Optimal Combination of Arctic Sea Ice Extent Measures: A Dynamic Factor Modeling Approach

Francis Diebold, Maximilian G\"obel, Philippe Goulet Coulombe, Glenn Rudebusch and Boyuan Zhang ()

Papers from arXiv.org

Abstract: The diminishing extent of Arctic sea ice is a key indicator of climate change as well as an accelerant for future global warming. Since 1978, Arctic sea ice has been measured using satellite-based microwave sensing; however, different measures of Arctic sea ice extent have been made available based on differing algorithmic transformations of the raw satellite data. We propose and estimate a dynamic factor model that combines four of these measures in an optimal way that accounts for their differing volatility and cross-correlations. We then use the Kalman smoother to extract an optimal combined measure of Arctic sea ice extent. It turns out that almost all weight is put on the NSIDC Sea Ice Index, confirming and enhancing confidence in the Sea Ice Index and the NASA Team algorithm on which it is based.

Date: 2020-03, Revised 2020-08
New Economics Papers: this item is included in nep-env and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://arxiv.org/pdf/2003.14276 Latest version (application/pdf)

Related works:
Journal Article: Optimal combination of Arctic sea ice extent measures: A dynamic factor modeling approach (2021)
Working Paper: Optimal Combination of Arctic Sea Ice Extent Measures: A Dynamic Factor Modeling Approach (2020)
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:arx:papers:2003.14276

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().