Preprints
https://doi.org/10.5194/gmd-2024-203
https://doi.org/10.5194/gmd-2024-203
Submitted as: model description paper
 | 
03 Jan 2025
Submitted as: model description paper |  | 03 Jan 2025
Status: this preprint is currently under review for the journal GMD.

The Development and Application of an Arctic Sea Ice Emulator v.1

Sian Megan Chilcott and Malte Meinshausen

Abstract. The high computational expense of complex climate models and their tendency to underestimate observational records of Arctic sea ice sensitivity to anthropogenic forcers, challenge our ability to assess the magnitude of forcing that will cause Arctic sea ice loss to cross critical thresholds. To address these limitations, we development an Arctic sea ice emulator, that is calibrated to the response of sea ice area to global warming in physically-based CMIP6 models and constrained to observations. Our constrained emulator reduces the remaining budget of CO2 that can be emitted to prevent seasonally ice-free conditions from 821 GtCO2 by CMIP6 multi-model ensemble estimates to 380 GtCO2. This suggests that limiting global warming to 1.5 °C is sufficient to prevent a seasonally ice-free Arctic Ocean, whereas 2 °C proves insufficient. Our results also provide insight into the future of winter sea ice over a greater ensemble range than previously possible, pinpointing the emission threshold at which the ice pack detaches from land, after which the ice pack rapidly disappears to year-round ice free conditions.

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Sian Megan Chilcott and Malte Meinshausen

Status: open (until 28 Feb 2025)

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Sian Megan Chilcott and Malte Meinshausen
Sian Megan Chilcott and Malte Meinshausen

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Short summary
Climate models are expensive to run and often underestimate how sensitive Arctic sea ice is to climate change. To address this, we developed a simple model that emulates the response of sea ice to global warming. We find the remaining carbon dioxide (CO2) emissions that will avoid a seasonally ice-free Arctic Ocean is lower than previous estimates of 821 Gigatonnes of CO2. Our model also provides insights into the future of winter sea ice, examining a larger ensemble than previously possible.