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Possible climate transitions from breakup of stratocumulus decks under greenhouse warming


Stratocumulus clouds cover 20% of the low-latitude oceans and are especially prevalent in the subtropics. They cool the Earth by shading large portions of its surface from sunlight. However, as their dynamical scales are too small to be resolvable in global climate models, predictions of their response to greenhouse warming have remained uncertain. Here we report how stratocumulus decks respond to greenhouse warming in large-eddy simulations that explicitly resolve cloud dynamics in a representative subtropical region. In the simulations, stratocumulus decks become unstable and break up into scattered clouds when CO2 levels rise above 1,200 ppm. In addition to the warming from rising CO2 levels, this instability triggers a surface warming of about 8 K globally and 10 K in the subtropics. Once the stratocumulus decks have broken up, they only re-form once CO2 concentrations drop substantially below the level at which the instability first occurred. Climate transitions that arise from this instability may have contributed importantly to hothouse climates and abrupt climate changes in the geological past. Such transitions to a much warmer climate may also occur in the future if CO2 levels continue to rise.

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Fig. 1: Simulated subtropical clouds in the present climate (400 ppm CO2), at higher CO2 (1,200 ppm) and after stratocumulus breakup (1,300 ppm).
Fig. 2: Clouds in the subtropical LES domain at different CO2 levels.
Fig. 3: Stratocumulus instability and hysteresis with fixed large-scale subsidence.
Fig. 4: Stratocumulus instability and hysteresis with weakening large-scale subsidence.

Code availability

The source code for the simulations is available at

Data availability

The authors declare that the data supporting the findings of this study are available within the article and its Supplementary Information files. The raw data in the figures are available from the corresponding author upon request.


  1. 1.

    Wood, R. Stratocumulus clouds. Mon. Weather Rev. 140, 2373–2423 (2012).

    Article  Google Scholar 

  2. 2.

    Bretherton, C. S. & Wyant, M. C. Moisture transport, lower-tropospheric stability, and decoupling of cloud-topped boundary layers. J. Atmos. Sci. 54, 148–167 (1997).

    Article  Google Scholar 

  3. 3.

    Stevens, B. et al. On entrainment rates in nocturnal marine stratocumulus. Q. J. R. Meteorol. Soc. 129, 3469–3493 (2003).

    Article  Google Scholar 

  4. 4.

    Stevens, B. et al. Evaluation of large-eddy simulations via observations of nocturnal marine stratocumulus. Mon. Weather Rev. 133, 1443–1462 (2005).

    Article  Google Scholar 

  5. 5.

    Stevens, B. et al. On the structure of the lower troposphere in the summertime stratocumulus regime of the northeast Pacific. Mon. Weather Rev. 135, 985–1005 (2007).

    Article  Google Scholar 

  6. 6.

    Mellado, J. P. Cloud-top entrainment in stratocumulus clouds. Annu. Rev. Fluid. Mech. 49, 145–169 (2016).

    Article  Google Scholar 

  7. 7.

    Schneider, T. et al. Climate goals and computing the future of clouds. Nat. Clim. Change 7, 3–5 (2017).

    Article  Google Scholar 

  8. 8.

    Nam, C., Bony, S., Dufresne, J.-L. & Chepfer, H. The ‘too few, too bright’ tropical low-cloud problem in CMIP5 models. Geophys. Res. Lett. 39, L21801 (2012).

    Article  Google Scholar 

  9. 9.

    Lin, J.-L., Qian, T. & Shinoda, T. Stratocumulus clouds in Southeastern Pacific simulated by eight CMIP5–CFMIP global climate models. J. Clim. 27, 3000–3022 (2014).

    Article  Google Scholar 

  10. 10.

    Boucher, O. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) Ch. 7 (IPCC, Cambridge Univ. Press, 2013).

  11. 11.

    Eastman, R., Warren, S. G. & Hahn, C. J. Variations in cloud cover and cloud types over the ocean from surface observations, 1954–2008. J. Clim. 24, 5914–5934 (2011).

    Article  Google Scholar 

  12. 12.

    Vial, J., Dufresne, J.-L. & Bony, S. On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates. Clim. Dyn. 41, 3339–3362 (2013).

    Article  Google Scholar 

  13. 13.

    Webb, M. J., Lambert, F. H. & Gregory, J. M. Origins of differences in climate sensitivity, forcing and feedback in climate models. Clim. Dyn. 40, 677–707 (2013).

    Article  Google Scholar 

  14. 14.

    Seneviratne, S. I., Donat, M. G., Pitman, A. J., Knutti, R. & Wilby, R. L. Allowable CO2 emissions based on regional and impact-related climate targets. Nature 529, 477–483 (2016).

    Article  Google Scholar 

  15. 15.

    Blossey, P. N. et al. Marine low cloud sensitivity to an idealized climate change: the CGILS LES intercomparison. J. Adv. Model. Earth Syst. 5, 234–258 (2013).

    Article  Google Scholar 

  16. 16.

    Zhang, M. et al. CGILS: results from the first phase of an international project to understand the physical mechanisms of low cloud feedbacks in general circulation models. J. Adv. Model. Earth Syst. 5, 826–842 (2013).

    Article  Google Scholar 

  17. 17.

    Bretherton, C. S., Blossey, P. N. & Jones, C. R. Mechanisms of marine low cloud sensitivity to idealized climate perturbations: a single-LES exploration extending the CGILS cases. J. Adv. Model. Earth Syst. 5, 316–337 (2013).

    Article  Google Scholar 

  18. 18.

    Bretherton, C. S. & Blossey, P. N. Low cloud reduction in a greenhouse-warmed climate: results from Lagrangian LES of a subtropical marine cloudiness transition. J. Adv. Model. Earth Syst. 6, 91–114 (2014).

    Article  Google Scholar 

  19. 19.

    Bretherton, C. S. Insights into low-latitude cloud feedbacks from high-resolution models. Phil. Trans. R. Soc. Lond. A 373, 20140415 (2015).

    Article  Google Scholar 

  20. 20.

    Pressel, K. G., Kaul, C. M., Schneider, T., Tan, Z. & Mishra, S. Large-eddy simulation in an anelastic framework with closed water and entropy balances. J. Adv. Model. Earth Syst. 7, 1425–1456 (2015).

    Article  Google Scholar 

  21. 21.

    Pressel, K. G., Mishra, S., Schneider, T., Kaul, C. M. & Tan, Z. Numerics and subgrid-scale modeling in large eddy simulations of stratocumulus clouds. J. Adv. Model. Earth Syst. 9, 1342–1365 (2017).

    Article  Google Scholar 

  22. 22.

    Klein, S. A. & Hartmann, D. L. The seasonal cycle of low stratiform clouds. J. Clim. 6, 1587–1606 (1993).

    Article  Google Scholar 

  23. 23.

    Tan, Z., Schneider, T., Teixeira, J. & Pressel, K. G. Large-eddy simulation of subtropical cloud-topped boundary layers: 1. A forcing framework with closed surface energy balance. J. Adv. Model. Earth Syst. 8, 1565–1585 (2016).

    Article  Google Scholar 

  24. 24.

    Tan, Z., Schneider, T., Teixeira, J. & Pressel, K. G. Large-eddy simulation of subtropical cloud-topped boundary layers: 2. Cloud response to climate change. J. Adv. Model. Earth Syst. 9, 19–38 (2017).

    Article  Google Scholar 

  25. 25.

    Pierrehumbert, R. T. Thermostats, radiator fins, and the local runaway greenhouse. J. Atmos. Sci. 52, 1784–1806 (1995).

    Article  Google Scholar 

  26. 26.

    Sobel, A. H., Nilsson, J. & Polvani, L. M. The weak temperature gradient approximation and balanced tropical moisture waves. J. Atmos. Sci. 58, 3650–3665 (2001).

    Article  Google Scholar 

  27. 27.

    Flato, G. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 741–853 (IPCC, Cambridge Univ. Press, 2013).

  28. 28.

    Loeb, N. G. et al. Clouds and the earth’s radiant energy system (CERES) energy balanced and filled (EBAF) top-of-atmosphere (TOA) edition-4.0 data product. J. Clim. 31, 895–918 (2018).

    Article  Google Scholar 

  29. 29.

    Christensen, M. W., Carrio, G. G., Stephens, G. L. & Cotton, W. R. Radiative impacts of free-tropospheric clouds on the properties of marine stratocumulus. J. Atmos. Sci. 70, 3102–3118 (2013).

    Article  Google Scholar 

  30. 30.

    Randall, D. A. & Suarez, M. J. On the dynamics of stratocumulus formation and dissipation. J. Atmos. Sci. 41, 3052–3057 (1984).

    Article  Google Scholar 

  31. 31.

    Bretherton, C. S., Uchida, J. & Blossey, P. N. Slow manifolds and multiple equilibria in stratocumulus-capped boundary layers. J. Adv. Model. Earth Syst. 2, 14 (2010).

    Article  Google Scholar 

  32. 32.

    Held, I. M. & Soden, B. J. Robust responses of the hydrological cycle to global warming. J. Clim. 19, 5686–5699 (2006).

    Article  Google Scholar 

  33. 33.

    Vecchi, G. A. & Soden, B. J. Global warming and the weakening of the tropical circulation. J. Clim. 20, 4316–4340 (2007).

    Article  Google Scholar 

  34. 34.

    Scheffer, M. et al. Early-warning signals for critical transitions. Nature 461, 53–59 (2009).

    Article  Google Scholar 

  35. 35.

    Huber, M. & Caballero, R. The early Eocene equable climate problem revisited. Clim. Past 7, 603–633 (2011).

    Article  Google Scholar 

  36. 36.

    Caballero, R. & Huber, M. State-dependent climate sensitivity in past warm climates and its implications for future climate projections. Proc. Natl Acad. Sci. USA 110, 14162–14167 (2013).

    Article  Google Scholar 

  37. 37.

    Kopp, R. E. et al. in Climate Science Special Report: Fourth National Climate Assessment Vol. I (eds Wuebbles, D. J. et al.) 411–429 (US Global Change Research Program, 2017).

  38. 38.

    Cramwinckel, M. J. et al. Synchronous tropical and deep-ocean temperature evolution in the Eocene. Nature 559, 382–386 (2018).

    Article  Google Scholar 

  39. 39.

    Anagnostou, E. et al. Changing atmospheric CO2 concentration was the primary driver of early Cenozoic climate. Nature 533, 380–384 (2016).

    Article  Google Scholar 

  40. 40.

    Liu, Z. et al. Global cooling during the Eocene–Oligocene climate transition. Science 323, 1187–1190 (2009).

    Article  Google Scholar 

  41. 41.

    Meinshausen, M. et al. The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Clim. Change 109, 213–241 (2011).

    Article  Google Scholar 

  42. 42.

    Jiang, G.-S. & Shu, C.-W. Efficient implementation of weighted ENO schemes. J. Comp. Phys. 126, 202–228 (1996).

    Article  Google Scholar 

  43. 43.

    Stevens, B. et al. Dynamics and chemistry of marine stratocumulus–DYCOMS-II. Bull. Am. Meteorol. Soc. 84, 579–593 (2003).

    Article  Google Scholar 

  44. 44.

    Matheou, G. Turbulence structure in a stratocumulus cloud. Atmosphere 9, 392 (2018).

    Article  Google Scholar 

  45. 45.

    Mellado, J. P., Bretherton, C. S., Stevens, B. & Wyant, M. C. DNS and LES for simulating stratocumulus: better together. J. Adv. Model. Earth Syst. 10, 1421–1438 (2018).

    Article  Google Scholar 

  46. 46.

    Shu, C.-W. & Osher, S. Efficient implementation of essentially non-oscillatory shock-capturing schemes. J. Comp. Phys. 77, 439–471 (1988).

    Article  Google Scholar 

  47. 47.

    Jones, C. R., Bretherton, C. S. & Pritchard, M. S. Mean-state acceleration of cloud-resolving models and large eddy simulations. J. Adv. Model. Earth Syst. 7, 1643–1660 (2015).

    Article  Google Scholar 

  48. 48.

    Iacono, M. J. et al. Radiative forcing by long-lived greenhouse gases: calculations with the AER radiative transfer models. J. Geophys. Res. 113, D13103 (2008).

    Article  Google Scholar 

  49. 49.

    Byun, D. W. On the analytical solutions of flux-profile relationships for the atmospheric surface layer. J. Appl. Meteorol. 29, 652–657 (1990).

    Article  Google Scholar 

  50. 50.

    Manabe, S. & Wetherald, R. T. Thermal equilibrium of the atmosphere with a given distribution of relative humidity. J. Atmos. Sci. 24, 241–259 (1967).

    Article  Google Scholar 

  51. 51.

    Akmaev, R. A. A direct algorithm for convective adjustment of the vertical temperature profile for an arbitrary critical lapse rate. Mon. Weather Rev. 119, 2499–2504 (1991).

    Article  Google Scholar 

  52. 52.

    Held, I. M. & Soden, B. J. Water vapor feedback and global warming. Annu. Rev. Energy Environ. 25, 441–475 (2000).

    Article  Google Scholar 

  53. 53.

    O’Gorman, P. A. & Schneider, T. The hydrological cycle over a wide range of climates simulated with an idealized GCM. J. Clim. 21, 3815–3832 (2008).

    Article  Google Scholar 

  54. 54.

    Schneider, T., O’Gorman, P. A. & Levine, X. J. Water vapor and the dynamics of climate changes. Rev. Geophys. 48, RG3001 (2010).

    Article  Google Scholar 

  55. 55.

    Sherwood, S. C. et al. Relative humidity changes in a warmer climate. J. Geophys. Res. 115, D09104 (2010).

    Article  Google Scholar 

  56. 56.

    Betts, A. K. & Ridgway, W. L. Climatic equilibrium of the atmospheric convective boundary layer over a tropical ocean. J. Atmos. Sci. 46, 2621–2641 (1989).

    Article  Google Scholar 

  57. 57.

    Trenberth, K. E. & Stepaniak, D. P. Seamless poleward atmospheric energy transports and implications for the Hadley circulation. J. Clim. 16, 3706–3722 (2003).

    Article  Google Scholar 

  58. 58.

    Kaul, C. M., Teixeira, J. & Suzuki, K. Sensitivities in large-eddy simulations of mixed-phase Arctic stratocumulus clouds using a simple microphysics approach. Mon. Weather Rev. 143, 4393–4421 (2015).

    Article  Google Scholar 

  59. 59.

    Straka, J. M. Cloud and Precipitation Microphysics: Principles and Parameterizations Ch. 4 (Cambridge Univ. Press, Cambridge, 2009).

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This research was supported by C. Trimble. The computations were performed on ETH Zurich’s Euler cluster and on Caltech’s High Performance Cluster, which is partially supported by a grant from the Gordon and Betty Moore Foundation. We thank M. Hell for assistance with the figures. Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.

Author information




T.S. designed the study, analysed results, and wrote the paper. C.M.K. and K.G.P. implemented the study design numerically, conducted the LES, analysed and visualized the results, and contributed to the writing.

Corresponding author

Correspondence to Tapio Schneider.

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Supplementary information

Supplementary Information

Supplementary Figures

Supplementary Movie

Time evolution of the stratocumulus instability. The shading shows the liquid water path in the subtropical LES domain in the 1300 ppm simulation between days 255 and 275, which is during the time of the stratocumulus breakup (Fig. 1). Blue for zero LWP, and the colorscale saturates white at a LWP of 300 μm. The time series at the bottom show the cloud fraction (blue) and SST (red) in the LES domain. The breakup of the stratocumulus clouds is more rapid than it would be in nature because of the unrealistically small thermal inertia of the underlying slab ocean.

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Schneider, T., Kaul, C.M. & Pressel, K.G. Possible climate transitions from breakup of stratocumulus decks under greenhouse warming. Nat. Geosci. 12, 163–167 (2019).

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