Articles | Volume 15, issue 2
https://doi.org/10.5194/esd-15-215-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-15-215-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Sea-ice thermodynamics can determine waterbelt scenarios for Snowball Earth
Johannes Hörner
CORRESPONDING AUTHOR
Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria
Aiko Voigt
Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria
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Geological evidence indicate persistent tropical sea-ice cover in the deep past, often called Snowball Earth. Using a climate model, we show here that clouds substantially cool down the tropics and facilitate the advance of sea-ice into lower latitudes. We identify a critical threshold temperature of 0 °C from where cooling down the Earth is accelerated. This value can be used as a constraint on Earth's sensitivity to CO2, as recent cold paleoclimates never entered Snowball Earth.
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Clouds absorb and re-emit infrared radiation from Earth's surface and absorb and reflect incoming solar radiation. As a result, they change atmospheric temperature gradients that drive large-scale circulation. To better simulate this circulation, we study how the radiative heating and cooling from clouds depends on model settings like grid spacing; whether we describe convection approximately or exactly; and the level of detail used to describe small-scale processes, or microphysics, in clouds.
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Clouds composed of ice crystals are key when evaluating atmospheric radiation. The morphology of the crystals found in clouds is not clear yet, and even less clear is the impact on cloud heating rate, which is essential to describe precipitation and wind patterns. This motivated us to study how the heating rate behaves under a variety of ice complexity and environmental conditions, finding that increasing complexity in high and dense clouds weakens the heating rate.
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Geological evidence indicate persistent tropical sea-ice cover in the deep past, often called Snowball Earth. Using a climate model, we show here that clouds substantially cool down the tropics and facilitate the advance of sea-ice into lower latitudes. We identify a critical threshold temperature of 0 °C from where cooling down the Earth is accelerated. This value can be used as a constraint on Earth's sensitivity to CO2, as recent cold paleoclimates never entered Snowball Earth.
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The warm conveyor belt (WCB), which is a stream of coherently rising air parcels, is an important feature of extratropical cyclones. This work presents the impact of model grid spacing on simulation of cloud diabatic processes in the WCB of a North Atlantic cyclone. We find that the refinement of the model grid systematically enhances the dynamical properties and heat releasing processes within the WCB. However, this pattern does not have a strong impact on the strength of associated cyclones.
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In climate science, it is helpful to identify coherent objects, for example, those formed by clouds. However, many models now use unstructured grids, which makes it harder to identify coherent objects. We present a new method that solves this problem by moving model data from an unstructured triangular grid to a structured cubical grid. We implement the method in an open-source Python package and show that the method is ready to be applied to climate model data.
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Related subject area
Topics: Climate dynamics and variability | Interactions: Cryosphere/atmosphere interactions | Methods: Earth system and climate modeling
Ensemble design for seasonal climate predictions: Studying extreme Arctic sea ice lows with a rare event algorithm
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An obstacle in studying climate extremes is the lack of robust statistics. We use a rare event algorithm to gather robust statistics on extreme Arctic sea ice lows with probabilities below 0.1 % and to study drivers of events with amplitudes larger than observed in 2012. The work highlights that the most extreme sea ice reductions result from the combined effects of preconditioning and weather variability, emphasizing the need for thoughtful ensemble design when turning to real applications.
Cited articles
Abbot, D. S., Eisenman, I., and Pierrehumbert, R. T.: The Importance of Ice Vertical Resolution for Snowball Climate and Deglaciation, J. Climate, 23, 6100–6109, https://doi.org/10.1175/2010JCLI3693.1, 2010. a, b
Abbot, D. S., Voigt, A., Branson, M., Pierrehumbert, R. T., Pollard, D., Hir, G. L., and Koll, D. D. B.: Clouds and Snowball Earth deglaciation, Geophys. Res. Lett., 39, L20711, https://doi.org/10.1029/2012GL052861, 2012. a
Bitz, C. M. and Lipscomb, W. H.: An energy-conserving thermodynamic model of sea ice, J. Geophys. Res.-Oceans, 104, 15669–15677, https://doi.org/10.1029/1999JC900100, 1999. a
Brunetti, M., Kasparian, J., and Vérard, C.: Co-existing climate attractors in a coupled aquaplanet, Clim. Dynam., 53, 6293–6308, https://doi.org/10.1007/s00382-019-04926-7, 2019. a, b
Dadic, R., Mullen, P. C., Schneebeli, M., Brandt, R. E., and Warren, S. G.: Effects of bubbles, cracks, and volcanic tephra on the spectral albedo of bare ice near the Transantarctic Mountains: Implications for sea glaciers on Snowball Earth, J. Geophys. Res.-Earth Surf., 118, 1658–1676, https://doi.org/10.1002/jgrf.20098, 2013. a, b
Giorgetta, M. A., Brokopf, R., Crueger, T., Esch, M., Fiedler, S., Helmert, J., Hohenegger, C., Kornblueh, L., Köhler, M., Manzini, E., Mauritsen, T., Nam, C., Raddatz, T., Rast, S., Reinert, D., Sakradzija, M., Schmidt, H., Schneck, R., Schnur, R., Silvers, L., Wan, H., Zängl, G., and Stevens, B.: ICON-A, the Atmosphere Component of the ICON Earth System Model: I. Model Description, J. Adv. Model. Earth Sy., 10, 1613–1637, https://doi.org/10.1029/2017MS001242, 2018. a, b
Gough, D. O.: Solar Interior Structure and Luminosity Variations, Sol. Phys., 74, 21–34, https://doi.org/10.1007/978-94-010-9633-1_4, 1981. a
Hoffman, P. and Schrag, D.: The snowball Earth hypothesis: testing the limits of global change, Terra Nova, 14, 129–155, https://doi.org/10.1046/J.1365-3121.2002.00408.X, 2002. a
Hoffman, P. F., Abbot, D. S., Ashkenazy, Y., Benn, D. I., Brocks, J. J., Cohen, P. A., Cox, G. M., Creveling, J. R., Donnadieu, Y., Erwin, D. H., Fairchild, I. J., Ferreira, D., Goodman, J. C., Halverson, G. P., Jansen, M. F., Hir, G. L., Love, G. D., Macdonald, F. A., Maloof, A. C., Partin, C. A., Ramstein, G., Rose, B. E. J., Rose, C. V., Sadler, P. M., Tziperman, E., Voigt, A., and Warren, S. G.: Snowball Earth climate dynamics and Cryogenian geology-geobiology, Sci. Adv., 3, e1600983, https://doi.org/10.1126/sciadv.1600983, 2017. a
Hörner, J. and Voigt, A.: Sea-ice thermodynamics can determine waterbelt scenarios for Snowball Earth, University of Vienna [code and data set], https://doi.org/10.25365/phaidra.429, 2024. a
Hyde, W. T., Crowley, T. J., Baum, S. K., and Peltier, W. R.: Neoproterozoic “snowball Earth” simulations with a coupled climate/ice-sheet model, Nature, 405, 425–429, https://doi.org/10.1038/35013005, 2000. a
Kirschvink, J. L.: Late Proterozoic Low-Latitude Global Glaciation: the Snowball Earth, in: The Proterozoic Biosphere: A Multidisciplinary Study, edited by: Schopf, J. W. and Klein, C., pp. 51–52, Cambridge University Press, New York, ISBN 978-0-521-36615-1, 1992. a
Klemp, J. B., Dudhia, J., and Hassiotis, A. D.: An Upper Gravity-Wave Absorbing Layer for NWP Applications, Mon. Weather Rev., 136, 3987–4004, https://doi.org/10.1175/2008MWR2596.1, 2008. a
Liu, Y., Peltier, W. R., Yang, J., and Hu, Y.: Influence of Surface Topography on the Critical Carbon Dioxide Level Required for the Formation of a Modern Snowball Earth, J. Climate, 31, 8463–8479, https://doi.org/10.1175/JCLI-D-17-0821.1, 2018. a
Marotzke, J. and Botzet, M.: Present-day and ice-covered equilibrium states in a comprehensive climate model, Geophys. Res. Lett., 34, L16704, https://doi.org/10.1029/2006GL028880, 2007. a
Marshall, J., Adcroft, A., Campin, J.-M., Hill, C., and White, A.: Atmosphere–Ocean Modeling Exploiting Fluid Isomorphisms, Mon. Weather Rev., 132, 2882–2894, https://doi.org/10.1175/MWR2835.1, 2004. a
Pierrehumbert, R. T., Abbot, D. S., Voigt, A., and Koll, D.: Climate of the Neoproterozoic, Annu. Rev. Earth Pl. Sc., 39, 417–460, https://doi.org/10.1146/annurev-earth-040809-152447, 2011. a
Ragon, C., Lembo, V., Lucarini, V., Vérard, C., Kasparian, J., and Brunetti, M.: Robustness of Competing Climatic States, J. Climate, 35, 2769–2784, https://doi.org/10.1175/JCLI-D-21-0148.1, 2022. a, b
Ramme, L. and Marotzke, J.: Climate and ocean circulation in the aftermath of a Marinoan snowball Earth, Clim. Past, 18, 759–774, https://doi.org/10.5194/cp-18-759-2022, 2022. a, b
Rose, B. E. J.: Stable “Waterbelt” climates controlled by tropical ocean heat transport: A nonlinear coupled climate mechanism of relevance to Snowball Earth, J. Geophys. Res.-Atmos., 120, 1404–1423, https://doi.org/10.1002/2014JD022659, 2015. a, b, c, d
Semtner, A. J.: A Model for the Thermodynamic Growth of Sea Ice in Numerical Investigations of Climate, J. Phys. Oceanogr., 6, 379–389, https://doi.org/10.1175/1520-0485(1976)006<0379:AMFTTG>2.0.CO;2, 1976. a, b
Semtner, A. J.: On modelling the seasonal thermodynamic cycle of sea ice in studies of climatic change, Clim. Change, 6, 27–37, https://doi.org/10.1007/BF00141666, 1984. a
Voigt, A. and Abbot, D. S.: Sea-ice dynamics strongly promote Snowball Earth initiation and destabilize tropical sea-ice margins, Clim. Past, 8, 2079–2092, https://doi.org/10.5194/cp-8-2079-2012, 2012. a, b
Voigt, A., Abbot, D. S., Pierrehumbert, R. T., and Marotzke, J.: Initiation of a Marinoan Snowball Earth in a state-of-the-art atmosphere-ocean general circulation model, Clim. Past, 7, 249–263, https://doi.org/10.5194/cp-7-249-2011, 2011. a
Warren, S. G., Brandt, R. E., Grenfell, T. C., and McKay, C. P.: Snowball Earth: Ice thickness on the tropical ocean, J. Geophys. Res.-Oceans, 107, 3167, https://doi.org/10.1029/2001JC001123, 2002. a
Webster, M. A. and Warren, S. G.: Regional Geoengineering Using Tiny Glass Bubbles Would Accelerate the Loss of Arctic Sea Ice, Earth's Future, 10, e2022EF002815, https://doi.org/10.1029/2022EF002815, 2022. a
Winton, M.: A Reformulated Three-Layer Sea Ice Model, J. Atmos. Ocean. Tech., 17, 525–531, https://doi.org/10.1175/1520-0426(2000)017<0525:ARTLSI>2.0.CO;2, 2000. a, b
Wolf, E. T., Shields, A. L., Kopparapu, R. K., Haqq-Misra, J., and Toon, O. B.: Constraints on Climate and Habitability for Earth-like Exoplanets Determined from a General Circulation Model, ApJ, 837, 107, https://doi.org/10.3847/1538-4357/aa5ffc, 2017. a
Yang, J., Peltier, W. R., and Hu, Y.: The Initiation of Modern “Soft Snowball” and “Hard Snowball” Climates in CCSM3. Part I: The Influences of Solar Luminosity, CO 2 Concentration, and the Sea Ice/Snow Albedo Parameterization, J. Climate, 25, 2711–2736, https://doi.org/10.1175/JCLI-D-11-00189.1, 2012a. a, b, c, d
Yang, J., Peltier, W. R., and Hu, Y.: The Initiation of Modern “Soft Snowball” and “Hard Snowball” Climates in CCSM3. Part II: Climate Dynamic Feedbacks, J. Climate, 25, 2737–2754, https://doi.org/10.1175/JCLI-D-11-00190.1, 2012b. a, b, c, d
Zhu, F. and Rose, B. E. J.: Multiple Equilibria in a Coupled Climate-Carbon Model, J. Climate, 36, 547–564, https://doi.org/10.1175/JCLI-D-21-0984.1, 2022. a
Short summary
Snowball Earth refers to a climate in the deep past of the Earth where the whole planet was covered in ice. Waterbelt states, where a narrow region of open water remains at the Equator, have been discussed as an alternative scenario, which might explain how life was able to survive these periods. Here, we demonstrate how waterbelt states are influenced by the thermodynamical sea-ice model used. The sea-ice model modulates snow on ice, ice albedo and ultimately the stability of waterbelt states.
Snowball Earth refers to a climate in the deep past of the Earth where the whole planet was...
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