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A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting

Francis Diebold and Maximilian Gobel

Papers from arXiv.org

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.

Date: 2021-01, Revised 2022-01
New Economics Papers: this item is included in nep-env, nep-ets and nep-for
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Citations: View citations in EconPapers (4)

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http://arxiv.org/pdf/2101.10359 Latest version (application/pdf)

Related works:
Journal Article: A benchmark model for fixed-target Arctic sea ice forecasting (2022) Downloads
Working Paper: A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting (2022) Downloads
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