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

• Main Authors: Francis X. Diebold, Maximilian Gobel, Philippe Goulet Coulombe, Glenn D. Rudebusch, Boyuan Zhang
• Format: Report
• Language: unknown
• Subjects: Arctic; Climate change; Global warming; Sea ice
• Online Access: https://economics.sas.upenn.edu/system/files/working-papers/20-012%20PIER%20Paper%20Submission.pdf

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. Climate modeling, nowcasting, model averaging, ensemble averaging