A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting

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 foreca...

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Bibliographic Details
Main Authors: Diebold, Francis X., Gobel, Maximilian
Format: Text
Language:unknown
Published: 2021
Subjects:
geo
envir
Arctic
Sea ice
Online Access:http://arxiv.org/abs/2101.10359
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spelling fttriple:oai:gotriple.eu:10670/1.8wpmf8 2023-05-15T14:40:47+02:00 A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting Diebold, Francis X. Gobel, Maximilian 2021-01-25 http://arxiv.org/abs/2101.10359 undefined unknown 10670/1.8wpmf8 http://arxiv.org/abs/2101.10359 undefined arXiv geo envir Text https://vocabularies.coar-repositories.org/resource_types/c_18cf/ 2021 fttriple 2023-01-22T17:56:43Z 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. Text Arctic Sea ice Unknown Arctic
institution Open Polar
collection Unknown
op_collection_id fttriple
language unknown
topic geo
envir
spellingShingle geo
envir
Diebold, Francis X.
Gobel, Maximilian
A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting
topic_facet geo
envir
description 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.
format Text
author Diebold, Francis X.
Gobel, Maximilian
author_facet Diebold, Francis X.
Gobel, Maximilian
author_sort Diebold, Francis X.
title A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting
title_short A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting
title_full A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting
title_fullStr A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting
title_full_unstemmed A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting
title_sort benchmark model for fixed-target arctic sea ice forecasting
publishDate 2021
url http://arxiv.org/abs/2101.10359
geographic Arctic
geographic_facet Arctic
genre Arctic
Sea ice
genre_facet Arctic
Sea ice
op_source arXiv
op_relation 10670/1.8wpmf8
http://arxiv.org/abs/2101.10359
op_rights undefined
_version_ 1766312661973204992

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