Modeling the annual cycle of daily Antarctic sea ice extent

The total Antarctic sea ice extent (SIE) experiences a distinct annual cycle, peaking in September and reaching its minimum in February. In this paper we propose a mathematical and statistical decomposition of this temporal variation in SIE. Each component is interpretable and, when combined, gives...

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Published in:The Cryosphere
Main Authors: Handcock, Mark S., Raphael, Marilyn N.
Format: Text
Language:English
Published: 2020
Subjects:
Online Access:https://doi.org/10.5194/tc-14-2159-2020
https://tc.copernicus.org/articles/14/2159/2020/
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spelling ftcopernicus:oai:publications.copernicus.org:tc79800 2023-05-15T13:55:28+02:00 Modeling the annual cycle of daily Antarctic sea ice extent Handcock, Mark S. Raphael, Marilyn N. 2020-07-02 application/pdf https://doi.org/10.5194/tc-14-2159-2020 https://tc.copernicus.org/articles/14/2159/2020/ eng eng doi:10.5194/tc-14-2159-2020 https://tc.copernicus.org/articles/14/2159/2020/ eISSN: 1994-0424 Text 2020 ftcopernicus https://doi.org/10.5194/tc-14-2159-2020 2020-07-20T16:22:03Z The total Antarctic sea ice extent (SIE) experiences a distinct annual cycle, peaking in September and reaching its minimum in February. In this paper we propose a mathematical and statistical decomposition of this temporal variation in SIE. Each component is interpretable and, when combined, gives a complete picture of the variation in the sea ice. We consider timescales varying from the instantaneous and not previously defined to the multi-decadal curvilinear trend, the longest. Because our representation is daily, these timescales of variability give precise information about the timing and rates of advance and retreat of the ice and may be used to diagnose physical contributors to variability in the sea ice. We define a number of annual cycles each capturing different components of variation, especially the yearly amplitude and phase that are major contributors to SIE variation. Using daily sea ice concentration data, we show that our proposed invariant annual cycle explains 29 % more of the variation in daily SIE than the traditional method. The proposed annual cycle that incorporates amplitude and phase variation explains 77 % more variation than the traditional method. The variation in phase explains more of the variability in SIE than the amplitude. Using our methodology, we show that the anomalous decay of sea ice in 2016 was associated largely with a change of phase rather than amplitude. We show that the long term trend in Antarctic sea ice extent is strongly curvilinear and the reported positive linear trend is small and dependent strongly on a positive trend that began around 2011 and continued until 2016. Text Antarc* Antarctic Sea ice Copernicus Publications: E-Journals Antarctic The Cryosphere 14 7 2159 2172
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collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description The total Antarctic sea ice extent (SIE) experiences a distinct annual cycle, peaking in September and reaching its minimum in February. In this paper we propose a mathematical and statistical decomposition of this temporal variation in SIE. Each component is interpretable and, when combined, gives a complete picture of the variation in the sea ice. We consider timescales varying from the instantaneous and not previously defined to the multi-decadal curvilinear trend, the longest. Because our representation is daily, these timescales of variability give precise information about the timing and rates of advance and retreat of the ice and may be used to diagnose physical contributors to variability in the sea ice. We define a number of annual cycles each capturing different components of variation, especially the yearly amplitude and phase that are major contributors to SIE variation. Using daily sea ice concentration data, we show that our proposed invariant annual cycle explains 29 % more of the variation in daily SIE than the traditional method. The proposed annual cycle that incorporates amplitude and phase variation explains 77 % more variation than the traditional method. The variation in phase explains more of the variability in SIE than the amplitude. Using our methodology, we show that the anomalous decay of sea ice in 2016 was associated largely with a change of phase rather than amplitude. We show that the long term trend in Antarctic sea ice extent is strongly curvilinear and the reported positive linear trend is small and dependent strongly on a positive trend that began around 2011 and continued until 2016.
format Text
author Handcock, Mark S.
Raphael, Marilyn N.
spellingShingle Handcock, Mark S.
Raphael, Marilyn N.
Modeling the annual cycle of daily Antarctic sea ice extent
author_facet Handcock, Mark S.
Raphael, Marilyn N.
author_sort Handcock, Mark S.
title Modeling the annual cycle of daily Antarctic sea ice extent
title_short Modeling the annual cycle of daily Antarctic sea ice extent
title_full Modeling the annual cycle of daily Antarctic sea ice extent
title_fullStr Modeling the annual cycle of daily Antarctic sea ice extent
title_full_unstemmed Modeling the annual cycle of daily Antarctic sea ice extent
title_sort modeling the annual cycle of daily antarctic sea ice extent
publishDate 2020
url https://doi.org/10.5194/tc-14-2159-2020
https://tc.copernicus.org/articles/14/2159/2020/
geographic Antarctic
geographic_facet Antarctic
genre Antarc*
Antarctic
Sea ice
genre_facet Antarc*
Antarctic
Sea ice
op_source eISSN: 1994-0424
op_relation doi:10.5194/tc-14-2159-2020
https://tc.copernicus.org/articles/14/2159/2020/
op_doi https://doi.org/10.5194/tc-14-2159-2020
container_title The Cryosphere
container_volume 14
container_issue 7
container_start_page 2159
op_container_end_page 2172
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