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Greater climate sensitivity implied by anvil cloud thinning

Nature Geoscience (2024)Cite this article

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Abstract

High clouds produced by tropical convection are expected to shrink in area as the climate warms, and the radiative feedback associated with this change has long been the subject of controversy. In a recent assessment of climate sensitivity, the World Climate Research Programme estimated that this feedback is substantially negative, albeit with substantial uncertainty. Here we examine the cloud response using an approach that treats high clouds as part of an optical continuum rather than entities with fixed opacity. We show that a substantial negative feedback is not supported by an ensemble of high-resolution atmospheric models. Rather, the models suggest that changes in cloud area and opacity together act as a weakly positive feedback. The positive opacity component arises from the disproportionate reduction in the area of thick, climate-cooling clouds relative to thin, climate-warming clouds. This suggests that thick cloud area is tightly coupled to the rate of convective overturning—which is expected to slow with warming—whereas thin cloud area is influenced by other, less certain processes. The positive feedback differs markedly from previous estimates and leads to a +0.3 °C shift in the median estimate of equilibrium climate sensitivity relative to a previous community assessment.

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Fig. 1: The tropical ice cloud continuum.
Fig. 2: Model representations of the ice cloud continuum.
Fig. 3: The ice cloud response to warming and its radiative effects.
Fig. 4: Updating the PDF of ECS.

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Data availability

The DARDAR-Cloud satellite products are available at https://www.icare.univ-lille.fr/dardar/data-access/ and the 2C-ICE products at https://www.cloudsat.cira.colostate.edu/data-products/2c-ice. RCEMIP model output is publicly available at http://hdl.handle.net/21.14101/d4beee8e-6996-453e-bbd1-ff53b6874c0e, and output from the SAM-P3 model runs is available from the corresponding author on request. The derived statistics needed to reproduce the figures in this paper, as well as output from the SAM-P3 model runs, is available at https://doi.org/10.5281/zenodo.10640752 (ref. 61).

Code availability

The code used for the climate sensitivity calculations is available from the WCRP at https://zenodo.org/record/3945276#.ZFvtAOzMJ8Z (ref. 62). The code needed to generate the figures in this paper is available at https://doi.org/10.5281/zenodo.10640752 (ref. 61).

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Acknowledgements

We thank C. Stauffer for processing and sharing RCEMIP data, L. Hahn for helpful feedback on this manuscript and J. Deutloff for helpful conversations about the treatment of cloud overlap. We acknowledge the many scientists who provided simulations for RCEMIP and the German Climate Computing Center (DKRZ) for hosting the standardized RCEMIP data. This work was supported by NASA FINESST grant 80NSSC20K1613 (A.B.S. and D.L.H.) and NSF grant AGS-2124496 (D.L.H.).

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Authors and Affiliations

  1. Department of Atmospheric Sciences, University of Washington, Seattle, WA, USA

    Adam B. Sokol & Dennis L. Hartmann

  2. Department of Geosciences, University of Oslo, Oslo, Norway

    Casey J. Wall

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Contributions

A.B.S. conceived the project, conducted the analysis, generated the figures and wrote the manuscript. C.J.W. ran the equilibrium climate sensitivity code and provided interpretation. D.L.H. interpreted results, contributed to manuscript revision and supervised all aspects of the project.

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Correspondence to Adam B. Sokol.

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Nature Geoscience thanks Brian Soden, Claudia Stubenrauch and Aiko Voigt for their contribution to the peer review of this work. Primary Handling Editor: Tom Richardson, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Relationship between IWP and optical depth.

Mean ice cloud optical depth τ as a function of IWP in the three combined radar-lidar satellite retrievals.

Extended Data Fig. 2 Observed cloud macrophysical properties in IWP space.

Cloud fraction composited by IWP and height in DARDAR v2.1.1. The red line shows the mean cloud top height at each IWP, with red shading between the 10th and 90th cloud top height percentiles. Following ref. 50, cloudy volumes are defined as those with nonzero ice water content and visible extinction coefficient exceeding 0.125 km−1. Data are for 150-180∘E and 12∘S-12∘N for the 2009 calendar year.

Extended Data Fig. 3 Modeled cloud macrophysical properties in IWP space.

Cloud fraction composited by pressure and IWP for the final 15 days of the RCEMIP simulations with Ts = 300 K. Grid boxes are considered cloudy if the total condensate mixing ratio exceeds 10−5 kg/kg. Red lines show the median cloud top pressure (CTP) of ice clouds, with red shading between the 10th and 90th CTP percentiles. The CTP statistics do not extend all the way down to IWP=1 g/m2 because such low IWPs can only result from ice mixing ratios below the cloudiness threshold.

Extended Data Fig. 4 Mean cloud radiative effects across the RCEMIP ensemble.

Box plots of Cice, Cthick, and Cthin in the CRM ensemble for each value of Ts. Boxes show Q1-Q3, the horizontal lines within each box show medians, red triangles show means, and each dot shows an individual model (n = 11). Outliers are defined as points that differ from Q1 or Q3 by more than 1.5x the interquartile range.

Extended Data Fig. 5 Results for individual RCEMIP models.

(a) Absolute and (c) fractional changes in f between 295 and 305 K, normalized by ΔTs. (b) C at 295 K and (d) ΔfC between 295 and 305 K. Thin lines show individual models. Heavy black lines show multimodel means. Heavy red lines show the ensemble standard deviation and are plotted on a different vertical axis shown in red on the right side of each plot.

Extended Data Fig. 6 Cloud fraction statistics for individual models.

Cloud fraction as a function of Ts for each model in the CRM ensemble. Panels are shown for different portions of the IWP continuum. The bottom-right shows the ratio of thin to thick ice clouds.

Extended Data Fig. 7 Correlation coefficients between IWP-resolved and domain-averaged quantities.

Correlation coefficients are shown for various quantities. Black: absolute changes in f (IWP) and fice. Green: fractional changes in f (IWP) and fice. Pink: ΔfC (IWP) and ΔfCice.

Extended Data Fig. 8 Relationships between changes in cloud fraction metrics and various radiative feedback components.

Changes in fice, fthick, and fthin versus ΔfCice and its area- and opacity-related components. ΔfCice plotted against a, Δfice; b, Δfthick; and c, Δfthin. The area component of ΔfCice plotted against d, Δfice; e, Δfthick; and f, Δfthin. The opacity component of ΔfCice plotted against g, Δfice; h, Δfthick; and i, Δfthin. Correlation coefficients are shown for each relationship and are marked with an asterisk if not statistically different from zero, that is if the 95% confidence interval includes zero (n = 11). All values are normalized by ΔTs.

Extended Data Fig. 9 Sensitivity of the ECS PDF to feedback uncertainty.

The test values for the anvil area and opacity feedback are displayed as N(x, y), which represents a Gaussian with mean x and standard deviation y. The three RCEMIP-informed feedback estimates use the same mean value but different standard deviations, which, in increasing order, correspond to the standard deviation of the RCEMIP models, the maximum absolute difference between a single model and multimodel mean, and the original standard deviation assessed by the WCRP.

Extended Data Table 1 Statistics for the posterior PDFs of equilibrium climate sensitivity
Full size table

Supplementary information

Supplementary Information

Supplementary Discussions 1 and 2, Figs. 1–4, and Tables 1 and 2.

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Sokol, A.B., Wall, C.J. & Hartmann, D.L. Greater climate sensitivity implied by anvil cloud thinning. Nat. Geosci. (2024). https://doi.org/10.1038/s41561-024-01420-6

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