Search arXivSearch

arXiv · 2308.15110

Water Condensation Zones around Main Sequence Stars

Abstract

Understanding the set of conditions that allow rocky planets to have liquid water on their surface -- in the form of lakes, seas or oceans -- is a major scientific step to determine the fraction of planets potentially suitable for the emergence and development of life as we know it on Earth. This effort is also necessary to define and refine the so-called "Habitable Zone" (HZ) in order to guide the search for exoplanets likely to harbor remotely detectable life forms. Until now, most numerical climate studies on this topic have focused on the conditions necessary to maintain oceans, but not to form them in the first place. Here we use the three-dimensional Generic Planetary Climate Model (PCM), historically known as the LMD Generic Global Climate Model (GCM), to simulate water-dominated planetary atmospheres around different types of Main-Sequence stars. The simulations are designed to reproduce the conditions of early ocean formation on rocky planets due to the condensation of the primordial water reservoir at the end of the magma ocean phase. We show that the incoming stellar radiation (ISR) required to form oceans by condensation is always drastically lower than that required to vaporize oceans. We introduce a Water Condensation Limit, which lies at significantly lower ISR than the inner edge of the HZ calculated with three-dimensional numerical climate simulations. This difference is due to a behavior change of water clouds, from low-altitude dayside convective clouds to high-altitude nightside stratospheric clouds. Finally, we calculated transit spectra, emission spectra and thermal phase curves of TRAPPIST-1b, c and d with H2O-rich atmospheres, and compared them to CO2 atmospheres and bare rock simulations. We show using these observables that JWST has the capability to probe steam atmospheres on low-mass planets, and could possibly test the existence of nightside water clouds.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Martin Turbet, Thomas J. Fauchez, Jeremy Leconte, Emeline Bolmont, Guillaume Chaverot, Francois Forget, Ehouarn Millour, Franck Selsis, Benjamin Charnay, Elsa Ducrot, Michaël Gillon, Alice Maurel, Geronimo L. Villanueva. 2023-08-29. Water Condensation Zones around Main Sequence Stars. https://doi.org/10.1051/0004-6361%2F202347539

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Strict Limits on Helium Absorption from LHS 1140 b from Four JWST NIRISS Transits

Orbiting in the habitable zone of its host star, the 1.7 $R_\oplus$, 5.6 $M_\oplus$ planet LHS 1140 b is a target of great interest. Recently Cherubim et al. (2026) published a detection of metastable He escaping from the atmosphere of LHS 1140 b, simultaneously providing the first concrete inference of an atmosphere on this planet and indicating that the atmosphere is He-rich and H-poor as would be expected due to Gyrs of fractionated mass loss. In this work, we analyze four archival transits of LHS 1140 b, spanning Dec 2023 to Jul 2026, taken with the NIRISS instrument on JWST, for evidence of He absorption. Each of the four visits disfavours the presence of He absorption compared to a flat continuum with odds ratios ranging from 3.9--11.6:1. He absorption with an amplitude and width equivalent to that observed by Cherubim et al. (2026) is strongly ruled out by the data with odds ratios from 300--8.6$\times$10$^4$:1 compared to a flat continuum --- though it should be noted that none of the JWST transits are contemporaneous with the Cherubim et al. (2026) detection. We also fit the absolute out-of-transit stellar spectra from these four visits, as well as an additional JWST NIRISS transit of planet c, to search for evidence of stellar variability, but find consistent photosphere and herterogeneity parameters in all five datasets. In all, our work provides a set of strict limits on He escape from LHS 1140 b that will be valuable to future studies into the nature and evolution of this intriguing world.

astro-ph.EP

Bridging magnetothermal winds and photoevaporation to model discs dispersal

Protoplanetary disc dispersal is driven by two processes usually modelled separately: photoevaporative and magnetohydrodynamic (MHD) disc winds. Global simulations indicate that in the inner disc these are not distinct outflows but a single magnetothermal wind. We assemble a closed-form, two-phase model that respects it. A single-field-line wind, whose base is fixed by the irradiated temperature and penetration column, supplies the launch and feeds a secular evolution, with photoevaporation convolved on as a sink. The flux closure $B_z\proptoΣ^q$ is self-limiting: for $q\le1/2$ depletion alone cannot demagnetise the disc, so dispersal requires independent flux loss, parameterised by the magnetic Reynolds number $\mathcal{R}_m$. Integrating the coupled system yields two regimes. Efficient flux loss ($\mathcal{R}_m\lesssim1$) lets the magnetisation front recede by over an order of magnitude and opens a photoevaporative gap. Flux retention ($\mathcal{R}_m\gg1$) drives the front outward, sustains accretion, and defers dispersal by $\approx2.7$~Myr. Deriving the base from stellar irradiation instead of prescribing it, we find that the cold-launch approximation is valid during the early stages of disc evolution: anchoring the base at plasma equipartition ($β_{\rm base} \sim 1$) confines irradiation's influence on the magnetic lever arm to the magnetothermal annulus, decoupling the peak accretion rate from the incident flux. Both regimes clear the disc inside-out, through either a photoevaporatively amplified cavity wall or an expanding magnetothermal front.

astro-ph.EP

Faithful Neural Embeddings for 3D Exoplanet Climate Modeling

With the rapid advancement of telescopes like JWST and Ariel, there is an urgent need for efficient 3D climate models to interpret observations of exoplanet atmospheres. Traditional 3D general circulation models (GCMs) are computationally intensive, prompting the development of machine learning (ML) emulators to accelerate simulations. Recent work, such as that by Plaschzug et al. 2026 \cite{plaschzug2026accelerating}, uses a dense neural network (DNN) to predict local gas temperatures and winds from input parameters, including local gas pressure, spatial coordinates (longitude and latitude), and global temperature. However, this model relies on predicting individual temperature values (points) at specific grid points, which can be limited by the resolution and constraints of the training grid. In this work, we investigate a couple of alternative frameworks based on latent-space representations of local gas temperature ($\text{T}_{\text{gas}}$) to obtain a faithful, low-dimensional representation of these profiles. This represents the first step toward developing a latent space regression model, offering a structurally cohesive alternative to the existing point-wise prediction method \cite{plaschzug2026accelerating}. By capturing the optimal embedding space of atmospheric data, our proposed framework can produce simulated profiles while maintaining computational efficiency, making it suitable for large-scale exoplanet ensemble studies.

astro-ph.EP