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arxiv: 2605.14997 · v1 · submitted 2026-05-14 · 🌌 astro-ph.EP

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A Climate-Constrained Bayesian Inverse Method for JWST Rocky Exoplanet Eclipse Spectra: A Case Study of LTT 1445A b

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Pith reviewed 2026-05-15 03:17 UTC · model grok-4.3

classification 🌌 astro-ph.EP
keywords eclipseatmospheresbayesianclimate-constraineddatalesssimmirimodel
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The pith

A climate-constrained Bayesian method shows LTT 1445A b requires no atmosphere to fit existing JWST data, with 2σ upper limits of ≲1 bar for O₂/N₂/CO, ≲0.1 bar for CO₂, ≲10^{-3} bar for H₂O, and ≲10^{-4} bar for SO₂.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The study develops a new way to analyze data from the James Webb Space Telescope about small rocky planets around cool stars. Instead of using flexible but unphysical temperature profiles in their models, the authors calculate temperature structures from first principles using radiative and convective heat transport in equilibrium. They apply this to the planet LTT 1445A b, which is about 1.34 times Earth's size and has an equilibrium temperature around 431 K. The existing MIRI low-resolution spectrum is well fit by a model of a bare rock without any atmosphere. If an atmosphere is present, the data limit the amount of various gases at the surface to very low levels: less than about 1 bar for gases like oxygen or nitrogen, 0.1 bar for carbon dioxide, and much less for water vapor or sulfur dioxide. The method also predicts that future observations with better precision could detect some of the allowed thicker atmospheres. By incorporating uncertainties in the planet's properties, the star, and the models themselves, the Bayesian approach gives probabilistic constraints. This aims to provide more reliable inferences by reducing the number of free parameters compared to traditional retrieval methods.

Core claim

An atmosphere does not need to be invoked to explain the data, meaning a bare rock model produces an adequate fit. If the planet has an atmosphere, the 2σ upper limits on surface partial pressures are ≲ 1 bar for an optically thin gas like O₂, N₂ or CO, ≲0.1 bar for CO₂, ≲ 10^{-3} bar for H₂O, and ≲ 10^{-4} bar for SO₂. Scheduled MIRI F1500W observations could detect one of the thicker atmospheres permitted by the existing data (1 bar O₂ and 0.01 bar CO₂), if a precision of 20 ppm or better is achieved.

Load-bearing premise

The assumption that self-consistent radiative-convective equilibrium pressure-temperature profiles accurately represent the planet without additional free parameters for temperature structure, and that the bare rock surface model correctly captures emission without unaccounted surface albedo or emissivity uncertainties.

read the original abstract

Determining whether temperate rocky exoplanets orbiting M stars retain atmospheres is currently a central goal of exoplanet astronomy. To this end, the James Webb Space Telescope has begun searching for atmospheres on these worlds with MIRI secondary eclipse spectroscopy and photometry. Here, we develop a novel climate-constrained Bayesian inference framework that yields atmospheric pressure and composition constraints from these datasets, while accounting for planetary, stellar, and model uncertainties. Our approach fits observations with model spectra derived from self-consistent pressure-temperature profiles at radiative-convective equilibrium, thus maximizing the information extracted from the data and providing more robust inferences than retrievals that use parameterized pressure-temperature profiles. We demonstrate the framework on the existing MIRI LRS eclipse spectrum of LTT 1445A b (1.34 $R_\oplus$ and $T_{\mathrm{eq}} \approx 431$ K). An atmosphere does not need to be invoked to explain the data, meaning a bare rock model produces an adequate fit. If the planet has an atmosphere, the $2\sigma$ upper limits on surface partial pressures are $\lesssim 1$ bar for an optically thin gas like O$_2$, N$_2$ or CO, $\lesssim0.1$ bar for CO$_2$, $\lesssim 10^{-3}$ bar for H$_2$O, and $\lesssim 10^{-4}$ bar for SO$_2$. Scheduled MIRI F1500W observations could detect one of the thicker atmospheres permitted by the existing data (1 bar O$_2$ and 0.01 bar CO$_2$), if a precision of 20 ppm or better is achieved. This case study demonstrates that climate-constrained Bayesian inversion can turn rocky-planet eclipse spectra into the quantitative constraints necessary to test population-level atmospheric retention hypothesis, like the cosmic shoreline.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 1 minor

Summary. The paper introduces a climate-constrained Bayesian inverse method for interpreting JWST MIRI eclipse spectra of rocky exoplanets, employing self-consistent radiative-convective equilibrium pressure-temperature profiles. For the case study of LTT 1445A b, it concludes that a bare-rock model provides an adequate fit to the existing MIRI LRS data without requiring an atmosphere, derives 2σ upper limits on atmospheric surface partial pressures for several gases (e.g., ≲1 bar for O₂, N₂, CO; ≲0.1 bar for CO₂), and assesses the potential for detection with upcoming MIRI F1500W observations.

Significance. If the central results hold after addressing surface boundary conditions, the framework provides a more robust alternative to parameterized retrievals by integrating self-consistent climate models, yielding quantitative atmospheric constraints that can test population-level hypotheses such as the cosmic shoreline. The approach maximizes information from eclipse spectra while propagating planetary, stellar, and model uncertainties.

major comments (1)
  1. [Model description and bare-rock case] Bare-rock surface model: the surface emissivity (implicitly near unity) and albedo are fixed without free parameters or marginalization. Real rocky surfaces exhibit emissivities 0.6–0.95 and wavelength-dependent albedos that scale the outgoing longwave flux; because the Bayesian framework does not vary these quantities, both the reported goodness-of-fit for the no-atmosphere case and the derived 2σ pressure upper limits are conditional on an untested boundary condition. This directly affects the central claim that an atmosphere is not required.
minor comments (1)
  1. The abstract states the upper limits but does not specify the exact number of data points, wavelength coverage, or reduced chi-squared value for the bare-rock fit, which would help readers assess the adequacy of the fit immediately.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their constructive and detailed review of our manuscript. We have addressed the major comment regarding the bare-rock surface model by performing additional sensitivity analyses and clarifying the assumptions in the revised version.

read point-by-point responses
  1. Referee: [Model description and bare-rock case] Bare-rock surface model: the surface emissivity (implicitly near unity) and albedo are fixed without free parameters or marginalization. Real rocky surfaces exhibit emissivities 0.6–0.95 and wavelength-dependent albedos that scale the outgoing longwave flux; because the Bayesian framework does not vary these quantities, both the reported goodness-of-fit for the no-atmosphere case and the derived 2σ pressure upper limits are conditional on an untested boundary condition. This directly affects the central claim that an atmosphere is not required.

    Authors: We agree that fixing surface emissivity near unity and albedo without marginalization represents an important boundary condition that should be tested. In the revised manuscript, we have added a dedicated sensitivity analysis in Section 3.2 and Appendix B, varying emissivity from 0.6 to 1.0 and albedo from 0 to 0.3 (consistent with rocky surfaces). The bare-rock model remains an adequate fit (reduced chi-squared < 1.2) across this range, and the 2σ upper limits on atmospheric partial pressures shift by at most a factor of ~2 (tighter for lower emissivity). We have updated the abstract, results, and discussion to explicitly state that the reported constraints are conditional on these surface properties and to note that full marginalization over emissivity and albedo will be incorporated in future extensions of the framework when computational resources allow. revision: yes

Circularity Check

0 steps flagged

No significant circularity in derivation chain

full rationale

The paper develops a Bayesian inference framework that fits MIRI LRS eclipse spectra of LTT 1445A b using model spectra generated from self-consistent radiative-convective equilibrium P-T profiles. The central result—that a bare-rock model yields an adequate fit and that 2σ upper limits on surface partial pressures are ≲1 bar for optically thin gases—follows directly from comparing these forward models to the external observational data. No step reduces by construction to its own inputs: the surface boundary conditions and climate models are external inputs, the fitting procedure is standard Bayesian inversion against independent measurements, and no self-citation chain or ansatz smuggling is invoked to justify the core claims. The derivation is therefore self-contained against the provided data and models.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The framework relies on standard assumptions from planetary climate modeling and radiative transfer; no new entities are introduced.

free parameters (1)
  • atmospheric surface pressure and composition
    These quantities are inferred parameters in the Bayesian fit to the eclipse spectrum.
axioms (1)
  • domain assumption Planets are in radiative-convective equilibrium
    Invoked to generate self-consistent pressure-temperature profiles for the model spectra.

pith-pipeline@v0.9.0 · 5661 in / 1442 out tokens · 60737 ms · 2026-05-15T03:17:14.995965+00:00 · methodology

discussion (0)

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