A simple model for daily basin-wide thermodynamic sea ice thickness growth retrieval
As changes to Earth's polar climate accelerate, the need for robust, long–term sea ice thickness observation datasets for monitoring those changes and for verification of global climate models is clear. By linking an algorithm for retrieving snow–ice interface temperature from passive microwave...
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Online Access: | https://doi.org/10.5194/tc-16-4403-2022 https://tc.copernicus.org/articles/16/4403/2022/ |
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ftcopernicus:oai:publications.copernicus.org:tc98599 2023-05-15T15:08:16+02:00 A simple model for daily basin-wide thermodynamic sea ice thickness growth retrieval Anheuser, James Liu, Yinghui Key, Jeffrey R. 2022-10-20 application/pdf https://doi.org/10.5194/tc-16-4403-2022 https://tc.copernicus.org/articles/16/4403/2022/ eng eng doi:10.5194/tc-16-4403-2022 https://tc.copernicus.org/articles/16/4403/2022/ eISSN: 1994-0424 Text 2022 ftcopernicus https://doi.org/10.5194/tc-16-4403-2022 2022-10-24T16:22:41Z As changes to Earth's polar climate accelerate, the need for robust, long–term sea ice thickness observation datasets for monitoring those changes and for verification of global climate models is clear. By linking an algorithm for retrieving snow–ice interface temperature from passive microwave satellite data to a thermodynamic sea ice energy balance relation known as Stefan's law, we have developed a retrieval method for estimating thermodynamic sea ice thickness growth from space: Stefan's Law Integrated Conducted Energy (SLICE). With an initial condition at the beginning of the sea ice growth season, the method can model basin-wide absolute sea ice thickness by combining the one-dimensional SLICE retrieval with an ice motion dataset. The advantages of the SLICE retrieval method include daily basin-wide coverage, lack of atmospheric reanalysis product input requirement, and a potential for use beginning in 1987. Validation of the retrieval against measurements from 10 ice mass balance buoys shows a mean correlation of 0.89 and a mean bias of 0.06 m over the course of an entire sea ice growth season. Despite its simplifications and assumptions relative to models like the Pan-Arctic Ice–Ocean Modeling and Assimilation System (PIOMAS), basin-wide SLICE performs nearly as well as PIOMAS when compared against CryoSat-2 and Operation IceBridge using a linear correlation between collocated points. Text Arctic Sea ice Copernicus Publications: E-Journals Arctic The Cryosphere 16 10 4403 4421 |
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Open Polar |
collection |
Copernicus Publications: E-Journals |
op_collection_id |
ftcopernicus |
language |
English |
description |
As changes to Earth's polar climate accelerate, the need for robust, long–term sea ice thickness observation datasets for monitoring those changes and for verification of global climate models is clear. By linking an algorithm for retrieving snow–ice interface temperature from passive microwave satellite data to a thermodynamic sea ice energy balance relation known as Stefan's law, we have developed a retrieval method for estimating thermodynamic sea ice thickness growth from space: Stefan's Law Integrated Conducted Energy (SLICE). With an initial condition at the beginning of the sea ice growth season, the method can model basin-wide absolute sea ice thickness by combining the one-dimensional SLICE retrieval with an ice motion dataset. The advantages of the SLICE retrieval method include daily basin-wide coverage, lack of atmospheric reanalysis product input requirement, and a potential for use beginning in 1987. Validation of the retrieval against measurements from 10 ice mass balance buoys shows a mean correlation of 0.89 and a mean bias of 0.06 m over the course of an entire sea ice growth season. Despite its simplifications and assumptions relative to models like the Pan-Arctic Ice–Ocean Modeling and Assimilation System (PIOMAS), basin-wide SLICE performs nearly as well as PIOMAS when compared against CryoSat-2 and Operation IceBridge using a linear correlation between collocated points. |
format |
Text |
author |
Anheuser, James Liu, Yinghui Key, Jeffrey R. |
spellingShingle |
Anheuser, James Liu, Yinghui Key, Jeffrey R. A simple model for daily basin-wide thermodynamic sea ice thickness growth retrieval |
author_facet |
Anheuser, James Liu, Yinghui Key, Jeffrey R. |
author_sort |
Anheuser, James |
title |
A simple model for daily basin-wide thermodynamic sea ice thickness growth retrieval |
title_short |
A simple model for daily basin-wide thermodynamic sea ice thickness growth retrieval |
title_full |
A simple model for daily basin-wide thermodynamic sea ice thickness growth retrieval |
title_fullStr |
A simple model for daily basin-wide thermodynamic sea ice thickness growth retrieval |
title_full_unstemmed |
A simple model for daily basin-wide thermodynamic sea ice thickness growth retrieval |
title_sort |
simple model for daily basin-wide thermodynamic sea ice thickness growth retrieval |
publishDate |
2022 |
url |
https://doi.org/10.5194/tc-16-4403-2022 https://tc.copernicus.org/articles/16/4403/2022/ |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
eISSN: 1994-0424 |
op_relation |
doi:10.5194/tc-16-4403-2022 https://tc.copernicus.org/articles/16/4403/2022/ |
op_doi |
https://doi.org/10.5194/tc-16-4403-2022 |
container_title |
The Cryosphere |
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16 |
container_issue |
10 |
container_start_page |
4403 |
op_container_end_page |
4421 |
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1766339653334466560 |