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  • Review Article
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Projections of an ice-free Arctic Ocean

Nature Reviews Earth & Environment volume 5, pages 164–176 (2024)Cite this article

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Abstract

Observed Arctic sea ice losses are a sentinel of anthropogenic climate change. These reductions are projected to continue with ongoing warming, ultimately leading to an ice-free Arctic (sea ice area <1 million km2). In this Review, we synthesize understanding of the timing and regional variability of such an ice-free Arctic. In the September monthly mean, the earliest ice-free conditions (the first single occurrence of an ice-free Arctic) could occur in 2020–2030s under all emission trajectories and are likely to occur by 2050. However, daily September ice-free conditions are expected approximately 4 years earlier on average, with the possibility of preceding monthly metrics by 10 years. Consistently ice-free September conditions (frequent occurrences of an ice-free Arctic) are anticipated by mid-century (by 2035–2067), with emission trajectories determining how often and for how long the Arctic could be ice free. Specifically, there is potential for ice-free conditions in May–January and August–October by 2100 under a high-emission and low-emission scenario, respectively. In all cases, sea ice losses begin in the European Arctic, proceed to the Pacific Arctic and end in the Central Arctic, if becoming ice free at all. Future research must assess the impact of model selection and recalibration on projections, and assess the drivers of internal variability that can cause early ice-free conditions.

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Fig. 1: A white to blue Arctic.
Fig. 2: Processes and feedbacks driving Arctic sea ice loss.
Fig. 3: Sensitivity of ice-free Arctic timing to definitions and model selection.
Fig. 4: Probability of ice-free conditions in all months of the year.
Fig. 5: Regional ice-free conditions.

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Data availability

The CMIP6 sea ice area data is the same as analysed in ref. 10. The underlying SIC data, also used for the spatial plot (Fig. 5), is available on the Earth System Grid Federation (ESGF, https://esgf-node.llnl.gov/search/cmip6/). The data for the CESM2-LE (ref. 112) is available at https://www.cesm.ucar.edu/projects/cvdp-le/data-repository. The data for the CLIVAR Large Ensemble Archive38 is available at https://www.earthsystemgrid.org/dataset/ucar.cgd.ccsm4.CLIVAR_LE.html.

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Acknowledgements

A.J. was supported by an Alexander von Humboldt Fellowship and NSF CAREER award 1847398. M.M.H. acknowledges support from NSF awards 2138788 and 2040538. J.E.K. was supported by NASA PREFIRE award 849K995 and NSF award 2233420. We thank J. Dörr for sharing the sea ice area data calculated for the SIMIP analysis10 and C. Wyburn-Powell for the assistance with regridding of the CMIP6 models for the spatial analysis. We also thank the participants at the Interagency Arctic Research Policy Committee (IARPC) webinar on an ice-free Arctic for the helpful discussions. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modelling groups for producing and making their model output available, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF. We also acknowledge the US Climate and Ocean: Variability, Predictability and Change (CLIVAR) Working Group on Large Ensembles, the modelling centres that contributed to the CLIVAR Large Ensemble project, and the CESM2-LE project.

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Authors and Affiliations

  1. Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO, USA

    Alexandra Jahn & Jennifer E. Kay

  2. Institute for Arctic and Alpine Research, University of Colorado Boulder, Boulder, CO, USA

    Alexandra Jahn

  3. Climate & Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, USA

    Marika M. Holland

  4. Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA

    Jennifer E. Kay

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A.J. decided on the overall scope of the article, wrote the majority of the article, and did all data analyses for the figures in the main article. M.M.H. and J.E.K. contributed to the writing of the manuscript, provided input on the article scope and figures, and edited the manuscript. M.M.H. also performed data analysis for supplementary figures and created one of the supplementary figures.

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Correspondence to Alexandra Jahn.

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Supplementary information

Glossary

Albedo

The fraction of incoming shortwave solar radiation that is reflected by a surface, ranging between 0 and 1.

Internal variability

The variability in the climate system attributable to the chaotic nature of the climate system.

Negative feedbacks

Dampening feedbacks in the climate system, reducing an initial perturbation.

Positive feedbacks

Amplifying feedbacks in the climate system, enhancing an initial perturbation.

Sea ice area

(SIA). The total area of sea ice present, without any threshold, calculated as sea ice concentration multiplied by grid area and summed over all Northern Hemisphere grid boxes. Note that sometimes, sea ice area is calculated only for grid cells with at least 15% sea ice cover.

Sea ice extent

(SIE). The area of all grid boxes that have at least 15% sea ice concentration, calculated as sea ice concentration multiplied by the area of all grid boxes with 15% or more sea ice concentration.

Sea ice sensitivity

The change in sea ice area divided by the change in global or Arctic temperature or cumulative CO2 emissions over the same time period.

Shared Socioeconomic Pathway

(SSP). A forcing scenario that is part of the Scenario Model Intercomparison Project of CMIP6.

Tipping point

An irreversible change in an environmental condition.

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Jahn, A., Holland, M.M. & Kay, J.E. Projections of an ice-free Arctic Ocean. Nat Rev Earth Environ 5, 164–176 (2024). https://doi.org/10.1038/s43017-023-00515-9

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