pith. machine review for the scientific record. sign in

arxiv: 2604.07461 · v1 · submitted 2026-04-08 · 🌌 astro-ph.EP · astro-ph.IM

Recognition: unknown

The Goldilocks problem for detecting water in terrestrial planets: Constraining water abundances in the mid-IR with LIFE

Sarah Rugheimer , Eleonora Alei , Bj\"orn S. Konrad , Benjamin Taysum , John Lee Grenfell , Tim Lichtenberg , Daniel Kitzmann , Floris van der Tak
show 2 more authors
Sascha P. Quanz LIFE collaboration
Authors on Pith no claims yet

Pith reviewed 2026-05-10 17:28 UTC · model grok-4.3

classification 🌌 astro-ph.EP astro-ph.IM
keywords exoplanetshabitabilitywater vapormid-infraredatmospheric retrievalterrestrial planetsLIFE mission
0
0 comments X

The pith

LIFE can constrain atmospheric water vapor abundances indicating habitable surface oceans on Earth-like exoplanets.

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

The paper tests whether the LIFE mission concept can use mid-infrared spectra to measure water vapor as a proxy for surface oceans on terrestrial planets. It simulates observations of a pre-biotic Earth-like world with surface water partial pressures from 10^{-7} to 1 bar, applying three different vertical distributions and Bayesian retrievals at resolutions of 50 and 100 while including realistic noise. For an Earth-like vertical profile the retrievals recover water levels from roughly 10^{-3} to 1 bar, a range the authors link to the presence of surface liquid water. Detection fails below 10^{-6} bar and becomes limited by saturation at the highest abundances, showing that results depend strongly on the assumed vertical structure. This matters because confirming atmospheric water at these levels would provide evidence of habitable surface conditions without needing direct surface imaging.

Core claim

Using simulated LIFE observations and Bayesian retrievals on models with constant, Manabe-Wetherald, and diffusion-photochemistry vertical water profiles, the authors show that LIFE can place meaningful constraints on H2O surface partial pressures between approximately 10^{-3} and 1 bar for an Earth-like distribution. This interval spans values both below and above modern Earth's 10^{-2} bar and is interpreted as evidence of surface oceans because water vapor reacts rapidly with surface minerals in their absence. Water remains undetectable in all profiles for surface pressures at or below 10^{-6} bar, while the highest abundances saturate features and reduce retrieval precision.

What carries the argument

Bayesian atmospheric retrievals on mid-infrared spectra simulated with LIFEsim at R=50 and 100, testing three vertical water distributions on a cloud-free pre-biotic Earth-like planet.

Load-bearing premise

That the three chosen vertical water profiles plus the complete absence of clouds represent the range of real exoplanet atmospheres and that any detectable atmospheric water must imply surface oceans.

What would settle it

An actual mid-infrared spectrum of a known terrestrial exoplanet whose surface water abundance and vertical profile have been measured independently, with the LIFE retrieval either recovering or failing to recover the correct H2O level within the modeled uncertainties.

Figures

Figures reproduced from arXiv: 2604.07461 by Benjamin Taysum, Bj\"orn S. Konrad, Daniel Kitzmann, Eleonora Alei, Floris van der Tak, John Lee Grenfell, LIFE collaboration, Sarah Rugheimer, Sascha P. Quanz, Tim Lichtenberg.

Figure 1
Figure 1. Figure 1: Water mixing ratios vs. altitude for each of our three profile assumptions (left) and the temperature vs altitude profile (right). The surface mixing ratio of water is fixed, spanning concentrations from 10−7 to 1 bar. The water profile above the surface is modeled to be constant with height (top panel), an Earth-like profile (middle panel), or from only diffusion and photochemical production (bottom panel… view at source ↗
Figure 2
Figure 2. Figure 2: Planet distance (AU) versus water surface mixing ratio (bar) needed to maintain an average surface tempera￾ture of 290K. While the surface mixing ratio of water is fixed, the profile higher up in the atmosphere can either be con￾stant with height (diamond), an Earth-like (cross), or based on diffusion and photochemistry (circle). for a low water, comparable to Mars (10−6 bar, red), medium Earth-like water … view at source ↗
Figure 3
Figure 3. Figure 3: Mid-IR input spectra at R=100 calculated by petitRADTRANS as input to LIFEsim for different H2O abun￾dances and H2O profiles. The top panel shows three spectra for vertically constant profile with surface H2O concentra￾tions corresponding to a water rich case of 1 bar (dark blue solid line), an Earth-like surface water case of 10−2 bar (pur￾ple line), and a water poor, Mars-like case of 10−6 bar (red line)… view at source ↗
Figure 4
Figure 4. Figure 4: Water posteriors for simulations for a range of surface H2O abundances from 1 bar to 10−7 bar at a resolution and signal to noise ratio of R = 100 and S/N = 10, respectively. The black lines are the H2O profiles in volume mixing ratios in log10(L) overlaying the H2O posteriors. The left panel assumes an altitude invariant profile for water, commonly used in retrievals. The center panel fixes the surface ab… view at source ↗
Figure 5
Figure 5. Figure 5: Corner plot for the posterior distributions from the retrievals of a 1 bar surface H2O vertically constant profile model. Black dotted lines indicate the expected values, abundances reported in volume mixing ratios. Retrieved values are the dashed black lines (both plotted as the median and 1σ uncertainties) and are in the table with the expected values. L denotes log10. Top-middle: The P–T profile with 2D… view at source ↗
Figure 6
Figure 6. Figure 6: As for [PITH_FULL_IMAGE:figures/full_fig_p017_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: As for [PITH_FULL_IMAGE:figures/full_fig_p018_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: As for [PITH_FULL_IMAGE:figures/full_fig_p019_8.png] view at source ↗
read the original abstract

We investigate how well the Large Interferometer for Exoplanets (LIFE) mission concept can detect habitable conditions on exoplanets through the presence of atmospheric water vapor as a proxy for surface oceans. We model the atmosphere of a pre-biotic Earth-like planet across a range of water concentrations, from water-poor to water-rich, with surface partial pressures from 10$^{-7}$ to 1 bar of H$_2$O. We simulate LIFE-like noise at spectral resolutions R = 50 and 100 using LIFEsim and perform Bayesian atmospheric retrievals to determine the technical requirements for LIFE to confirm habitability. We model three vertical water distributions: a vertically constant profile, a Manabe-Wetherald based Earth-like profile, and a diffusion and photochemistry profile to test how the assumed vertical structure influences the retrieved abundances. Clouds are not modeled. We find the ability for LIFE to detect water strongly depends on the vertical profile assumed. LIFE is unable to constrain the highest water cases and provides upper limits on low water planets. For the highest water abundances, absorption features saturate and reduce sensitivity to characterize precise H$_2$O levels. Water vapor is not detectable in any profile modeled for $\leq10^{-6}$ bar in surface water, comparable to Mars. For an Earth-like profile, LIFE could constrain H$_2$O concentrations from $\sim10^{-3}$ to 1 bar, spanning below and above present-day Earth concentrations of 10$^{-2}$ bar. Detectable atmospheric water may imply surface oceans, as water is highly reactive and rapidly removed by surface mineral reactions. Thus, LIFE can characterize water abundances indicative of habitable surface conditions.

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

3 major / 2 minor

Summary. The manuscript models pre-biotic Earth-like exoplanet atmospheres with surface H2O partial pressures ranging from 10^{-7} to 1 bar using three vertical profiles (constant, Manabe-Wetherald, and diffusion-photochemistry). LIFEsim is used to generate noisy mid-IR spectra at R=50 and 100, followed by Bayesian retrievals to evaluate LIFE's ability to detect and constrain water vapor as a habitability proxy. Key results are that detection depends strongly on the assumed vertical profile, water is undetectable below ~10^{-6} bar, constraints are possible from ~10^{-3} to 1 bar for an Earth-like profile (with saturation at high abundances), and detectable atmospheric water may imply surface oceans due to rapid mineral reactions.

Significance. If the results hold, the work offers useful guidance for LIFE mission design by quantifying the water-abundance range accessible in the mid-IR and demonstrating sensitivity to vertical structure. The multi-profile approach and use of realistic LIFE noise simulation are strengths that help identify saturation limits and non-detections at low abundances. This contributes to habitability assessment strategies, though the findings remain conditional on the modeling assumptions.

major comments (3)
  1. [Abstract and modeling approach] Abstract and modeling description: the claim that LIFE 'could constrain H2O concentrations from ∼10^{-3} to 1 bar' for an Earth-like profile is derived from retrievals performed under explicitly cloud-free conditions. At the modeled abundances up to 1 bar, condensation into water clouds is expected and would add continuum opacity that can mask or saturate the H2O features central to the retrieval; no sensitivity test or justification for omitting clouds is provided, making this assumption load-bearing for the high-water and habitability conclusions.
  2. [Abstract and vertical-profile tests] Abstract and vertical-profile tests: the three tested distributions (constant, Manabe-Wetherald, diffusion-photochemistry) do not incorporate cloud formation or its feedback on the H2O vertical structure and temperature profile. This omission directly affects whether the reported profile-dependent constraints and saturation behavior would persist in more realistic atmospheres.
  3. [Conclusions] Conclusions: the statement that 'detectable atmospheric water may imply surface oceans' is presented as a qualitative inference from mineral-reaction timescales but is not quantitatively connected to the retrieval framework, error bars, or simulated spectra; it therefore does not follow directly from the technical results.
minor comments (2)
  1. [Abstract] Abstract: quantitative retrieval metrics (e.g., posterior uncertainties, detection significances, or reduced-chi-squared values) are not reported for the different profiles and abundance cases, making it difficult to assess the strength of the 'constrain' statements.
  2. [Modeling section] Notation and clarity: the precise implementation details of the three vertical profiles (e.g., how the Manabe-Wetherald profile is scaled to the surface partial-pressure range) could be stated more explicitly to allow reproduction.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their constructive and detailed comments, which have helped us improve the clarity and balance of the manuscript. We respond to each major comment below and indicate the revisions made.

read point-by-point responses

  1. Referee: [Abstract and modeling approach] Abstract and modeling description: the claim that LIFE 'could constrain H2O concentrations from ∼10^{-3} to 1 bar' for an Earth-like profile is derived from retrievals performed under explicitly cloud-free conditions. At the modeled abundances up to 1 bar, condensation into water clouds is expected and would add continuum opacity that can mask or saturate the H2O features central to the retrieval; no sensitivity test or justification for omitting clouds is provided, making this assumption load-bearing for the high-water and habitability conclusions.

    Authors: We agree that performing the retrievals under cloud-free conditions is a key assumption, especially at the highest water abundances where condensation is expected. The manuscript explicitly states that clouds are not modeled, and our intent was to establish a baseline for water-vapor detectability by isolating the effects of abundance and vertical structure without the additional complexities of cloud microphysics and coverage. We have added a justification in the methods section for this choice and a dedicated paragraph in the discussion section acknowledging that continuum opacity from clouds could reduce sensitivity at high abundances and potentially alter the saturation behavior. We did not perform new cloud-inclusive sensitivity tests, as this would require substantial additional modeling assumptions outside the current scope, but we now flag this explicitly as a limitation for the high-abundance regime. revision: partial

  2. Referee: [Abstract and vertical-profile tests] Abstract and vertical-profile tests: the three tested distributions (constant, Manabe-Wetherald, and diffusion-photochemistry) do not incorporate cloud formation or its feedback on the H2O vertical structure and temperature profile. This omission directly affects whether the reported profile-dependent constraints and saturation behavior would persist in more realistic atmospheres.

    Authors: The referee correctly identifies that none of the three vertical profiles include cloud formation or its feedbacks on temperature and H2O structure. These profiles were chosen to systematically explore the sensitivity of the retrievals to different H2O distributions while keeping other variables fixed. In the revised manuscript we have expanded the discussion to describe how cloud formation could deplete upper-level water or modify the temperature profile, and we note that this could change the precise boundaries of the detectable range and the saturation limits we report. The profile dependence itself remains a robust qualitative result even within the simplified framework. revision: partial

  3. Referee: [Conclusions] Conclusions: the statement that 'detectable atmospheric water may imply surface oceans' is presented as a qualitative inference from mineral-reaction timescales but is not quantitatively connected to the retrieval framework, error bars, or simulated spectra; it therefore does not follow directly from the technical results.

    Authors: We accept that the link between detectable atmospheric water and surface oceans is an interpretive step based on known mineral-reaction chemistry rather than a direct quantitative output from the retrievals. The statement is supported by literature on rapid water-mineral reaction timescales on pre-biotic Earth, which would remove atmospheric H2O unless replenished by a surface reservoir. In the revised conclusions we have separated the technical retrieval findings from this interpretation, added specific references to the relevant reaction timescale studies, and clarified that the implication is contextual rather than a direct deduction from the simulated spectra or error bars. revision: yes

Circularity Check

0 steps flagged

No significant circularity in forward modeling and retrieval simulations

full rationale

The paper performs forward modeling of atmospheres with three specified vertical water profiles, simulates LIFE spectra via LIFEsim, and conducts Bayesian retrievals to assess constraints on H2O abundances. These steps produce outputs from external simulation and retrieval frameworks rather than reducing any claimed prediction to a quantity defined in terms of the paper's own fitted parameters or self-citations. The no-cloud modeling choice and interpretive link to surface oceans are explicit assumptions and statements, not self-definitional or load-bearing circular elements. The derivation chain is self-contained through standard methods and does not rely on uniqueness theorems or ansatzes imported from prior author work.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The central claim rests on atmospheric forward models, the choice of three vertical profiles, the absence of clouds, and the interpretation of water vapor as a surface-ocean proxy.

free parameters (1)
  • surface water partial pressure
    Parametrically varied from 10^{-7} to 1 bar to explore detection limits.
axioms (1)
  • domain assumption Detectable atmospheric water vapor implies surface oceans because water is highly reactive and rapidly removed by surface mineral reactions.
    Explicitly invoked in the abstract to link atmospheric detection to habitability.

pith-pipeline@v0.9.0 · 5651 in / 1302 out tokens · 42815 ms · 2026-05-10T17:28:44.754831+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

108 extracted references · 33 canonical work pages

  1. [1]

    S., Angerhausen, D., et al

    Alei, E., Konrad, B. S., Angerhausen, D., et al. 2022, Astronomy & Astrophysics, 665, A106

    2022

  2. [2]

    P., Konrad, B., et al

    Alei, E., Quanz, S. P., Konrad, B., et al. 2024, Astronomy & Astrophysics, 689, A245

    2024

  3. [3]

    B., Garvin, E

    Angerhausen, D., Balbi, A., Kovačević, A. B., Garvin, E. O., & Quanz, S. P. 2025, The Astronomical Journal, 169, 238, 10.3847/1538-3881/adb96d

    work page doi:10.3847/1538-3881/adb96d 2025

  4. [4]

    2024, The Astronomical Journal, 167, 128, 10.3847/1538-3881/ad1f4b

    Angerhausen, D., Pidhorodetska, D., Leung, M., et al. 2024, The Astronomical Journal, 167, 128, 10.3847/1538-3881/ad1f4b

    work page doi:10.3847/1538-3881/ad1f4b 2024

  5. [5]

    K., Aigrain, S., Irwin, P

    Barstow, J. K., Aigrain, S., Irwin, P. G., Kendrew, S., & Fletcher, L. N. 2016, Monthly Notices of the Royal Astronomical Society, 458, 2657

    2016

  6. [6]

    A., et al

    Bello-Arufe, A., Damiano, M., Bennett, K. A., et al. 2025, The Astrophysical Journal Letters, 980, L26

    2025

  7. [7]

    D., Nicholls , H., & Lichtenberg , T

    Boer , I. D., Nicholls , H., & Lichtenberg , T. 2025, , 987, 172, 10.3847/1538-4357/add69f

    work page doi:10.3847/1538-4357/add69f 2025

  8. [8]

    2020, Astronomy & Astrophysics, 637, A36

    Bourrier, V., Kitzmann, D., Kuntzer, T., et al. 2020, Astronomy & Astrophysics, 637, A36

    2020

  9. [9]

    2014, Astronomy & Astrophysics, 564, A125

    Buchner, J., Georgakakis, A., Nandra, K., et al. 2014, Astronomy & Astrophysics, 564, A125

    2014

  10. [10]

    2024, , 692, A172, 10.1051/0004-6361/202450764

    Cesario , L., Lichtenberg , T., Alei , E., et al. 2024, , 692, A172, 10.1051/0004-6361/202450764

    work page doi:10.1051/0004-6361/202450764 2024

  11. [11]

    Claire and John Sheets and Martin Cohen and Ignasi Ribas and Victoria S

    Claire , M. W., Sheets , J., Cohen , M., et al. 2012, , 757, 95, 10.1088/0004-637X/757/1/95

    work page doi:10.1088/0004-637x/757/1/95 2012

  12. [12]

    B., Lustig-Yaeger, J., Hu, R., Mayorga, L

    Cowan, N. B., Lustig-Yaeger, J., Hu, R., Mayorga, L. C., & Robinson, T. D. 2025, arXiv preprint arXiv:2507.03071

    work page arXiv 2025

  13. [13]

    B., Agol, E., Meadows, V

    Cowan, N. B., Agol, E., Meadows, V. S., et al. 2009, The Astrophysical Journal, 700, 915

    2009

  14. [14]

    2022, The Astronomical Journal, 163, 299

    Damiano, M., & Hu, R. 2022, The Astronomical Journal, 163, 299

    2022

  15. [15]

    Dannert, F. A. 2025, PhD thesis, ETH Zurich

    2025

  16. [16]

    A., Ottiger, M., Quanz, S

    Dannert, F. A., Ottiger, M., Quanz, S. P., et al. 2022, Astronomy & Astrophysics, 664, A22

    2022

  17. [17]

    A., Huber, P

    Dannert, F. A., Huber, P. A., Birbacher, T., et al. 2025, The Astronomical Journal, 170, 193

    2025

  18. [18]

    2009, , 121, 952, 10.1086/605913

    Deming , D., Seager , S., Winn , J., et al. 2009, , 121, 952, 10.1086/605913

    work page doi:10.1086/605913 2009

  19. [19]

    J., Harwit , M

    Des Marais , D. J., Harwit , M. O., Jucks , K. W., et al. 2002, Astrobiology, 2, 153, 10.1089/15311070260192246

    work page doi:10.1089/15311070260192246 2002

  20. [20]

    2025, Nature Astronomy, 9, 358

    Ducrot, E., Lagage, P.-O., Min, M., et al. 2025, Nature Astronomy, 9, 358

    2025

  21. [21]

    2024, in Space Telescopes and Instrumentation 2024: Optical, Infrared, and Millimeter Wave, Vol

    Feinberg, L., Ziemer, J., Ansdell, M., et al. 2024, in Space Telescopes and Instrumentation 2024: Optical, Infrared, and Millimeter Wave, Vol. 13092, SPIE, 511--522

    2024

  22. [22]

    K., Robinson, T

    Feng, Y. K., Robinson, T. D., Fortney, J. J., et al. 2018, The Astronomical Journal, 155, 200

    2018

  23. [23]

    1992, Journal of Atmospheric Sciences, 49, 2139

    Fu, Q., & Liou, K. 1992, Journal of Atmospheric Sciences, 49, 2139

    1992

  24. [24]

    2025, submitted

    Fujii, Y., Angerhausen, D., Matsuo, T., & Wolf, E. 2025, submitted

    2025

  25. [25]

    D., Li, C., & Yung, Y

    Gao, P., Hu, R., Robinson, T. D., Li, C., & Yung, Y. L. 2015, The Astrophysical Journal, 806, 249

    2015

  26. [26]

    2018, Astrobiology, 18, 856

    Gebauer, S., Grenfell, J., Lehmann, R., & Rauer, H. 2018, Astrobiology, 18, 856

    2018

  27. [27]

    J., & Conrath , B

    Gierasch , P. J., & Conrath , B. J. 1985, in Recent Advances in Planetary Meteorology, ed. G. E. Hunt , 121--146

    1985

  28. [28]

    1989, Journal of Quantitative Spectroscopy and Radiative Transfer, 42, 539

    Goody, R., West, R., Chen, L., & Crisp, D. 1989, Journal of Quantitative Spectroscopy and Radiative Transfer, 42, 539

    1989

  29. [29]

    P., Bell, T

    Greene, T. P., Bell, T. J., Ducrot, E., et al. 2023, Nature, 618, 39

    2023

  30. [30]

    L., Gebauer, S., Godolt, M., et al

    Grenfell, J. L., Gebauer, S., Godolt, M., et al. 2018, The Astrophysical Journal, 861, 38

    2018

  31. [31]

    L., Stracke, B., von Paris, P., et al

    Grenfell, J. L., Stracke, B., von Paris, P., et al. 2007, , 55, 661

    2007

  32. [32]

    2015, The Astrophysical Journal, 812, 137

    Harman, C., Schwieterman, E., Schottelkotte, J., & Kasting, J. 2015, The Astrophysical Journal, 812, 137

    2015

  33. [33]

    R., Hurford, T

    Hendrix, A. R., Hurford, T. A., Barge, L. M., et al. 2019, Astrobiology, 19, 1

    2019

  34. [34]

    A., Dannert, F

    Huber, P. A., Dannert, F. A., Laugier, R., et al. 2024, in Optical and Infrared Interferometry and Imaging IX, Vol. 13095, SPIE, 382--391

    2024

  35. [35]

    A., Dannert, F

    Huber, P. A., Dannert, F. A., Laugier, R., et al. 2025, The Astronomical Journal, 170, 227

    2025

  36. [36]

    Ingersoll, A. P. 1969, Journal of Atmospheric Sciences, 26, 1191

    1969

  37. [37]

    1998, Journal of Geophysical Research: Atmospheres, 103, 21967

    Johnston, H., & Kinnison, D. 1998, Journal of Geophysical Research: Atmospheres, 103, 21967

    1998

  38. [38]

    Jordan, S., Shorttle, O., & Rimmer, P. B. 2025, Science Advances, 11, eadp8105

    2025

  39. [39]

    2012, International Journal of Astrobiology, 11, 297–307, 10.1017/S1473550412000134

    Kaltenegger, L., Miguel, Y., & Rugheimer, S. 2012, International Journal of Astrobiology, 11, 297–307, 10.1017/S1473550412000134

    work page doi:10.1017/s1473550412000134 2012

  40. [40]

    Kaltenegger , L., & Traub , W. A. 2009, , 698, 519, 10.1088/0004-637X/698/1/519

    work page doi:10.1088/0004-637x/698/1/519 2009

  41. [41]

    A., & Jucks , K

    Kaltenegger , L., Traub , W. A., & Jucks , K. W. 2007, , 658, 598, 10.1086/510996

    work page doi:10.1086/510996 2007

  42. [42]

    Kasting , J. F. 1988, Icarus, 74, 472, 10.1016/0019-1035(88)90116-9

    work page doi:10.1016/0019-1035(88)90116-9 1988

  43. [43]

    F., Chen, H., & Kopparapu, R

    Kasting, J. F., Chen, H., & Kopparapu, R. K. 2015, The Astrophysical Journal Letters, 813, L3

    2015

  44. [44]

    F., Pollack , J

    Kasting , J. F., Pollack , J. B., & Crisp , D. 1984, J. Atmos. Chem., 1, 403

    1984

  45. [45]

    F., Whitmire, D

    Kasting, J. F., Whitmire, D. P., & Reynolds, R. T. 1993, Icarus, 101, 108

    1993

  46. [46]

    2019, The Astronomical Journal, 157, 213

    Kawashima, Y., & Rugheimer, S. 2019, The Astronomical Journal, 157, 213

    2019

  47. [47]

    F., & Siefert , J

    Kharecha , P., Kasting , J. F., & Siefert , J. 2005, Geobiology, 3, 53

    2005

  48. [48]

    Kitzmann , D., Patzer , A. B. C., von Paris , P., Godolt , M., & Rauer , H. 2011 a , , 531, A62, 10.1051/0004-6361/201014343

    work page doi:10.1051/0004-6361/201014343 2011

  49. [49]

    2011 b , , 534, A63, 10.1051/0004-6361/201117375

    ---. 2011 b , , 534, A63, 10.1051/0004-6361/201117375

    work page doi:10.1051/0004-6361/201117375 2011

  50. [50]

    2022, Astronomy & Astrophysics, 664, A23

    Konrad, B., Alei, E., Quanz, S., et al. 2022, Astronomy & Astrophysics, 664, A23

    2022

  51. [51]

    S., Quanz, S

    Konrad, B. S., Quanz, S. P., Alei, E., & Wordsworth, R. 2024, The Astrophysical Journal, 975, 13

    2024

  52. [52]

    S., Alei , E., Quanz , S

    Konrad , B. S., Alei , E., Quanz , S. P., et al. 2023, , 673, A94, 10.1051/0004-6361/202245655

    work page doi:10.1051/0004-6361/202245655 2023

  53. [53]

    K., Ramirez, R., Kasting, J

    Kopparapu , R. K., Ramirez , R., Kasting , J. F., et al. 2013, , 765, 131, 10.1088/0004-637X/765/2/131

    work page doi:10.1088/0004-637x/765/2/131 2013

  54. [54]

    Krasnopolsky, V. A. 2010, Icarus, 207, 638

    2010

  55. [55]

    2012, Icarus, 218, 230

    ---. 2012, Icarus, 218, 230

    2012

  56. [56]

    A., & Oinas, V

    Lacis, A. A., & Oinas, V. 1991, Journal of Geophysical Research: Atmospheres, 96, 9027

    1991

  57. [57]

    D., & Morley, C

    Loftus, K., Wordsworth, R. D., & Morley, C. V. 2019, The Astrophysical Journal, 887, 231

    2019

  58. [58]

    2015, Astrobiology, 15, 119

    Luger , R., & Barnes , R. 2015, Astrobiology, 15, 119

    2015

  59. [59]

    S., & Lincowski, A

    Lustig-Yaeger, J., Meadows, V. S., & Lincowski, A. P. 2019, The Astrophysical Journal Letters, 887, L11

    2019

  60. [60]

    S., Mendoza, G

    Lustig-Yaeger, J., Meadows, V. S., Mendoza, G. T., et al. 2018, The Astronomical Journal, 156, 301

    2018

  61. [61]

    Manabe, S., & Wetherald, R. T. 1967, J. atmos. Sci, 24, 241

    1967

  62. [62]

    1981, Journal of Geophysical Research: Oceans, 86, 9859

    Massie, S., & Hunten, D. 1981, Journal of Geophysical Research: Oceans, 86, 9859

    1981

  63. [63]

    McCullough, P. R. 2006, arXiv: Astrophysics. https://api.semanticscholar.org/CorpusID:16867414

    2006

  64. [64]

    S., Reinhard, C

    Meadows, V. S., Reinhard, C. T., Arney, G. N., et al. 2018, Astrobiology, 18, 630

    2018

  65. [65]

    S., Quanz, S

    Mettler, J.-N., Konrad, B. S., Quanz, S. P., & Helled, R. 2024, The Astrophysical Journal, 963, 24, 10.3847/1538-4357/ad198b

    work page doi:10.3847/1538-4357/ad198b 2024

  66. [66]

    L., & Rugheimer , S

    Miguel , Y., Kaltenegger , L., Linsky , J. L., & Rugheimer , S. 2015, MNRAS, 446, 345

    2015

  67. [67]

    2019, Astronomy & Astrophysics, 627, A67

    Molli \`e re, P., Wardenier, J., Van Boekel, R., et al. 2019, Astronomy & Astrophysics, 627, A67

    2019

  68. [68]

    2020, Astronomy & Astrophysics, 640, A131

    Molli \`e re, P., Stolker, T., Lacour, S., et al. 2020, Astronomy & Astrophysics, 640, A131

    2020

  69. [69]

    E., Stevenson, K

    Moran, S. E., Stevenson, K. B., Sing, D. K., et al. 2023, The Astrophysical Journal Letters, 948, L11

    2023

  70. [70]

    M., et al

    Nasedkin, E., Schrader, M., Vos, J. M., et al. 2025, Astronomy & Astrophysics, 702, A1

    2025

  71. [71]

    2021, Pathways to Discovery in Astronomy and Astrophysics for the 2020s

    National Academies of Sciences, E., Medicine, et al. 2021, Pathways to Discovery in Astronomy and Astrophysics for the 2020s

    2021

  72. [72]

    Seligman and Amaya Moro-Mart

    Padovani, P., & Cirasuolo, M. 2023, Contemporary Physics, 64, 47, 10.1080/00107514.2023.2266921

    work page doi:10.1080/00107514.2023.2266921 2023

  73. [73]

    A., Brown , L

    Pavlov , A. A., Brown , L. L., & Kasting , J. F. 2001, , 106, 23267, 10.1029/2000JE001448

    work page doi:10.1029/2000je001448 2001

  74. [74]

    A., & Kasting , J

    Pavlov , A. A., & Kasting , J. F. 2002, Astrobiology, 2, 27, 10.1089/153110702753621321

    work page doi:10.1089/153110702753621321 2002

  75. [75]

    A., Kasting , J

    Pavlov , A. A., Kasting , J. F., Brown , L. L., Rages , K. A., & Freedman , R. 2000, , 105, 11981, 10.1029/1999JE001134

    work page doi:10.1029/1999je001134 2000

  76. [76]

    P., Kammerer, J., Defr \`e re, D., et al

    Quanz, S. P., Kammerer, J., Defr \`e re, D., et al. 2018, in Optical and Infrared Interferometry and Imaging VI, Vol. 10701, SPIE, 415--431

    2018

  77. [77]

    P., Ottiger, M., Fontanet, E., et al

    Quanz, S. P., Ottiger, M., Fontanet, E., et al. 2022 a , Astronomy & Astrophysics, 664, A21

    2022

  78. [78]

    P., Absil, O., Benz, W., et al

    Quanz, S. P., Absil, O., Benz, W., et al. 2022 b , Experimental Astronomy, 54, 1197

    2022

  79. [79]

    v., Paris, P., et al

    Rauer, H., Gebauer, S. v., Paris, P., et al. 2011, , 529

    2011

  80. [80]

    D., Meadows, V

    Robinson, T. D., Meadows, V. S., & Crisp, D. 2010, The Astrophysical Journal Letters, 721, L67

    2010

Showing first 80 references.