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Day–night cloud asymmetry prevents early oceans on Venus but not on Earth

Abstract

Earth has had oceans for nearly four billion years1 and Mars had lakes and rivers 3.5–3.8 billion years ago2. However, it is still unknown whether water has ever condensed on the surface of Venus3,4 because the planet—now completely dry5—has undergone global resurfacing events that obscure most of its history6,7. The conditions required for water to have initially condensed on the surface of Solar System terrestrial planets are highly uncertain, as they have so far only been studied with one-dimensional numerical climate models3 that cannot account for the effects of atmospheric circulation and clouds, which are key climate stabilizers. Here we show using three-dimensional global climate model simulations of early Venus and Earth that water clouds—which preferentially form on the nightside, owing to the strong subsolar water vapour absorption—have a strong net warming effect that inhibits surface water condensation even at modest insolations (down to 325 watts per square metre, that is, 0.95 times the Earth solar constant). This shows that water never condensed and that, consequently, oceans never formed on the surface of Venus. Furthermore, this shows that the formation of Earth’s oceans required much lower insolation than today, which was made possible by the faint young Sun. This also implies the existence of another stability state for present-day Earth: the ‘steam Earth’, with all the water from the oceans evaporated into the atmosphere.

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Fig. 1: Day and night water cloud feedbacks.
Fig. 2: Water clouds and thermal emission horizontal maps.
Fig. 3: Mechanisms of nocturnal cloud formation.
Fig. 4: Hysteresis loops and conditions of ocean formation on Earth and Venus.

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Data availability

The data that support the findings of this study are available at https://doi.org/10.5281/zenodo.4680905Source data are provided with this paper.

Code availability

The LMD Generic global climate model code (and documentation on how to use the model) used in this work can be downloaded from the SVN repository at https://svn.lmd.jussieu.fr/Planeto/trunk/LMDZ.GENERIC/ (version 2528). More information and documentation are available at http://www-planets.lmd.jussieu.fr.

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Acknowledgements

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement number 832738/ESCAPE. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement numbers 724427/FOUR ACES and 679030/WHIPLASH). This work has been carried out within the framework of the National Centre of Competence in Research PlanetS supported by the Swiss National Science Foundation. We acknowledge the financial support of the SNSF. M.T. thanks the Gruber Foundation for its support to this research. M.T. thanks N. Chaniaud for her help in preparing Fig. 1. We thank the LMD Generic global climate team for the teamwork development and improvement of the model. This work was performed using the high-performance computing resources of Centre Informatique National de l’Enseignement Supérieur (CINES) under the allocation A0080110391 made by Grand Équipement National de Calcul Intensif (GENCI). A total of about 600,000 CPU hours were used for this project on the OCCIGEN supercomputer, resulting in roughly one ton equivalent of CO2 emissions.

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Contributions

M.T. developed the core ideas of the manuscript, developed and performed the 3D GCM simulations, wrote the manuscript and prepared the figures. E.B. and G.C. provided advice on sensitivity studies. D.E., G.C. and J.L. provided advice on the structure of the figures. J.L. provided advice on the organization of the manuscript, as well as for understanding the mechanism of cloud formation. E.M. provided advice on literature selection. All authors provided guidance and comments on the manuscript.

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Correspondence to Martin Turbet.

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Peer review information Nature thanks Stephen Kane, James Kasting and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Temporal evolution of modelled surface temperatures.

Temporal evolution of the globally averaged surface temperatures in the 3-D GCM baseline simulations of (initially hot and steamy) Venus, for several insolations.

Extended Data Fig. 2 Cloud forcings in hot and steamy early Venus and Earth simulations.

Radiative balance of clouds on hot and steamy Earth (a) and Venus (b) as a function of the incident solar flux. Blue curves indicate the greenhouse effect of clouds. Red curves indicate the amount of incoming solar radiation reflected back by the clouds (the more negative the value, the greater the reflected flux.). Black curves indicate the net radiative effect of clouds (positive values mean warming). In all initially hot and steamy simulations, clouds lead to a strong atmospheric warming.

Source data

Extended Data Fig. 3 Radiative budget comparisons between 1D and 3D models.

Thermal emission to space (a) and bond albedo (b) as a function of the surface temperature for our 3-D GCM simulations of Earth (blue) and Venus (red). We have also added the results of 1-D radiative-convective cloud-free calculations29 (in black), using H2O and N2 partial pressures of 10 and 1 bar, respectively, as in the 3-D baseline simulations. For comparison, we added the moist tropospheric radiation limits68 for the thermal emission67 and the bond albedo from refs. 27,28.

Source data

Extended Data Fig. 4 Impact of cloud microphysical properties on their spatial distribution.

Maps of water cloud column for early Venus (at a top-of-atmosphere insolation of 500 W m−2, i.e. the minimal insolation received on Venus, about 4 billion years ago when the Sun was 25% fainter than today), with different cloud microphysics parameterisations (103, 104, 105, 106 and 107 cloud condensation nuclei (CCN) per kg of air, for panels a, b, c, d and e, respectively). The maps were calculated in the heliocentric frame (i.e., keeping the subsolar point at 0° longitude and 0° latitude), and using an average of two Venusian days. The distribution of clouds (present on the nightside, absent on the dayside) is robust to the choice of the number of CCN.

Source data

Extended Data Fig. 5 Effects of water and carbon dioxide atmospheric contents.

Impact of the water and carbon dioxide atmospheric contents on the surface temperature (a), thermal emission to space (b), bond albedo (c) and net cloud radiative forcing (d). The calculations assume a hot and steamy Venus (insolation at 500 W/m2) with 1 bar of N2 and between 1 and 30 bar of H2O (in blue); with 1-10 bar of CO2 and 10 bar of H2O (in red).

Extended Data Table 1 Summary of the main physical parameters used in the GCM for the baseline hot and steamy Earth and Venus simulations

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Turbet, M., Bolmont, E., Chaverot, G. et al. Day–night cloud asymmetry prevents early oceans on Venus but not on Earth. Nature 598, 276–280 (2021). https://doi.org/10.1038/s41586-021-03873-w

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