September Arctic sea ice minimum prediction — a skillful new statistical approach

Sea ice in both polar regions is an important indicator of the expression of global climate change and its polar amplification. Consequently, broad interest exists on sea ice coverage, variability and long-term change. However, its predictability is complex and it depends strongly on different atmos...

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Published in:Earth System Dynamics
Main Authors: Ionita, Monica, Grosfeld, Klaus, Scholz, Patrick, Treffeisen, Renate, Lohmann, Gerrit
Format: Article in Journal/Newspaper
Language:unknown
Published: Copernicus Publications 2019
Subjects:
Online Access:https://epic.awi.de/id/eprint/49304/
https://epic.awi.de/id/eprint/49304/1/Ionita-ESD2019.pdf
https://www.earth-syst-dynam.net/10/189/2019/
https://hdl.handle.net/10013/epic.b00f0923-9e6f-40af-8a5c-30edc16804ec
https://hdl.handle.net/
id ftawi:oai:epic.awi.de:49304
record_format openpolar
spelling ftawi:oai:epic.awi.de:49304 2023-05-15T14:27:44+02:00 September Arctic sea ice minimum prediction — a skillful new statistical approach Ionita, Monica Grosfeld, Klaus Scholz, Patrick Treffeisen, Renate Lohmann, Gerrit 2019-03-21 application/pdf https://epic.awi.de/id/eprint/49304/ https://epic.awi.de/id/eprint/49304/1/Ionita-ESD2019.pdf https://www.earth-syst-dynam.net/10/189/2019/ https://hdl.handle.net/10013/epic.b00f0923-9e6f-40af-8a5c-30edc16804ec https://hdl.handle.net/ unknown Copernicus Publications https://epic.awi.de/id/eprint/49304/1/Ionita-ESD2019.pdf https://hdl.handle.net/ Ionita, M. orcid:0000-0001-8240-4380 , Grosfeld, K. orcid:0000-0001-5936-179X , Scholz, P. orcid:0000-0003-2692-7624 , Treffeisen, R. and Lohmann, G. orcid:0000-0003-2089-733X (2019) September Arctic sea ice minimum prediction — a skillful new statistical approach , Earth System Dynamics, 10 (1), pp. 189-203 . doi:10.5194/esd-10-189-2019 <https://doi.org/10.5194/esd-10-189-2019> , hdl:10013/epic.b00f0923-9e6f-40af-8a5c-30edc16804ec EPIC3Earth System Dynamics, Copernicus Publications, 10(1), pp. 189-203, ISSN: 2190-4979 Article isiRev 2019 ftawi https://doi.org/10.5194/esd-10-189-2019 2021-12-24T15:44:36Z Sea ice in both polar regions is an important indicator of the expression of global climate change and its polar amplification. Consequently, broad interest exists on sea ice coverage, variability and long-term change. However, its predictability is complex and it depends strongly on different atmospheric and oceanic parameters. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we applied a robust statistical model based on different oceanic and atmospheric parameters to calculate an estimate of the September sea ice extent (SSIE) on a monthly timescale. Although previous statistical attempts of monthly/seasonal SSIE forecasts show a relatively reduced skill, when the trend is removed, we show here that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months’ oceanic and atmospheric conditions. Our statistical model skillfully captures the interannual variability of the SSIE and could provide a valuable tool for identifying relevant regions and oceanic and atmospheric parameters that are important for the sea ice development in the Arctic and for detecting sensitive/critical regions in global coupled climate models with a focus on sea ice formation. Article in Journal/Newspaper Arctic Arctic Climate change Sea ice Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) Arctic Earth System Dynamics 10 1 189 203
institution Open Polar
collection Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center)
op_collection_id ftawi
language unknown
description Sea ice in both polar regions is an important indicator of the expression of global climate change and its polar amplification. Consequently, broad interest exists on sea ice coverage, variability and long-term change. However, its predictability is complex and it depends strongly on different atmospheric and oceanic parameters. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we applied a robust statistical model based on different oceanic and atmospheric parameters to calculate an estimate of the September sea ice extent (SSIE) on a monthly timescale. Although previous statistical attempts of monthly/seasonal SSIE forecasts show a relatively reduced skill, when the trend is removed, we show here that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months’ oceanic and atmospheric conditions. Our statistical model skillfully captures the interannual variability of the SSIE and could provide a valuable tool for identifying relevant regions and oceanic and atmospheric parameters that are important for the sea ice development in the Arctic and for detecting sensitive/critical regions in global coupled climate models with a focus on sea ice formation.
format Article in Journal/Newspaper
author Ionita, Monica
Grosfeld, Klaus
Scholz, Patrick
Treffeisen, Renate
Lohmann, Gerrit
spellingShingle Ionita, Monica
Grosfeld, Klaus
Scholz, Patrick
Treffeisen, Renate
Lohmann, Gerrit
September Arctic sea ice minimum prediction — a skillful new statistical approach
author_facet Ionita, Monica
Grosfeld, Klaus
Scholz, Patrick
Treffeisen, Renate
Lohmann, Gerrit
author_sort Ionita, Monica
title September Arctic sea ice minimum prediction — a skillful new statistical approach
title_short September Arctic sea ice minimum prediction — a skillful new statistical approach
title_full September Arctic sea ice minimum prediction — a skillful new statistical approach
title_fullStr September Arctic sea ice minimum prediction — a skillful new statistical approach
title_full_unstemmed September Arctic sea ice minimum prediction — a skillful new statistical approach
title_sort september arctic sea ice minimum prediction — a skillful new statistical approach
publisher Copernicus Publications
publishDate 2019
url https://epic.awi.de/id/eprint/49304/
https://epic.awi.de/id/eprint/49304/1/Ionita-ESD2019.pdf
https://www.earth-syst-dynam.net/10/189/2019/
https://hdl.handle.net/10013/epic.b00f0923-9e6f-40af-8a5c-30edc16804ec
https://hdl.handle.net/
geographic Arctic
geographic_facet Arctic
genre Arctic
Arctic
Climate change
Sea ice
genre_facet Arctic
Arctic
Climate change
Sea ice
op_source EPIC3Earth System Dynamics, Copernicus Publications, 10(1), pp. 189-203, ISSN: 2190-4979
op_relation https://epic.awi.de/id/eprint/49304/1/Ionita-ESD2019.pdf
https://hdl.handle.net/
Ionita, M. orcid:0000-0001-8240-4380 , Grosfeld, K. orcid:0000-0001-5936-179X , Scholz, P. orcid:0000-0003-2692-7624 , Treffeisen, R. and Lohmann, G. orcid:0000-0003-2089-733X (2019) September Arctic sea ice minimum prediction — a skillful new statistical approach , Earth System Dynamics, 10 (1), pp. 189-203 . doi:10.5194/esd-10-189-2019 <https://doi.org/10.5194/esd-10-189-2019> , hdl:10013/epic.b00f0923-9e6f-40af-8a5c-30edc16804ec
op_doi https://doi.org/10.5194/esd-10-189-2019
container_title Earth System Dynamics
container_volume 10
container_issue 1
container_start_page 189
op_container_end_page 203
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