RT Generic
T1 Global, Arctic, and Antarctic sea ice volume predictions: using score-driven threshold climate models
A1 Blazsek, Szabolcs Istvan
A1 Escribano, Álvaro
A1 Kristof, Erzsebet
A2 Universidad Carlos III de Madrid. Departamento de Economía, 
AB 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 mainlyon the Arctic. According to the same literature, GCMs are not sensitive enough to tipping points in theAtlantic meridional overturning circulation (AMOC), and they underestimate the sensitivity of Arcticsea ice to carbon emissions. In this paper, we use a novel time series model, named the score-driventhreshold climate (SDTC) model, and we report global, Arctic, and Antarctic sea ice predictions. Forthe SDTC model, the estimations are computationally less demanding than those of the GCMs. Wecombine long-run 1,000-year frequency climate data from 798,000 to 1,000 years ago, and short-runannual data from year 850 to year 2014. We present the evolution of long-run and short-run climatedata with descriptive statistics. We estimate the SDTC model using annual data from 850 to 2014for Arctic and Antarctic sea ice volume Ice𝑡 and Antarctic land surface temperature Temp𝑡 . We usethe atmospheric CO2,𝑡 concentration as a clustering variable to define periods of climate change. Wereport in-sample interval forecasts of global, Arctic, and Antarctic sea ice from 1980 to 2014. Observedglobal and Arctic sea ice volumes are below the forecasted interval from 2003. Observed Antarctic seaice volume is below the forecasted interval from 2011. We report out-of-sample interval forecasts ofsea ice from 2015 to 2314. The out-of-sample forecasts, 𝜇[𝜇 ± 2𝜎], indicate that if the current trendof climate change continues, then Arctic sea ice will disappear around 2058[2049, 2068], and globaland Antarctic sea ice will disappear around 2174[2123, 2270].
SN 2340-5031
YR 2024
FD 2024-01-25
LK https://hdl.handle.net/10016/39546
UL https://hdl.handle.net/10016/39546
LA eng
NO 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 Comunidadde Madrid, grant EPUC3M11 (V PRICIT), is gratefully acknowledged.
DS e-Archivo
RD 1 sept. 2024