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Global, Arctic, and Antarctic sea ice volume predictions: using score-driven threshold climate models

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  • Blazsek, Szabolcs Istvan
  • Kristof, Erzsebet
  • Escribano, Álvaro

Abstract

The literature on sea ice predictions uses a variety of general circulation models (GCMs), which suggest diverse predictions of the date of ice-free or almost ice-free oceans, and focus mainly on the Arctic. According to the same literature, GCMs are not sensitive enough to tipping points in the Atlantic meridional overturning circulation (AMOC), and they underestimate the sensitivity of Arctic sea ice to carbon emissions. In this paper, we use a novel time series model, named the score-driven threshold climate (SDTC) model, and we report global, Arctic, and Antarctic sea ice predictions. For the SDTC model, the estimations are computationally less demanding than those of the GCMs. We combine long-run 1,000-year frequency climate data from 798,000 to 1,000 years ago, and short-run annual data from year 850 to year 2014. We present the evolution of long-run and short-run climate data with descriptive statistics. We estimate the SDTC model using annual data from 850 to 2014 for Arctic and Antarctic sea ice volume Ice𝑡 and Antarctic land surface temperature Temp𝑡 . We use the atmospheric CO2,𝑡 concentration as a clustering variable to define periods of climate change. We report in-sample interval forecasts of global, Arctic, and Antarctic sea ice from 1980 to 2014. Observed global and Arctic sea ice volumes are below the forecasted interval from 2003. Observed Antarctic sea ice volume is below the forecasted interval from 2011. We report out-of-sample interval forecasts of sea ice from 2015 to 2314. The out-of-sample forecasts, 𝜇[𝜇 ± 2𝜎], indicate that if the current trend of climate change continues, then Arctic sea ice will disappear around 2058[2049, 2068], and global and Antarctic sea ice will disappear around 2174[2123, 2270].

Suggested Citation

  • Blazsek, Szabolcs Istvan & Kristof, Erzsebet & Escribano, Álvaro, 2024. "Global, Arctic, and Antarctic sea ice volume predictions: using score-driven threshold climate models," UC3M Working papers. Economics 39546, Universidad Carlos III de Madrid. Departamento de Economía.
  • Handle: RePEc:cte:werepe:39546
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    References listed on IDEAS

    as
    1. Peter Ditlevsen & Susanne Ditlevsen, 2023. "Warning of a forthcoming collapse of the Atlantic meridional overturning circulation," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    2. Szabolcs Blazsek & Alvaro Escribano, 2022. "Robust Estimation and Forecasting of Climate Change Using Score-Driven Ice-Age Models," Econometrics, MDPI, vol. 10(1), pages 1-29, February.
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    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. 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).
    6. Blazsek, Szabolcs & Escribano, Alvaro, 2023. "Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts," Energy Economics, Elsevier, vol. 118(C).
    7. Drew Creal & Siem Jan Koopman & André Lucas, 2013. "Generalized Autoregressive Score Models With Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 777-795, August.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Climate Change;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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