Revisiting the potential of melt pond fraction as a predictor for the seasonal Arctic sea ice extent minimum
The rapid change in Arctic sea ice in recent decades has led to a rising demand for seasonal sea ice prediction. A recent modeling study that employed a prognostic melt pond model in a stand-alone sea ice model found that September Arctic sea ice extent can be accurately predicted from the melt pond...
Published in: | Environmental Research Letters |
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Online Access: | https://doi.org/10.1088/1748-9326/10/5/054017 https://doaj.org/article/52ad759418aa4f42a56b33dae9cf2f3b |
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ftdoajarticles:oai:doaj.org/article:52ad759418aa4f42a56b33dae9cf2f3b 2023-09-05T13:16:56+02:00 Revisiting the potential of melt pond fraction as a predictor for the seasonal Arctic sea ice extent minimum Jiping Liu Mirong Song Radley M Horton Yongyun Hu 2015-01-01T00:00:00Z https://doi.org/10.1088/1748-9326/10/5/054017 https://doaj.org/article/52ad759418aa4f42a56b33dae9cf2f3b EN eng IOP Publishing https://doi.org/10.1088/1748-9326/10/5/054017 https://doaj.org/toc/1748-9326 doi:10.1088/1748-9326/10/5/054017 1748-9326 https://doaj.org/article/52ad759418aa4f42a56b33dae9cf2f3b Environmental Research Letters, Vol 10, Iss 5, p 054017 (2015) seasonal sea ice prediction melt pond fraction sea ice extent Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 article 2015 ftdoajarticles https://doi.org/10.1088/1748-9326/10/5/054017 2023-08-13T00:37:54Z The rapid change in Arctic sea ice in recent decades has led to a rising demand for seasonal sea ice prediction. A recent modeling study that employed a prognostic melt pond model in a stand-alone sea ice model found that September Arctic sea ice extent can be accurately predicted from the melt pond fraction in May. Here we show that satellite observations show no evidence of predictive skill in May. However, we find that a significantly strong relationship (high predictability) first emerges as the melt pond fraction is integrated from early May to late June, with a persistent strong relationship only occurring after late July. Our results highlight that late spring to mid summer melt pond information is required to improve the prediction skill of the seasonal sea ice minimum. Furthermore, satellite observations indicate a much higher percentage of melt pond formation in May than does the aforementioned model simulation, which points to the need to reconcile model simulations and observations, in order to better understand key mechanisms of melt pond formation and evolution and their influence on sea ice state. Article in Journal/Newspaper Arctic Sea ice Directory of Open Access Journals: DOAJ Articles Arctic Environmental Research Letters 10 5 054017 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
seasonal sea ice prediction melt pond fraction sea ice extent Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 |
spellingShingle |
seasonal sea ice prediction melt pond fraction sea ice extent Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 Jiping Liu Mirong Song Radley M Horton Yongyun Hu Revisiting the potential of melt pond fraction as a predictor for the seasonal Arctic sea ice extent minimum |
topic_facet |
seasonal sea ice prediction melt pond fraction sea ice extent Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 |
description |
The rapid change in Arctic sea ice in recent decades has led to a rising demand for seasonal sea ice prediction. A recent modeling study that employed a prognostic melt pond model in a stand-alone sea ice model found that September Arctic sea ice extent can be accurately predicted from the melt pond fraction in May. Here we show that satellite observations show no evidence of predictive skill in May. However, we find that a significantly strong relationship (high predictability) first emerges as the melt pond fraction is integrated from early May to late June, with a persistent strong relationship only occurring after late July. Our results highlight that late spring to mid summer melt pond information is required to improve the prediction skill of the seasonal sea ice minimum. Furthermore, satellite observations indicate a much higher percentage of melt pond formation in May than does the aforementioned model simulation, which points to the need to reconcile model simulations and observations, in order to better understand key mechanisms of melt pond formation and evolution and their influence on sea ice state. |
format |
Article in Journal/Newspaper |
author |
Jiping Liu Mirong Song Radley M Horton Yongyun Hu |
author_facet |
Jiping Liu Mirong Song Radley M Horton Yongyun Hu |
author_sort |
Jiping Liu |
title |
Revisiting the potential of melt pond fraction as a predictor for the seasonal Arctic sea ice extent minimum |
title_short |
Revisiting the potential of melt pond fraction as a predictor for the seasonal Arctic sea ice extent minimum |
title_full |
Revisiting the potential of melt pond fraction as a predictor for the seasonal Arctic sea ice extent minimum |
title_fullStr |
Revisiting the potential of melt pond fraction as a predictor for the seasonal Arctic sea ice extent minimum |
title_full_unstemmed |
Revisiting the potential of melt pond fraction as a predictor for the seasonal Arctic sea ice extent minimum |
title_sort |
revisiting the potential of melt pond fraction as a predictor for the seasonal arctic sea ice extent minimum |
publisher |
IOP Publishing |
publishDate |
2015 |
url |
https://doi.org/10.1088/1748-9326/10/5/054017 https://doaj.org/article/52ad759418aa4f42a56b33dae9cf2f3b |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
Environmental Research Letters, Vol 10, Iss 5, p 054017 (2015) |
op_relation |
https://doi.org/10.1088/1748-9326/10/5/054017 https://doaj.org/toc/1748-9326 doi:10.1088/1748-9326/10/5/054017 1748-9326 https://doaj.org/article/52ad759418aa4f42a56b33dae9cf2f3b |
op_doi |
https://doi.org/10.1088/1748-9326/10/5/054017 |
container_title |
Environmental Research Letters |
container_volume |
10 |
container_issue |
5 |
container_start_page |
054017 |
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1776198333786750976 |