael

AU - Traub, Wesley A.

AU - Zahnle, Kevin

PY - 2016/12/1

Y1 - 2016/12/1

N2 - Upcoming space-based coronagraphic instruments in the next decade will perform reflected light spectroscopy and photometry of cool directly imaged extrasolar giant planets. We are developing a new atmospheric retrieval methodology to help assess the science return and inform the instrument design for such future missions, and ultimately interpret the resulting observations. Our retrieval technique employs a geometric albedo model coupled with both a Markov chain Monte Carlo Ensemble Sampler (emcee) and a multimodal nested sampling algorithm (MultiNest) to map the posterior distribution. This combination makes the global evidence calculation more robust for any given model and highlights possible discrepancies in the likelihood maps. As a proof of concept, our current atmospheric model contains one or two cloud layers, methane as a major absorber, and a H2-He background gas. This 6-to-9 parameter model is appropriate for Jupiter-like planets and can be easily expanded in the future. In addition to deriving the marginal likelihood distribution and confidence intervals for the model parameters, we perform model selection to determine the significance of methane and cloud detection as a function of expected signal-to-noise ratio in the presence of spectral noise correlations. After internal validation, the method is applied to realistic spectra of Jupiter, Saturn, and HD 99492c, a model observing target. We find that the presence or absence of clouds and methane can be determined with high confidence, while parameter uncertainties are model dependent and correlated. Such general methods will also be applicable to the interpretation of direct imaging spectra of cloudy terrestrial planets.

AB - Upcoming space-based coronagraphic instruments in the next decade will perform reflected light spectroscopy and photometry of cool directly imaged extrasolar giant planets. We are developing a new atmospheric retrieval methodology to help assess the science return and inform the instrument design for such future missions, and ultimately interpret the resulting observations. Our retrieval technique employs a geometric albedo model coupled with both a Markov chain Monte Carlo Ensemble Sampler (emcee) and a multimodal nested sampling algorithm (MultiNest) to map the posterior distribution. This combination makes the global evidence calculation more robust for any given model and highlights possible discrepancies in the likelihood maps. As a proof of concept, our current atmospheric model contains one or two cloud layers, methane as a major absorber, and a H2-He background gas. This 6-to-9 parameter model is appropriate for Jupiter-like planets and can be easily expanded in the future. In addition to deriving the marginal likelihood distribution and confidence intervals for the model parameters, we perform model selection to determine the significance of methane and cloud detection as a function of expected signal-to-noise ratio in the presence of spectral noise correlations. After internal validation, the method is applied to realistic spectra of Jupiter, Saturn, and HD 99492c, a model observing target. We find that the presence or absence of clouds and methane can be determined with high confidence, while parameter uncertainties are model dependent and correlated. Such general methods will also be applicable to the interpretation of direct imaging spectra of cloudy terrestrial planets.

KW - methods: statistical

KW - planets and satellites: atmospheres

KW - planets and satellites: composition

KW - techniques: spectroscopic

UR - http://www.scopus.com/inward/record.url?scp=85009088532&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85009088532&partnerID=8YFLogxK

U2 - 10.3847/0004-6256/152/6/217

DO - 10.3847/0004-6256/152/6/217

M3 - Article

AN - SCOPUS:85009088532

VL - 152

JO - Astronomical Journal

JF - Astronomical Journal

SN - 0004-6256

IS - 6

M1 - 217

ER -