EGU22-4740
https://doi.org/10.5194/egusphere-egu22-4740
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Antarctic-climate multi-millenia coupled simulations under different pCO2 levels with the iLOVECLIM-GRISLI model

Gaelle Leloup1,2, Aurélien Quiquet, Christophe Dumas, Didier Roche, and Didier Paillard
Gaelle Leloup et al.
  • 1LSCE Laboratoire des Sciences du Climat et de l'Environnement, CLIM - Climate Modeling, Paris, France (gaelle.leloup@lsce.ipsl.fr)
  • 2ANDRA Agence nationale pour la gestion des déchets radioactifs, Châtenay-Malabry, France

Ice sheets and the rest of the climate system interact in various ways, notably via the atmosphere, ocean and solid earth. Atmospheric and oceanic temperatures and circulations affect the evolution of ice-sheets, and conversely ice-sheet evolution impacts the rest of the climate system via various processes, including albedo modification, topographic changes and freshwater flux release into the ocean. To correctly model the evolution of the climate system and sea level rise, these feedbacks therefore need to be considered.

Under the highest emission scenario, temperature is expected to reach levels comparable to the Eocene epoch in a few centuries [1]. At this time, there was no widespread glaciation in Antarctica.

The work of Garbe et al [2] has shown that the Antarctic ice sheet has a hysteresis behavior and gave different temperature thresholds leading to committed Antarctic mass loss. For example, between 6 and 9 degrees of warming (a global temperature increase comparable to the one expected in 2300 for the most emissive scenario), the loss of 70% of the present-day ice volume is triggered. However, the modelling study used idealized perturbations of the climate fields based solely on global mean temperature. More specifically, global mean temperature is translated into local changes of ocean and surface air temperature and increased until a complete deglaciation of the Antarctic ice-sheet is reached. In addition the study did not take into account the ice sheet change feedback on the climate system.

In our work we intend to go a step further by taking into account both the influence of atmosphere and oceanic temperature and circulations on the ice sheet in a physical way, as well as the influence of the ice sheet on the rest of the climate system.

To do so, we use the coupled ocean-atmosphere-vegetation intermediate complexity model iLOVECLIM [3], fully coupled to the GRISLI ice-sheet model for Antarctica [4, 5].

We perform several multi-millenia equilibria simulations for different pCO2 levels, thanks to the relative rapidity of both the iLOVECLIM and GRISLI models. These simulations lead to different atmospheric and oceanic temperatures and Antarctic mass loss. 

These coupled simulations allow us to explore the impact of the ice sheet feedback on the climate and to investigate the differences compared to cases where these feedbacks are not included. The influence of the model parameters linked to the ice sheet coupling is also studied.

 

References :

[1] Westerhold et al 2020, “An astronomically dated record of Earth’s climate and its predictability over the last 66 million years”

[2] Garbe et al 2020 “The hysteresis of the Antarctic Ice Sheet”

[3] Quiquet et al 2018, “Online dynamical downscaling of temperature and precipitation within the iLOVECLIM model (version 1.1)”

[4] Quiquet et al 2018, “The GRISLI ice sheet model (version 2.0): calibration and validation for multi-millennial changes of the Antarctic ice sheet”

[5] Quiquet et al 2021 “Climate and ice sheet evolutions from the last glacial maximum to the pre-industrial period with an ice-sheet–climate coupled model”

How to cite: Leloup, G., Quiquet, A., Dumas, C., Roche, D., and Paillard, D.: Antarctic-climate multi-millenia coupled simulations under different pCO2 levels with the iLOVECLIM-GRISLI model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4740, https://doi.org/10.5194/egusphere-egu22-4740, 2022.

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