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Retrievals of Dayside Emission Spectra: Trends in Chemistry Michael Line, Aaron Wolf, Xi Zhang, Yuk Yung Caltech
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Retrievals of Dayside Emission Spectra: Trends in Chemistry

Feb 23, 2016

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Retrievals of Dayside Emission Spectra: Trends in Chemistry. Michael Line, Aaron Wolf, Xi Zhang, Yuk Yung Caltech. Ions. Photochemistry. Vertically Mixed. CO . CH 4 quenched. CH 4. CO quenched. Thermo. Eq. H 2 O + CH 4 = CO + 3H 2. Synthetic Study. Spitzer Broadband+IRS+NICMOS. - PowerPoint PPT Presentation
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Page 1: Retrievals of Dayside Emission Spectra: Trends in Chemistry

Retrievals of Dayside Emission Spectra: Trends in Chemistry

Michael Line, Aaron Wolf, Xi Zhang,Yuk YungCaltech

Page 2: Retrievals of Dayside Emission Spectra: Trends in Chemistry

Thermo. Eq.

Vertically Mixed

Photochemistry

Ions

CO

CH4

CO quenched

CH4 quenched

Page 3: Retrievals of Dayside Emission Spectra: Trends in Chemistry

fH2O fCH4fCO fH2

3 P 2=Keq

H2O + CH4 = CO + 3H2

Page 4: Retrievals of Dayside Emission Spectra: Trends in Chemistry

Synthetic Study

S/N~3.5Δλ=0.0075 μm

Spitzer Broadband Spitzer Broadband+IRS+NICMOS

FINESSE

Page 5: Retrievals of Dayside Emission Spectra: Trends in Chemistry

MCMC

Optimal Est.

Page 6: Retrievals of Dayside Emission Spectra: Trends in Chemistry

HD189733Moses et al. 2011

WASP12Kopparapu et al. 2012

GJ436Line et al. 2011

Page 7: Retrievals of Dayside Emission Spectra: Trends in Chemistry

GJ436

HD189733

TRES2

HD149026

WASP19 WASP12

HD189733Moses et al. 2011

WASP12Kopparapu et al. 2012

GJ436Line et al. 2011

Page 8: Retrievals of Dayside Emission Spectra: Trends in Chemistry

GJ436

HD189733

TRES2

HD149026

WASP19 WASP12

MCMC

OPT. EST.

Dis-eq. Models

HD189733Moses et al. 2011

WASP12Kopparapu et al. 2012

GJ436Line et al. 2011

Page 9: Retrievals of Dayside Emission Spectra: Trends in Chemistry

Conclusions• Opt est and MCMC agree for “quality” data

• Most planets seem out of equilibrium (to within “1-sigma”)

• Errors large on current gas estimations

• Need dedicated space based spectroscopic instrument

• Can maybe constrain Kzz

Page 10: Retrievals of Dayside Emission Spectra: Trends in Chemistry

Goals

• Look at the ensemble of planetary atmospheres. Indentify trends in composition—equilibrium vs. disequilibrium

• First must robustly determine temperatures and compositions of exoplanet atmosphere

Page 11: Retrievals of Dayside Emission Spectra: Trends in Chemistry

Two Bayesian Retrieval Approaches

P(T,f |Data)∝ P(Data |T,f) × P(T,f)Optimal Estimation

(Lee et al. 2011 , Line et al. 2012)

This Parameter

That

Par

amet

er

χ 2

-Levenberg-Marquardt to find best solution

-Assumes Gaussian posterior

- Fast—not slowed down by additional parameters or more sophisticated forward models

This Parameter

That

Par

amet

er

χ 2

- Randomly explore’s all of parameter space

- Accounts for non-Gaussian posteriors

- Slow—many parameters and more sophisticated forward models unwieldy

Markov Chain Monte Carlo(Madhusudhan et al. 2011 , Benneke & Seager 2012)

Forward Model: [T, fH2O, fCH4, fCO ,fCO2]

Guillot 2010 [γv1, γv2, κIR, α, β]

Page 12: Retrievals of Dayside Emission Spectra: Trends in Chemistry

Synthetic StudySpitzer Broadband Spitzer Broadband+IRS+NICMOS

FINESSE

MCMCOpt. Est.True

Page 13: Retrievals of Dayside Emission Spectra: Trends in Chemistry

Synthetic StudySpitzer Broadband Spitzer Broadband+IRS+NICMOS

FINESSE