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

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. From this model, we extract an optimal combined measure of Arctic sea ice extent using the Kalman smoother.

Keywords: Climate modeling, nowcasting, model averaging, ensemble averaging

JEL Classification: Q54, C22

Suggested Citation: Suggested Citation

Diebold, Francis X. and Göbel, Maximilian and Goulet Coulombe, Philippe and Rudebusch, Glenn D. and Zhang, Boyuan, Optimal Combination of Arctic Sea Ice Extent Measures: A Dynamic Factor Modeling Approach (March 31, 2020). PIER Working Paper No. 20-012 , Available at SSRN: https://ssrn.com/abstract=3566029 or http://dx.doi.org/10.2139/ssrn.3566029

Francis X. Diebold (Contact Author)

University of Pennsylvania - Department of Economics ( email )

Ronald O. Perelman Center for Political Science
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