Articles | Volume 18, issue 4
https://doi.org/10.5194/cp-18-759-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/cp-18-759-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Climate and ocean circulation in the aftermath of a Marinoan snowball Earth
Lennart Ramme
CORRESPONDING AUTHOR
Max Planck Institute for Meteorology, Hamburg, Germany
International Max Planck Research School on Earth System Modelling, Hamburg, Germany
Jochem Marotzke
Max Planck Institute for Meteorology, Hamburg, Germany
Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany
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Cited articles
Abbot, D. S. and Pierrehumbert, R. T.: Mudball: Surface dust and snowball Earth
deglaciation, J. Geophys. Res.-Atmos., 115, D03104, https://doi.org/10.1029/2009JD012007, 2010. a
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., Li, D., Hir, G. L., Pierrehumbert, R. T., Branson, M.,
Pollard, D., and B. Koll, D. D.: Robust elements of Snowball Earth
atmospheric circulation and oases for life, J. Geophys. Res.-Atmos., 118,
6017–6027, https://doi.org/10.1002/jgrd.50540, 2013. a, b, c
Allen, P. A. and Hoffman, P. F.: Extreme winds and waves in the aftermath of a Neoproterozoic glaciation, Nature, 433, 123–127, https://doi.org/10.1038/nature03176, 2005. a
Ashkenazy, Y., Gildor, H., Losch, M., Macdonald, F. A., Schrag, D. P., and
Tziperman, E.: Dynamics of a Snowball Earth ocean, Nature, 495, 90–93,
https://doi.org/10.1038/nature11894, 2013. a, b
Bao, H., Lyons, J., and Zhou, C.: Triple oxygen isotope evidence for elevated
CO2 levels after a Neoproterozoic glaciation, Nature, 453, 504–506,
https://doi.org/10.1038/nature06959, 2008. a, b
Benn, D. I., Le Hir, G., Bao, H., Donnadieu, Y., Dumas, C., Fleming, E. J.,
Hambrey, M. J., McMillan, E. A., Petronis, M. S., Ramstein, G., Stevenson, Carl, T. E., Wynn, P. M., and Fairchild, I. J.:
Orbitally forced ice sheet fluctuations during the Marinoan Snowball Earth
glaciation, Nat. Geosci., 8, 704–707, https://doi.org/10.1038/ngeo2502, 2015. a, b, c
Brocks, J. J., Jarrett, A. J., Sirantoine, E., Hallmann, C., Hoshino, Y., and
Liyanage, T.: The rise of algae in Cryogenian oceans and the emergence of
animals, Nature, 548, 578–581, https://doi.org/10.1038/nature23457, 2017. a
Bryan, K. and Cox, M. D.: The circulation of the world ocean: a numerical
study. Part I, a homogeneous model, J. Phys. Oceanogr., 2, 319–335,
https://doi.org/10.1175/1520-0485(1972)002<0319:TCOTWO>2.0.CO;2, 1972. a
Calver, C., Crowley, J., Wingate, M., Evans, D., Raub, T., and Schmitz, M.:
Globally synchronous Marinoan deglaciation indicated by U-Pb geochronology of
the Cottons Breccia, Tasmania, Australia, Geology, 41, 1127–1130,
https://doi.org/10.1130/G34568.1, 2013. a, b
Campin, J.-M., Marshall, J., and Ferreira, D.: Sea ice–ocean coupling using a
rescaled vertical coordinate z∗, Ocean Model., 24, 1–14,
https://doi.org/10.1016/j.ocemod.2008.05.005, 2008. a
Cariolle, D. and Teyssèdre, H.: A revised linear ozone photochemistry parameterization for use in transport and general circulation models: multi-annual simulations, Atmos. Chem. Phys., 7, 2183–2196, https://doi.org/10.5194/acp-7-2183-2007, 2007. a
Crueger, T., Giorgetta, M. A., Brokopf, R., Esch, M., Fiedler, S., Hohenegger,
C., Kornblueh, L., Mauritsen, T., Nam, C., Naumann, A. K., Peters, K., Rast, S., Roeckner, E., Sakradzija, M., Schmidt,
H., Vial, J., Vogel, R., and Stevens, B.: ICON-A,
The atmosphere component of the ICON Earth system model: II. Model
evaluation, J. Adv. Model. Earth. Sy., 10, 1638–1662,
https://doi.org/10.1029/2017MS001233, 2018. a
Dohrmann, M. and Wörheide, G.: Dating early animal evolution using
phylogenomic data, Sci. Rep., 7, 1–6, https://doi.org/10.1038/s41598-017-03791-w,
2017. a
Ferreira, D., Marshall, J., and Rose, B.: Climate determinism revisited:
Multiple equilibria in a complex climate model, J. Climate, 24, 992–1012,
https://doi.org/10.1175/2010JCLI3580.1, 2011. a
Fiorella, R. P. and Poulsen, C. J.: Dehumidification over tropical continents
reduces climate sensitivity and inhibits snowball Earth initiation, J.
Climate, 26, 9677–9695, https://doi.org/10.1175/JCLI-D-12-00820.1, 2013. a
Font, E., Nédélec, A., Trindade, R., and Moreau, C.: Fast or slow
melting of the Marinoan snowball Earth? The cap dolostone record,
Palaeogeogr. Palaeoclimatol. Palaeoecol., 295, 215–225,
https://doi.org/10.1016/j.palaeo.2010.05.039, 2010. a
Gent, P. R., Willebrand, J., McDougall, T. J., and McWilliams, J. C.:
Parameterizing eddy-induced tracer transports in ocean circulation models, J.
Phys. Oceanogr., 25, 463–474,
https://doi.org/10.1175/1520-0485(1995)025<0463:PEITTI>2.0.CO;2, 1995. a
Gernon, T., Hincks, T., Tyrrell, T., Rohling, E., and Palmer, M.: Snowball
Earth ocean chemistry driven by extensive ridge volcanism during Rodinia
breakup, Nat. Geosci., 9, 242–248, https://doi.org/10.1038/ngeo2632, 2016. a
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
Hanke, M., Redler, R., Holfeld, T., and Yastremsky, M.: YAC 1.2. 0: new aspects
for coupling software in Earth system modelling, Geosci. Model Dev., 9,
2755–2769, https://doi.org/10.5194/gmd-9-2755-2016, 2016. a
Hoffman, P. F.: Strange bedfellows: glacial diamictite and cap carbonate from
the Marinoan (635 Ma) glaciation in Namibia, Sedimentology, 58, 57–119,
https://doi.org/10.1111/j.1365-3091.2010.01206.x, 2011. a, b, c
Hoffman, P. F., Kaufman, A. J., Halverson, G. P., and Schrag, D. P.: A
Neoproterozoic snowball earth, Science, 281, 1342–1346,
https://doi.org/10.1126/science.281.5381.1342, 1998. a, b
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, b
Jungclaus, J. H., Lorenz, S. J., Schmidt, H., Brovkin, V., Brüggemann, N.,
Chegini, F., De-Vrese, P., Gayler, V., Giorgetta, M. A., Gutjahr, O., Haak,
H., Hagemann, S., Hanke, M., Ilyina, T., Korn, P., Kröger, J.,
Linardakis, L., Mehlmann, C., Mikolajewicz, U., Müller, W. A., Nabel, J.
E. M. S., Notz, D., Pohlmann, H., Putrasahan, D., Raddatz, T., Ramme, L.,
Redler, R., Reick, C. H., Riddick, T., Sam, T., Schneck, R., Schnur, R.,
Schupfner, M., von Storch, J.-S., Wachsmann, F., Wieners, K.-H., Ziemen, F.,
Stevens, B., Marotzke, J., and Claussen, M.: The ICON Earth System Model
Version 1.0, J. Adv. Model. Earth. Sy., https://doi.org/10.1029/2021MS002813, in press, 2022. a, b
Kasemann, S. A., Hawkesworth, C. J., Prave, A. R., Fallick, A. E., and Pearson,
P. N.: Boron and calcium isotope composition in Neoproterozoic carbonate
rocks from Namibia: evidence for extreme environmental change, Earth Planet.
Sci. Lett., 231, 73–86, https://doi.org/10.1016/j.epsl.2004.12.006, 2005. a, b, c
Kendall, B., Creaser, R. A., and Selby, D.: Re-Os geochronology of postglacial
black shales in Australia: Constraints on the timing of “Sturtian”
glaciation, Geology, 34, 729–732, https://doi.org/10.1130/G22775.1, 2006. a
Kennedy, M. J.: Stratigraphy, sedimentology, and isotopic geochemistry of
Australian Neoproterozoic postglacial cap dolostones; deglaciation, delta13C excursions, and carbonate precipitation, J. Sediment Res., 66, 1050–1064,
https://doi.org/10.2110/jsr.66.1050, 1996. a
Korn, P.: Formulation of an unstructured grid model for global ocean dynamics,
J. Comput. Phys., 339, 525–552, https://doi.org/10.1016/j.jcp.2017.03.009, 2017. a, b
Le Hir, G., Donnadieu, Y., Goddéris, Y., Pierrehumbert, R. T., Halverson,
G. P., Macouin, M., Nédélec, A., and Ramstein, G.: The snowball Earth
aftermath: Exploring the limits of continental weathering processes, Earth
Planet. Sci. Lett., 277, 453–463, https://doi.org/10.1016/j.epsl.2008.11.010,
2008a. a, b, c
Le Hir, G., Goddéris, Y., Donnadieu, Y., and Ramstein, G.: A geochemical modelling study of the evolution of the chemical composition of seawater linked to a ”snowball” glaciation, Biogeosciences, 5, 253–267, https://doi.org/10.5194/bg-5-253-2008, 2008b. a
Le Hir, G., Ramstein, G., Donnadieu, Y., and Goddéris, Y.: Scenario for the
evolution of atmospheric pCO2 during a snowball Earth, Geology, 36, 47–50,
https://doi.org/10.1130/G24124A.1, 2008c. a, b, c
Lewis, J., Weaver, A., and Eby, M.: Deglaciating the snowball Earth:
Sensitivity to surface albedo, Geophys. Res. Lett., 33, L23604,
https://doi.org/10.1029/2006GL027774, 2006. a
Li, Z.-X., Evans, D. A., and Halverson, G. P.: Neoproterozoic glaciations in a
revised global palaeogeography from the breakup of Rodinia to the assembly of
Gondwanaland, Sediment. Geol., 294, 219–232,
https://doi.org/10.1016/j.sedgeo.2013.05.016, 2013. a, b, c
Liu, C., Wang, Z., Raub, T. D., Macdonald, F. A., and Evans, D. A.:
Neoproterozoic cap-dolostone deposition in stratified glacial meltwater
plume, Earth Planet. Sci. Lett., 404, 22–32,
https://doi.org/10.1016/j.epsl.2014.06.039, 2014. a, b
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
Mauritsen, T., Bader, J., Becker, T., et al.: Developments in the
MPI-M Earth System Model version 1.2 (MPI-ESM1. 2) and its response to
increasing CO2, J. Adv. Model. Earth. Sy., 11, 998–1038,
https://doi.org/10.1029/2018MS001400, 2019. a
McDougall, T. J.: Neutral surfaces, J. Phys. Oceanogr., 17, 1950–1964,
https://doi.org/10.1175/1520-0485(1987)017<1950:NS>2.0.CO;2, 1987. a
Merdith, A. S., Collins, A. S., Williams, S. E., Pisarevsky, S., Foden, J. D.,
Archibald, D. B., Blades, M. L., Alessio, B. L., Armistead, S., Plavsa, D.,
Clark, C., and Müller, R. D.: A full-plate global reconstruction of the Neoproterozoic, Gondwana
Res., 50, 84–134, https://doi.org/10.1016/j.gr.2017.04.001, 2017. a, b, c
Poulsen, C. and Jacob, R.: Factors that inhibit snowball Earth simulation,
Paleoceanography, 19, PA4021, https://doi.org/10.1029/2004PA001056, 2004. a
Prave, A. R., Condon, D. J., Hoffmann, K. H., Tapster, S., and Fallick, A. E.:
Duration and nature of the end-Cryogenian (Marinoan) glaciation, Geology, 44,
631–634, https://doi.org/10.1130/G38089.1, 2016. a
Ramme, L.: Publication data for “Ramme and Marotzke: Climate
and Ocean Circulation in the Aftermath of a Marinoan Snowball
Earth”, DOKU at DKRZ [code], https://cera-www.dkrz.de/WDCC/ui/cerasearch/entry?acronym=DKRZ_LTA_033_ds00013, last access: 5 April 2022. a
Redi, M. H.: Oceanic isopycnal mixing by coordinate rotation, J. Phys.
Oceanogr., 12, 1154–1158,
https://doi.org/10.1175/1520-0485(1982)012<1154:OIMBCR>2.0.CO;2, 1982. a
Rothschild, L. J. and Mancinelli, R. L.: Life in extreme environments, Nature,
409, 1092–1101, https://doi.org/10.1038/35059215, 2001. a
Russell, J. L., Dixon, K. W., Gnanadesikan, A., Stouffer, R. J., and
Toggweiler, J.: The Southern Hemisphere westerlies in a warming world:
Propping open the door to the deep ocean, J. Climate, 19, 6382–6390,
https://doi.org/10.1175/JCLI3984.1, 2006. a
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
Shields, G. A.: Neoproterozoic cap carbonates: a critical appraisal of existing
models and the plumeworld hypothesis, Terra Nova, 17, 299–310,
https://doi.org/10.1111/j.1365-3121.2005.00638.x, 2005. a
Stevens, B., Giorgetta, M., Esch, M., Mauritsen, T.,
Crueger, T., Rast, S., Salzmann, M., Schmidt, H., Bader, J., Block, K., Brokopf, R., Fast, I., Kinne, S., Kornblueh, L.,
Lohmann, U., Pincus, R., Reichler, T., and Roeckner, E.: Atmospheric component of the MPI-M Earth system model: ECHAM6, J. Adv. Model. Earth Syst., 5, 146–172, Wiley Online Library, 2013. a
Thompson, D. W. and Solomon, S.: Interpretation of recent Southern Hemisphere
climate change, Science, 296, 895–899, https://doi.org/10.1126/science.1069270, 2002. a
Trindade, R., Font, E., D'Agrella-Filho, M., Nogueira, A., and Riccomini, C.:
Low-latitude and multiple geomagnetic reversals in the Neoproterozoic Puga
cap carbonate, Amazon craton, Terra Nova, 15, 441–446,
https://doi.org/10.1046/j.1365-3121.2003.00510.x, 2003.
a
Turner, E. C.: Possible poriferan body fossils in early Neoproterozoic
microbial reefs, Nature, 596, 1–5, https://doi.org/10.1038/s41586-021-03773-z, 2021. a
Tziperman, E., Abbot, D. S., Ashkenazy, Y., Gildor, H., Pollard, D., Schoof,
C. G., and Schrag, D. P.: Continental constriction and oceanic ice-cover
thickness in a Snowball-Earth scenario, J. Geophys. Res.-Oceans, 117, C05016,
https://doi.org/10.1029/2011JC007730, 2012. a
Voigt, A. and Marotzke, J.: The transition from the present-day climate to a
modern Snowball Earth, Clim. Dynam., 35, 887–905,
https://doi.org/10.1007/s00382-009-0633-5, 2010. a
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, b
Wolff, J.-O., Maier-Reimer, E., and Olbers, D. J.: Wind-driven flow over
topography in a zonal β-plane channel: A quasi-geostrophic model of the
Antarctic Circumpolar Current, J. Phys. Oceanogr., 21, 236–264,
https://doi.org/10.1175/1520-0485(1991)021<0236:WDFOTI>2.0.CO;2, 1991. a, b, c
Zängl, G., Reinert, D., Rípodas, P., and Baldauf, M.: The ICON
(ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M:
Description of the non-hydrostatic dynamical core, Q. J. Roy. Meteor. Soc.,
141, 563–579, https://doi.org/10.1002/qj.2378, 2015. a
Short summary
After the Marinoan snowball Earth, the climate warmed rapidly due to enhanced greenhouse conditions, and the freshwater inflow of melting glaciers caused a strong stratification of the ocean. Our climate simulations reveal a potentially only moderate global temperature increase and a break-up of the stratification within just a few thousand years. The findings give insights into the environmental conditions relevant for the geological and biological evolution during that time.
After the Marinoan snowball Earth, the climate warmed rapidly due to enhanced greenhouse...