Probability assessments of an ice-free Arctic: Comparing statistical and climate model projections
Francis Diebold and
Glenn Rudebusch
Journal of Econometrics, 2022, vol. 231, issue 2, 520-534
Abstract:
The downward trend in the amount of Arctic sea ice has a wide range of environmental and economic consequences including important effects on the pace and intensity of global climate change. Based on several decades of satellite data, we provide statistical forecasts of Arctic sea ice extent during the rest of this century. The best fitting statistical model indicates that overall sea ice coverage is declining at an increasing rate. By contrast, average projections from the CMIP5 global climate models foresee a gradual slowing of Arctic sea ice loss even in scenarios with high carbon emissions. Our long-range statistical projections also deliver probability assessments of the timing of an ice-free Arctic. These results indicate almost a 60 percent chance of an effectively ice-free Arctic Ocean sometime during the 2030s — much earlier than the average projection from the global climate models.
Keywords: Sea ice extent; Climate models; Climate change; Climate trends; Climate prediction (search for similar items in EconPapers)
JEL-codes: C22 C51 C52 C53 Q54 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407620304012
Full text for ScienceDirect subscribers only
Related works:
Working Paper: Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections (2021) 
Working Paper: Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections (2020) 
Working Paper: Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections (2020) 
Working Paper: Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections (2019) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:231:y:2022:i:2:p:520-534
DOI: 10.1016/j.jeconom.2020.12.007
Access Statistics for this article
Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson
More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().