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Ice-free tropical waterbelt for Snowball Earth events questioned by uncertain clouds


Geological evidence of active tropical glaciers reaching sea level during the Neoproterozoic (1,000–541 Ma), suggesting a global ocean completely covered in ice, was the key observation in the development of the hard Snowball Earth hypothesis. These conditions are hard to reconcile with the survival of complex marine life through Snowball Earth glaciations, which led to alternative waterbelt scenarios where a large-scale refugium was present in the form of a narrow ice-free strip in the tropical ocean. Here we assess whether a waterbelt scenario maintained by snow-free dark sea ice at low latitudes is plausible using simulations from two climate models run with a variety of cloud treatments in combination with an energy-balance model. Our simulations show that waterbelt states are not a robust and naturally emerging feature of Neoproterozoic climate. Intense shortwave reflection by mixed-phase clouds, in addition to a low albedo of bare sea ice, is needed for geologically relevant waterbelt states. Given the large uncertainty in mixed-phase clouds and their interaction with radiation, our results strongly question the idea that waterbelt scenarios can explain the Neoproterozoic geology. Hence, Neoproterozoic life has probably faced the harsh conditions of a hard Snowball Earth.

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Fig. 1: Low-latitude clouds control the existence and absence of waterbelt states in the GCMs CAM and ICON.
Fig. 2: Differences in clouds and their SWCRE as obtained from the GCMs CAM and ICON as well as ICON WBF.
Fig. 3: Analysis of the waterbelt regime in a one-dimensional EBM.

Data availability

The data and corresponding run scripts that support the findings of this study45 are available at

Code availability

The custom computer code used to generate the results45 is available at


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C.B. and A.V. received support from Deutsche Forschungsgemeinschaft (DFG) under grant agreement VO 1765/5-1. A.V. received partial support from the German Ministry of Education and Research (BMBF) and FONA: Research for Sustainable Development ( under grant agreement 01LK1509A. J.G.P. thanks the AXA Research Fund for support. We thank the German Climate Computing Centre (DKRZ, Hamburg) for computing and storage resources as part of project 1092 and T. Mauritsen for pointing us towards the WBF modification in ICON.

Author information

Authors and Affiliations



A.V. designed the study. C.B. and J.H. implemented modifications in CAM and ICON. C.B. performed the CAM simulations. J.H. and C.B. performed the ICON simulations. C.B. performed the analysis, created the figures and wrote the initial draft. C.B. and A.V. led the writing of the final draft. All authors contributed with discussions and edited the manuscript.

Corresponding authors

Correspondence to Christoph Braun or Aiko Voigt.

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The authors declare no competing interests.

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Nature Geoscience thanks Robin Wordsworth and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: James Super and Tamara Goldin, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Temporal evolution of the global-mean ice edge latitude for the default GCM setups.

(a) CAM and (b) ICON. Global-mean ice edge latitude is calculated as the sine of global-mean ice-free surface fraction. Labels indicate the constant atmospheric CO2 concentration and the global-mean ice-edge latitude of the initialisation. Thin lines represent the 10-year rolling mean. Solid lines indicate simulations considered to exhibit (semi-)stable waterbelt states. Thick solid lines represent monthly-mean for 40-year periods that are analyzed as (semi-)stable waterbelt states.

Extended Data Fig. 2 Low clear-sky planetary albedo due to exposure of bare sea ice in the subtropical region in CAM and ICON.

Climatological zonal-mean clear-sky planetary albedo determined from (a) CAM simulation at 10000 ppmv CO2 and (b) ICON simulation at 4063 ppmv CO2. Dashed contours indicate the water-equivalent snow thickness of 0.01 m, which marks the minimum thickness of a snow-layer to be considered in the determination of the surface albedo in ICON. For each simulation 40-year periods are analyzed. Further details are given in text S1.

Extended Data Fig. 3 CAM and ICON exhibit similar large-scale thermal structure across the seasonal cycle and the simulated CO2- range.

Monthly climatological zonal-mean cloud cover and air temperature indicated by isotherms determined from CAM at 2000 ppmv CO2 and 10000 ppmv CO2, and ICON at 4063 ppmv CO2. Each period of analysis spans 40 years after stabilizing in a stable waterbelt state.

Extended Data Fig. 4 CAM and ICON exhibit similar large-scale circulation in CAM and ICON across the seasonal cycle and the simulated CO2- range.

Monthly climatological zonal-mean cloud cover and mass stream function indicated by contours. Contour intervals are 5  1010 kgs−1. Positive contours are solid and negative contours are dashed. The zero contour is not shown. The mass stream function is calculated by \(\psi (p,\phi )=2\Pi {r}_{E}cos(\phi )/g\int\nolimits_{p}^{{p}_{s}}vdp\) with pressure p, surface pressure ps, latitude ϕ, radius of Earth rE = 6371 km, gravitational constant g = 9.81 ms−2, and zonal-mean meridional wind v. Same simulations and time periods as in Extended Data Figure 3 are used.

Extended Data Fig. 5 Temporal evolution of the global-mean ice edge latitude for the modified GCM setups.

(a) CAM pCOOKIE and (b) ICON WBF. See caption of Extended Data Figure 1 for further details.

Extended Data Fig. 6 Impact of pCOOKIE modification in CAM on clouds and cloud-radiative effects.

(a) Planetary albedo α, (b) total cloud cover, (c) shortwave CRE, and (e) longwave CRE for CAM standard and pCOOKIE. Shown are 40-year-means over all simulations after stabilizing in a stable waterbelt state. (d) 40-year-mean of zonal-mean cloud cover from a single simulation with CAM pCOOKIE after stabilizing in a waterbelt state at 5000 ppmv CO2 along with 273 K, 235 K, and 192 K isotherms.

Extended Data Fig. 7 Impact of WBF modification in ICON on cloud liquid and longwave cloud-radiative effect.

(a) and (b): Annual-mean zonal-mean specific cloud liquid from single simulations after stabilizing in a waterbelt state at 4063 ppmv CO2 (ICON) and 6000 ppmv CO2 (ICON WBF) along with 273 K, 235 K, and 192 K isotherms. (c) Annual-mean zonal-mean liquid water path LWP, and (d) longwave CRE averaged over all simulations with a (semi-)stable waterbelt state. The period of analysis spans 40 years after stabilizing in a (semi-)stable waterbelt state.

Extended Data Fig. 8 The geologically relevant domain of waterbelt states is impacted by the intensity of meridional heat transport.

Domains spanned by planetary albedo over icefree ocean αo and bare sea ice albedo αi,b for stable and accessible waterbelt impacted by the intensity of meridional heat transport. states (white) and stable but unaccessible waterbelt states (light gray). The orange circle marks albedo values for CAM pCOOKIE. The orange line marks the lower boundary of the stable and accessible domain and is calculated with the meridional heat transport parameter C = 1.6B corresponding to CAM pCOOKIE. The black dotted line marks the lower boundary of the stable and accessible domain if calculated with C = 1.5B corresponding to CAM (similar as in Fig. 3c). Weaker meridional heat transport stabilizes the waterbelt climate because it is characterized by strong meridional temperature gradients. The red dotted box indicates the range of plausible values for αo and αi,b.

Extended Data Table 1 Estimates for the longwave feedback parameter based on GCM simulations

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Braun, C., Hörner, J., Voigt, A. et al. Ice-free tropical waterbelt for Snowball Earth events questioned by uncertain clouds. Nat. Geosci. 15, 489–493 (2022).

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