The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1
Abstract. Recent decades have seen significant developments in climate prediction capabilities at seasonal-to-interannual timescales. However, until recently the potential of such systems to predict Arctic climate had rarely been assessed. This paper describes a multi-model predictability experiment...
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Online Access: | https://centaur.reading.ac.uk/66008/ https://centaur.reading.ac.uk/66008/1/gmd-9-2255-2016.pdf https://doi.org/10.5194/gmd-9-2255-2016 |
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ftunivreading:oai:centaur.reading.ac.uk:66008 2024-06-23T07:48:44+00:00 The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1 Day, Jonny J. Tietsche, Steffen Collins, Mat Goessling, Helge F. Guemas, Virginie Guillory, Anabelle Hurlin, William J. Ishii, Masayoshi Keeley, Sarah P. E. Matei, Daniela Msadek, Rym Sigmond, Michael Tatebe, Hiroaki Hawkins, Ed 2016-06-29 text https://centaur.reading.ac.uk/66008/ https://centaur.reading.ac.uk/66008/1/gmd-9-2255-2016.pdf https://doi.org/10.5194/gmd-9-2255-2016 en eng European Geosciences Union https://centaur.reading.ac.uk/66008/1/gmd-9-2255-2016.pdf Day, J. J. <https://centaur.reading.ac.uk/view/creators/90004387.html>, Tietsche, S., Collins, M., Goessling, H. F., Guemas, V., Guillory, A., Hurlin, W. J., Ishii, M., Keeley, S. P. E., Matei, D., Msadek, R., Sigmond, M., Tatebe, H. and Hawkins, E. <https://centaur.reading.ac.uk/view/creators/90000949.html> orcid:0000-0001-9477-3677 (2016) The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1. Geoscientific Model Development, 9 (6). pp. 2255-2270. ISSN 1991-9603 doi: https://doi.org/10.5194/gmd-9-2255-2016 <https://doi.org/10.5194/gmd-9-2255-2016> cc_by Article PeerReviewed 2016 ftunivreading https://doi.org/10.5194/gmd-9-2255-2016 2024-06-11T15:05:53Z Abstract. Recent decades have seen significant developments in climate prediction capabilities at seasonal-to-interannual timescales. However, until recently the potential of such systems to predict Arctic climate had rarely been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Interannual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to interannual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre), an assessment of Arctic sea ice extent and volume predictability estimates in these models, and an investigation into to what extent predictability is dependent on the initial state. The inclusion of additional models expands the range of sea ice volume and extent predictability estimates, demonstrating that there is model diversity in the potential to make seasonal-to-interannual timescale predictions. We also investigate whether sea ice forecasts started from extreme high and low sea ice initial states exhibit higher levels of potential predictability than forecasts started from close to the models' mean state, and find that the result depends on the metric. Although designed to address Arctic predictability, we describe the archived data here so that others can use this data set to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño–Southern Oscillation. Article in Journal/Newspaper Arctic Arctic Sea ice CentAUR: Central Archive at the University of Reading Arctic Geoscientific Model Development 9 6 2255 2270 |
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CentAUR: Central Archive at the University of Reading |
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ftunivreading |
language |
English |
description |
Abstract. Recent decades have seen significant developments in climate prediction capabilities at seasonal-to-interannual timescales. However, until recently the potential of such systems to predict Arctic climate had rarely been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Interannual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to interannual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre), an assessment of Arctic sea ice extent and volume predictability estimates in these models, and an investigation into to what extent predictability is dependent on the initial state. The inclusion of additional models expands the range of sea ice volume and extent predictability estimates, demonstrating that there is model diversity in the potential to make seasonal-to-interannual timescale predictions. We also investigate whether sea ice forecasts started from extreme high and low sea ice initial states exhibit higher levels of potential predictability than forecasts started from close to the models' mean state, and find that the result depends on the metric. Although designed to address Arctic predictability, we describe the archived data here so that others can use this data set to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño–Southern Oscillation. |
format |
Article in Journal/Newspaper |
author |
Day, Jonny J. Tietsche, Steffen Collins, Mat Goessling, Helge F. Guemas, Virginie Guillory, Anabelle Hurlin, William J. Ishii, Masayoshi Keeley, Sarah P. E. Matei, Daniela Msadek, Rym Sigmond, Michael Tatebe, Hiroaki Hawkins, Ed |
spellingShingle |
Day, Jonny J. Tietsche, Steffen Collins, Mat Goessling, Helge F. Guemas, Virginie Guillory, Anabelle Hurlin, William J. Ishii, Masayoshi Keeley, Sarah P. E. Matei, Daniela Msadek, Rym Sigmond, Michael Tatebe, Hiroaki Hawkins, Ed The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1 |
author_facet |
Day, Jonny J. Tietsche, Steffen Collins, Mat Goessling, Helge F. Guemas, Virginie Guillory, Anabelle Hurlin, William J. Ishii, Masayoshi Keeley, Sarah P. E. Matei, Daniela Msadek, Rym Sigmond, Michael Tatebe, Hiroaki Hawkins, Ed |
author_sort |
Day, Jonny J. |
title |
The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1 |
title_short |
The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1 |
title_full |
The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1 |
title_fullStr |
The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1 |
title_full_unstemmed |
The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1 |
title_sort |
arctic predictability and prediction on seasonal-to-interannual timescales (apposite) data set version 1 |
publisher |
European Geosciences Union |
publishDate |
2016 |
url |
https://centaur.reading.ac.uk/66008/ https://centaur.reading.ac.uk/66008/1/gmd-9-2255-2016.pdf https://doi.org/10.5194/gmd-9-2255-2016 |
geographic |
Arctic |
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Arctic |
genre |
Arctic Arctic Sea ice |
genre_facet |
Arctic Arctic Sea ice |
op_relation |
https://centaur.reading.ac.uk/66008/1/gmd-9-2255-2016.pdf Day, J. J. <https://centaur.reading.ac.uk/view/creators/90004387.html>, Tietsche, S., Collins, M., Goessling, H. F., Guemas, V., Guillory, A., Hurlin, W. J., Ishii, M., Keeley, S. P. E., Matei, D., Msadek, R., Sigmond, M., Tatebe, H. and Hawkins, E. <https://centaur.reading.ac.uk/view/creators/90000949.html> orcid:0000-0001-9477-3677 (2016) The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1. Geoscientific Model Development, 9 (6). pp. 2255-2270. ISSN 1991-9603 doi: https://doi.org/10.5194/gmd-9-2255-2016 <https://doi.org/10.5194/gmd-9-2255-2016> |
op_rights |
cc_by |
op_doi |
https://doi.org/10.5194/gmd-9-2255-2016 |
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Geoscientific Model Development |
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