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The diminishing extent of Arctic sea ice is a key indicator of climate changeas well as an accelerant for future global warming. Since 1978, Arctic sea icehas been measured using satellite-based microwave sensing; however, differentmeasures of Arctic sea ice extent have been made available based on differingalgorithmic transformations of the raw satellite data. We propose and estimatea dynamic factor model that combines four of these measures in an optimal waythat accounts for their differing volatility and cross-correlations. We thenuse the Kalman smoother to extract an optimal combined measure of Arctic seaice extent. It turns out that almost all weight is put on the NSIDC Sea IceIndex, confirming and enhancing confidence in the Sea Ice Index and the NASATeam algorithm on which it is based.

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