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When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume

Author

Listed:
  • Francis X. Diebold
  • Glenn D. Rudebusch
  • Maximilian Göbel
  • Philippe Goulet Coulombe
  • Boyuan Zhang

Abstract

Rapidly diminishing Arctic summer sea ice is a strong signal of the pace of global climate change. We provide point, interval, and density forecasts for four measures of Arctic sea ice: area, extent, thickness, and volume. Importantly, we enforce the joint constraint that these measures must simultaneously arrive at an ice-free Arctic. We apply this constrained joint forecast procedure to models relating sea ice to atmospheric carbon dioxide concentration and models relating sea ice directly to time. The resulting "carbon-trend" and "time-trend" projections are mutually consistent and predict a nearly ice-free summer Arctic Ocean by the mid-2030s with an 80% probability. Moreover, the carbon-trend projections show that global adoption of a lower carbon path would likely delay the arrival of a seasonally ice-free Arctic by only a few years.

Suggested Citation

  • Francis X. Diebold & Glenn D. Rudebusch & Maximilian Göbel & Philippe Goulet Coulombe & Boyuan Zhang, 2022. "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," NBER Working Papers 30732, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:30732
    Note: EEE
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    1. is not listed on IDEAS
    2. Alexandre Andorra & Maximilian Gobel, 2024. "Unveiling True Talent: The Soccer Factor Model for Skill Evaluation," Papers 2412.05911, arXiv.org.
    3. Brock, William A. & Miller, J. Isaac, 2024. "Polar amplification in a moist energy balance model: A structural econometric approach to estimation and testing," Journal of Econometrics, Elsevier, vol. 245(1).
    4. Luke P. Jackson & Katarina Juselius & Andrew B. Martinez & Felix Pretis, 2025. "Modelling the dependence between recent changes in polar ice sheets: Implications for global sea-level projections," Working Papers 2025-002, The George Washington University, The Center for Economic Research.
    5. B. Cooper Boniece & Lajos Horv'ath & Lorenzo Trapani, 2023. "On changepoint detection in functional data using empirical energy distance," Papers 2310.04853, arXiv.org.
    6. Diebold, Francis X. & Rudebusch, Glenn D., 2023. "Climate models underestimate the sensitivity of Arctic sea ice to carbon emissions," Energy Economics, Elsevier, vol. 126(C).
    7. Blazsek, Szabolcs & Escribano, Alvaro & Kristof, Erzsebet, 2024. "Global, Arctic, and Antarctic sea ice volume predictions using score-driven threshold climate models," Energy Economics, Elsevier, vol. 134(C).

    More about this item

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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