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Earth’s long-term climate stabilized by clouds


The Sun was dimmer earlier in Earth’s history, but glaciation was rare in the Precambrian: this is the ‘faint young Sun problem’. Most solutions rely on changes to the chemical composition of the atmosphere to compensate via a stronger greenhouse effect, whereas physical feedbacks have received less attention. We perform global climate model experiments, using two versions of the Community Atmosphere Model, in which a reduced solar constant is offset by higher CO2. Model runs corresponding to past climate show a substantial decrease in low clouds and hence planetary albedo compared with present, which contributes 40% of the required forcing to offset the faint Sun. Through time, the climatically important stratocumulus decks have grown in response to a brightening Sun and decreasing greenhouse effect, driven by stronger cloud-top radiative cooling (which drives low cloud formation) and a stronger inversion (which sustains clouds against dry air entrainment from above). We find that systematic changes to low clouds have had a major role in stabilizing climate through Earth’s history, which demonstrates the importance of physical feedbacks on long-term climate stabilization, and a smaller role for geochemical feedbacks.

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Fig. 1: Schematic representing the processes that maintain low cloud decks.
Fig. 2: Model climatology from CAM4.
Fig. 3: Zonally averaged model climatology from CAM4.
Fig. 4: Systematic dependence of key parameters on solar constant for CAM4 and CAM5.
Fig. 5: Model cloud climatology from CAM4.
Fig. 6: Difference in cloud forcing between CAM4 model runs with changes to solar constant compensated by changed CO2, and present day.

Data availability

Output from the climate and radiative transfer runs used here is archived in the Federated Research Data Repository at

Code availability

The CAM used here is part of the open source CESM, available from Offline runs of the CAM3/CAM4 radiation code were done using the Climate Modelling and Diagnostics Toolkit ( CAM5 uses the RRTMG radiation code ( Our analysis and plotting scripts are available at


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Financial support for this work came from an NSERC Discovery Grant to C.G., and NSERC USRA Fellowships to V.L.M. Computing facilities were provided by Westgrid and Compute Canada. We thank M. Dewey for performing the SMART runs and J. Xiong for performing the RRTMG runs used for radiative transfer intercomparison.

Author information

Authors and Affiliations



C.G. designed the study, lead the theoretical analysis and drafted the paper. V.L.M. ran the GCM experiments with help from K.E.M. and C.G., led the computational analysis and drafted the figures. All authors contributed to the analysis and to writing the paper.

Corresponding authors

Correspondence to Colin Goldblatt or Victoria L. McDonald.

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Competing interests

The authors declare no competing interests.

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Peer review information Nature Geoscience thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editor: Rebecca Neely.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Model climatology from CAM5.

Present day solar constant and CO2 (left column), 90% present day solar constant compensated by high CO2 (centre column), and difference (right column).

Extended Data Fig. 2 Zonally averaged model climatology from CAM5.

(a-b) Surface temperature and difference from present day, for 0.9≤S/S0≤1.05 shown as brown to pink, with present day in black. (c-e) are present day solar constant and CO2 (left column), 90% present day solar constant compensated by high CO2 (centre column), and difference (right column).

Extended Data Fig. 3 Model cloud climatolology from CAM5.

Present day solar constant and CO2 (left column), 90% present day solar constant compensated by high CO2 (centre column), and difference (right column).

Extended Data Fig. 4 Difference in cloud forcing between CAM5 model runs with changes to solar constant compensated by changed CO2 and present day.

Ratio of solar constant to modern, S/S0, is given as plot title. (a) Shortwave cloud forcing (compare to Fig. 5c), (b) longwave cloud forcing (compare to Fig. 5f).

Extended Data Fig. 5 Surface energy balance.

Markers correspond to CAM4 model runs. Flux type from CAM5 runs is to be inferred from nearest CAM4 line.

Extended Data Fig. 6 Two dimensional histograms of cloud behaviour against forcings.

Shading is area-weighted number of grid cells. (a) Anomalies in CAM4 for S/S0 = 0.8 (b) Anomalies in CAM4 for S/S0 = 0.9(c) Anomalies in CAM5 for S/S0 = 0.9. Whether there is any clear trend can be seen from any line that the high data density areas describe. Note how low cloud fraction and low cloud water path are positively correlated with EIS, whereas such positive correlations do not exist relative to surface temperature, humidity or latent heat flux.

Extended Data Fig. 7 CO2 and solar constant pairs used in model experiments.

S/S0 is the ratio of model to modern solar constant.

Extended Data Fig. 8 Radiative transfer verification.

Forcings are calculated as flux minus flux at standard greenhouse gas levels.

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Goldblatt, C., McDonald, V.L. & McCusker, K.E. Earth’s long-term climate stabilized by clouds. Nat. Geosci. 14, 143–150 (2021).

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