Aspects of designing and evaluating seasonal‐to‐interannual Arctic sea‐ice prediction systems
Using lessons from idealised predictability experiments, we discuss some issues and perspectives on the design of operational seasonal to inter‐annual Arctic sea‐ice prediction systems. We first review the opportunities to use a hierarchy of different types of experiment to learn about the predictab...
Published in: | Quarterly Journal of the Royal Meteorological Society |
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crwiley:10.1002/qj.2643 2024-09-15T18:35:13+00:00 Aspects of designing and evaluating seasonal‐to‐interannual Arctic sea‐ice prediction systems Hawkins, Ed Tietsche, Steffen Day, Jonathan J. Melia, Nathanael Haines, Keith Keeley, Sarah UK NERC 2015 http://dx.doi.org/10.1002/qj.2643 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fqj.2643 https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2643 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/qj.2643 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2643 en eng Wiley http://creativecommons.org/licenses/by/4.0/ Quarterly Journal of the Royal Meteorological Society volume 142, issue 695, page 672-683 ISSN 0035-9009 1477-870X journal-article 2015 crwiley https://doi.org/10.1002/qj.2643 2024-07-18T04:22:06Z Using lessons from idealised predictability experiments, we discuss some issues and perspectives on the design of operational seasonal to inter‐annual Arctic sea‐ice prediction systems. We first review the opportunities to use a hierarchy of different types of experiment to learn about the predictability of Arctic climate. We also examine key issues for ensemble system design, such as measuring skill, the role of ensemble size and generation of ensemble members. When assessing the potential skill of a set of prediction experiments, using more than one metric is essential as different choices can significantly alter conclusions about the presence or lack of skill. We find that increasing both the number of hindcasts and ensemble size is important for reliably assessing the correlation and expected error in forecasts. For other metrics, such as dispersion, increasing ensemble size is most important. Probabilistic measures of skill can also provide useful information about the reliability of forecasts. In addition, various methods for generating the different ensemble members are tested. The range of techniques can produce surprisingly different ensemble spread characteristics. The lessons learnt should help inform the design of future operational prediction systems. Article in Journal/Newspaper Sea ice Wiley Online Library Quarterly Journal of the Royal Meteorological Society 142 695 672 683 |
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Open Polar |
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Wiley Online Library |
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crwiley |
language |
English |
description |
Using lessons from idealised predictability experiments, we discuss some issues and perspectives on the design of operational seasonal to inter‐annual Arctic sea‐ice prediction systems. We first review the opportunities to use a hierarchy of different types of experiment to learn about the predictability of Arctic climate. We also examine key issues for ensemble system design, such as measuring skill, the role of ensemble size and generation of ensemble members. When assessing the potential skill of a set of prediction experiments, using more than one metric is essential as different choices can significantly alter conclusions about the presence or lack of skill. We find that increasing both the number of hindcasts and ensemble size is important for reliably assessing the correlation and expected error in forecasts. For other metrics, such as dispersion, increasing ensemble size is most important. Probabilistic measures of skill can also provide useful information about the reliability of forecasts. In addition, various methods for generating the different ensemble members are tested. The range of techniques can produce surprisingly different ensemble spread characteristics. The lessons learnt should help inform the design of future operational prediction systems. |
author2 |
UK NERC |
format |
Article in Journal/Newspaper |
author |
Hawkins, Ed Tietsche, Steffen Day, Jonathan J. Melia, Nathanael Haines, Keith Keeley, Sarah |
spellingShingle |
Hawkins, Ed Tietsche, Steffen Day, Jonathan J. Melia, Nathanael Haines, Keith Keeley, Sarah Aspects of designing and evaluating seasonal‐to‐interannual Arctic sea‐ice prediction systems |
author_facet |
Hawkins, Ed Tietsche, Steffen Day, Jonathan J. Melia, Nathanael Haines, Keith Keeley, Sarah |
author_sort |
Hawkins, Ed |
title |
Aspects of designing and evaluating seasonal‐to‐interannual Arctic sea‐ice prediction systems |
title_short |
Aspects of designing and evaluating seasonal‐to‐interannual Arctic sea‐ice prediction systems |
title_full |
Aspects of designing and evaluating seasonal‐to‐interannual Arctic sea‐ice prediction systems |
title_fullStr |
Aspects of designing and evaluating seasonal‐to‐interannual Arctic sea‐ice prediction systems |
title_full_unstemmed |
Aspects of designing and evaluating seasonal‐to‐interannual Arctic sea‐ice prediction systems |
title_sort |
aspects of designing and evaluating seasonal‐to‐interannual arctic sea‐ice prediction systems |
publisher |
Wiley |
publishDate |
2015 |
url |
http://dx.doi.org/10.1002/qj.2643 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fqj.2643 https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2643 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/qj.2643 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2643 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
Quarterly Journal of the Royal Meteorological Society volume 142, issue 695, page 672-683 ISSN 0035-9009 1477-870X |
op_rights |
http://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.1002/qj.2643 |
container_title |
Quarterly Journal of the Royal Meteorological Society |
container_volume |
142 |
container_issue |
695 |
container_start_page |
672 |
op_container_end_page |
683 |
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1810478225872125952 |