A benchmark model for fixed-target Arctic sea ice forecasting

Francis Diebold and Maximilian Göbel

Economics Letters, 2022, vol. 215, issue C

Abstract: We propose a reduced-form benchmark predictive model (BPM) for fixed-target forecasting of Arctic sea ice extent, and we provide a case study of its real-time performance for target date September 2020. We visually detail the evolution of the statistically-optimal point, interval, and density forecasts as time passes, new information arrives, and the end of September approaches. Comparison to the BPM may prove useful for evaluating and selecting among various more sophisticated dynamical sea ice models, which are widely used to quantify the likely future evolution of Arctic conditions and their two-way interaction with economic activity.

Keywords: Climate forecasting; Climate prediction; Climate change; Forecast evaluation (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 (4)

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Related works:
Working Paper: A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting (2022)
Working Paper: A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:215:y:2022:i:c:s0165176522001161

DOI: 10.1016/j.econlet.2022.110478

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