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

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]. ; Financial support by MICIN/AEI/10.13039/501100011033, Agencia Estatal de Investigacion-Ministerio de Ciencia e Innovación, (María de Maeztu); MICIN/AEI/2023/00378/001 and CEX2021-001181-M; and Comunidad de Madrid, grant EPUC3M11 (V PRICIT), is gratefully acknowledged.