A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data
Sea-ice thickness on a global scale is derived from different satellite sensors using independent retrieval methods. Due to the sensor and orbit characteristics, such satellite retrievals differ in spatial and temporal resolution as well as in the sensitivity to certain sea-ice types and thickness r...
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Copernicus Publications
2017
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ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00009660 2023-05-15T14:56:36+02:00 A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data Ricker, Robert Hendricks, Stefan Kaleschke, Lars Tian-Kunze, Xiangshan King, Jennifer Haas, Christian 2017-07 electronic https://doi.org/10.5194/tc-11-1607-2017 https://noa.gwlb.de/receive/cop_mods_00009660 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00009617/tc-11-1607-2017.pdf https://tc.copernicus.org/articles/11/1607/2017/tc-11-1607-2017.pdf eng eng Copernicus Publications The Cryosphere -- ˜Theœ Cryosphere -- http://www.bibliothek.uni-regensburg.de/ezeit/?2393169 -- http://www.the-cryosphere.net/ -- 1994-0424 https://doi.org/10.5194/tc-11-1607-2017 https://noa.gwlb.de/receive/cop_mods_00009660 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00009617/tc-11-1607-2017.pdf https://tc.copernicus.org/articles/11/1607/2017/tc-11-1607-2017.pdf uneingeschränkt info:eu-repo/semantics/openAccess article Verlagsveröffentlichung article Text doc-type:article 2017 ftnonlinearchiv https://doi.org/10.5194/tc-11-1607-2017 2022-02-08T22:57:27Z Sea-ice thickness on a global scale is derived from different satellite sensors using independent retrieval methods. Due to the sensor and orbit characteristics, such satellite retrievals differ in spatial and temporal resolution as well as in the sensitivity to certain sea-ice types and thickness ranges. Satellite altimeters, such as CryoSat-2 (CS2), sense the height of the ice surface above the sea level, which can be converted into sea-ice thickness. Relative uncertainties associated with this method are large over thin ice regimes. Another retrieval method is based on the evaluation of surface brightness temperature (TB) in L-band microwave frequencies (1.4 GHz) with a thickness-dependent emission model, as measured by the Soil Moisture and Ocean Salinity (SMOS) satellite. While the radiometer-based method looses sensitivity for thick sea ice (> 1 m), relative uncertainties over thin ice are significantly smaller than for the altimetry-based retrievals. In addition, the SMOS product provides global sea-ice coverage on a daily basis unlike the altimeter data. This study presents the first merged product of complementary weekly Arctic sea-ice thickness data records from the CS2 altimeter and SMOS radiometer. We use two merging approaches: a weighted mean (WM) and an optimal interpolation (OI) scheme. While the weighted mean leaves gaps between CS2 orbits, OI is used to produce weekly Arctic-wide sea-ice thickness fields. The benefit of the data merging is shown by a comparison with airborne electromagnetic (AEM) induction sounding measurements. When compared to airborne thickness data in the Barents Sea, the merged product has a root mean square deviation (RMSD) of about 0.7 m less than the CS2 product and therefore demonstrates the capability to enhance the CS2 product in thin ice regimes. However, in mixed first-year (FYI) and multiyear (MYI) ice regimes as in the Beaufort Sea, the CS2 retrieval shows the lowest bias. Article in Journal/Newspaper Arctic Barents Sea Beaufort Sea Sea ice The Cryosphere Niedersächsisches Online-Archiv NOA Arctic Barents Sea The Cryosphere 11 4 1607 1623 |
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English |
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article Verlagsveröffentlichung |
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article Verlagsveröffentlichung Ricker, Robert Hendricks, Stefan Kaleschke, Lars Tian-Kunze, Xiangshan King, Jennifer Haas, Christian A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data |
topic_facet |
article Verlagsveröffentlichung |
description |
Sea-ice thickness on a global scale is derived from different satellite sensors using independent retrieval methods. Due to the sensor and orbit characteristics, such satellite retrievals differ in spatial and temporal resolution as well as in the sensitivity to certain sea-ice types and thickness ranges. Satellite altimeters, such as CryoSat-2 (CS2), sense the height of the ice surface above the sea level, which can be converted into sea-ice thickness. Relative uncertainties associated with this method are large over thin ice regimes. Another retrieval method is based on the evaluation of surface brightness temperature (TB) in L-band microwave frequencies (1.4 GHz) with a thickness-dependent emission model, as measured by the Soil Moisture and Ocean Salinity (SMOS) satellite. While the radiometer-based method looses sensitivity for thick sea ice (> 1 m), relative uncertainties over thin ice are significantly smaller than for the altimetry-based retrievals. In addition, the SMOS product provides global sea-ice coverage on a daily basis unlike the altimeter data. This study presents the first merged product of complementary weekly Arctic sea-ice thickness data records from the CS2 altimeter and SMOS radiometer. We use two merging approaches: a weighted mean (WM) and an optimal interpolation (OI) scheme. While the weighted mean leaves gaps between CS2 orbits, OI is used to produce weekly Arctic-wide sea-ice thickness fields. The benefit of the data merging is shown by a comparison with airborne electromagnetic (AEM) induction sounding measurements. When compared to airborne thickness data in the Barents Sea, the merged product has a root mean square deviation (RMSD) of about 0.7 m less than the CS2 product and therefore demonstrates the capability to enhance the CS2 product in thin ice regimes. However, in mixed first-year (FYI) and multiyear (MYI) ice regimes as in the Beaufort Sea, the CS2 retrieval shows the lowest bias. |
format |
Article in Journal/Newspaper |
author |
Ricker, Robert Hendricks, Stefan Kaleschke, Lars Tian-Kunze, Xiangshan King, Jennifer Haas, Christian |
author_facet |
Ricker, Robert Hendricks, Stefan Kaleschke, Lars Tian-Kunze, Xiangshan King, Jennifer Haas, Christian |
author_sort |
Ricker, Robert |
title |
A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data |
title_short |
A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data |
title_full |
A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data |
title_fullStr |
A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data |
title_full_unstemmed |
A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data |
title_sort |
weekly arctic sea-ice thickness data record from merged cryosat-2 and smos satellite data |
publisher |
Copernicus Publications |
publishDate |
2017 |
url |
https://doi.org/10.5194/tc-11-1607-2017 https://noa.gwlb.de/receive/cop_mods_00009660 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00009617/tc-11-1607-2017.pdf https://tc.copernicus.org/articles/11/1607/2017/tc-11-1607-2017.pdf |
geographic |
Arctic Barents Sea |
geographic_facet |
Arctic Barents Sea |
genre |
Arctic Barents Sea Beaufort Sea Sea ice The Cryosphere |
genre_facet |
Arctic Barents Sea Beaufort Sea Sea ice The Cryosphere |
op_relation |
The Cryosphere -- ˜Theœ Cryosphere -- http://www.bibliothek.uni-regensburg.de/ezeit/?2393169 -- http://www.the-cryosphere.net/ -- 1994-0424 https://doi.org/10.5194/tc-11-1607-2017 https://noa.gwlb.de/receive/cop_mods_00009660 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00009617/tc-11-1607-2017.pdf https://tc.copernicus.org/articles/11/1607/2017/tc-11-1607-2017.pdf |
op_rights |
uneingeschränkt info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5194/tc-11-1607-2017 |
container_title |
The Cryosphere |
container_volume |
11 |
container_issue |
4 |
container_start_page |
1607 |
op_container_end_page |
1623 |
_version_ |
1766328689185783808 |