EGU2020-11241
https://doi.org/10.5194/egusphere-egu2020-11241
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Quantifying uncertainties in the land ice contribution to sea level from ISMIP6 and GlacierMIP

Tamsin Edwards1 and the ISMIP6, GlacierMIP and friends*
Tamsin Edwards and the ISMIP6, GlacierMIP and friends
  • 1King's College London, Geography, United Kingdom of Great Britain and Northern Ireland (tamsin.edwards@kcl.ac.uk)
  • *A full list of authors appears at the end of the abstract

The land ice contribution to global mean sea level has not yet been predicted for the latest generation of socio-economic scenarios, nor with coordinated assessment of uncertainties from the various computer models involved (climate, Greenland and Antarctic ice sheets, and global glaciers). Two recent projects generated a large suite of projections but used previous generation scenarios and climate models and could not fully explore uncertainties. Here we estimate probability distributions for their projections, using statistical emulation, and find uncertainty does not diminish if greenhouse gas concentrations are reduced: the sea level contribution of land ice is 28 [5, 57] cm from 2015 to 2100 under no mitigation (median and 90% range), and 16 [-5, 46] cm under very stringent mitigation. Greenland is projected to contribute around 2.5 cm/ºC of global warming, and Alaskan and Arctic glaciers a total of around 2 cm/ºC, but Antarctic uncertainties are too large to determine temperature-dependence. Knowing future global mean temperature exactly for a given socio-economic scenario would reduce the uncertainty for glaciers by up to two thirds (6 cm) but have little effect for ice sheets. Quantifying how ice sheet margins respond to ocean warming would reduce uncertainty by up to one third (Antarctica 15 cm; Greenland 7 cm). The remaining uncertainty for a given scenario is dominated by the climate and glaciological models themselves. Improved modelling and observations of polar regions, rather than global warming and glaciers, would therefore have the greatest effect in reducing uncertainty in future sea level rise.

ISMIP6, GlacierMIP and friends:

Sophie Nowicki, Heiko Goelzer, Hélène Seroussi, Ben Marzeion, Christopher J. Smith, Nicolas C. Jourdain, Donald Slater, Christine M. McKenna, Erika Simon, Ayako Abe Ouchi, Jonathan M. Gregory, Regine Hock, Eric Larour, William H. Lipscomb, Antony J. Payne, Andrew Shepherd, Cécile Agosta, Patrick Alexander, Torsten Albrecht, Brian Anderson, Xylar Asay-Davis, Andy Aschwanden, Alice Barthel, Andrew Bliss, Reinhard Calov, Christopher Chambers, Nicolas Champollion, Youngmin Choi, Richard Cullather, Joshua Cuzzone, Christophe Dumas, Denis Felikson, Xavier Fettweis, Koji Fujita, Rupert Gladstone, Nicholas R. Golledge, Ralf Greve, Tore Hattermann, Matthew J. Hoffman, Angelika Humbert, Matthias Huss, Philippe Huybrechts, Walter Immerzeel, Thomas Kleiner, Philip Kraaijenbrink, Sébastien Le clec'h, Victoria Lee, Gunter R. Leguy, Christopher M. Little, Daniel P. Lowry, Jan-Hendrik Malles, Fabien Maussion, Mathieu Morlighem, Isabel Nias, Frank Pattyn, Tyler Pelle, Steve Price, Aurélien Quiquet, Valentina Radić, Ronja Reese, David R. Rounce, Martin Rückamp, Akiko Sakai, Nicole-Jeanne Schlegel, Sarah Shannon, Robin Smith, Fiammetta Straneo, Sainan Sun, Lev Tarasov, Luke D. Trusel, Jonas Van Breedam, Roderik van de Wal, Michiel van den Broeke, Ricarda Winkelmann, Chen Zhao, Tong Zhang, Harry Zekollari, Thomas Zwinger

How to cite: Edwards, T. and the ISMIP6, GlacierMIP and friends: Quantifying uncertainties in the land ice contribution to sea level from ISMIP6 and GlacierMIP, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11241, https://doi.org/10.5194/egusphere-egu2020-11241, 2020

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  • CC1: Comment on EGU2020-11241, Gael Durand, 05 May 2020

    Hi Tamsin.. Regarding the remaining uncertainties due to ice sheet models, can you say more on which process is the most impacting ? Presumably MICI and friction law?

    • AC1: Reply to CC1, Tamsin Edwards, 06 May 2020

      Hi Gael, thanks for your question.

      I haven't done a systematic review of the model processes to see which make most difference. Some things I noticed: 

      - several PISM Antarctic projections that use their own basal melt parameterisations (not ISMIP6 one) give negative WAIS contributions at 2100

      - climate model differences in SMB make a big difference to net AIS contribution

      - initialisation period/method can make as big a difference as different ice sheet models.

      None of the ISMIP6 ensemble include MICI, so I did a max estimate of this for the paper based on DeConto & Pollard's (2016) for WAIS and EAIS (large).

      The individual ISMIP6 papers have more details on model processes and types: Seroussi et al. and Goelzer et al. in the Cryosphere ISMIP6 special issue for the CMIP5-forced runs (CMIP6-forced are not in an open review journal). 

      All the best,

      Tamsin

  • AC2: Error found in Antarctic simulation processing, Tamsin Edwards, 11 May 2020

    Please note an error in Antarctic control simulation subtraction has recently been found which affects several models - in particular, please disregard the WAIS low mode on slide 10 and the comment about this being due to open melt PISM models.

    Tamsin

    • AC3: Reply to AC2, Tamsin Edwards, 11 May 2020

      (the error does not affect other ISMIP6 papers, just this analysis)