SMOS-derived thin sea ice thickness: algorithm baseline, product specifications and initial verification

Following the launch of ESA's Soil Moisture and Ocean salinity (SMOS) mission it has been shown that brightness temperatures at a low microwave frequency of 1.4 GHz (L-band) are sensitive to sea ice properties. In a first demonstration study, sea ice thickness has been derived using a semi-empi...

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Published in:The Cryosphere
Main Authors: Tian-Kunze, X., Kaleschke, L., Maaß, N., Mäkynen, M., Serra, N., Drusch, M., Krumpen, T.
Format: Article in Journal/Newspaper
Language:English
Published: 2014
Subjects:
Online Access:http://hdl.handle.net/11858/00-001M-0000-0023-FCD2-1
http://hdl.handle.net/11858/00-001M-0000-0024-B8EB-F
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spelling ftpubman:oai:pure.mpg.de:item_2065599 2024-09-09T19:25:56+00:00 SMOS-derived thin sea ice thickness: algorithm baseline, product specifications and initial verification Tian-Kunze, X. Kaleschke, L. Maaß, N. Mäkynen, M. Serra, N. Drusch, M. Krumpen, T. 2014-05-27 application/pdf http://hdl.handle.net/11858/00-001M-0000-0023-FCD2-1 http://hdl.handle.net/11858/00-001M-0000-0024-B8EB-F eng eng info:eu-repo/semantics/altIdentifier/doi/10.5194/tc-8-997-2014 http://hdl.handle.net/11858/00-001M-0000-0023-FCD2-1 http://hdl.handle.net/11858/00-001M-0000-0024-B8EB-F info:eu-repo/semantics/openAccess The Cryosphere info:eu-repo/semantics/article 2014 ftpubman https://doi.org/10.5194/tc-8-997-2014 2024-07-31T09:31:29Z Following the launch of ESA's Soil Moisture and Ocean salinity (SMOS) mission it has been shown that brightness temperatures at a low microwave frequency of 1.4 GHz (L-band) are sensitive to sea ice properties. In a first demonstration study, sea ice thickness has been derived using a semi-empirical algorithm with constant tie-points. Here we introduce a novel iterative retrieval algorithm that is based on a sea ice thermodynamic model and a three-layer radiative transfer model, which explicitly takes variations of ice temperature and ice salinity into account. In addition, ice thickness variations within a SMOS footprint are considered through a statistical thickness distribution function derived from high-resolution ice thickness measurements from NASA's Operation IceBridge campaign. This new algorithm has been used for the continuous operational production of a SMOS based sea ice thickness data set from 2010 on. This data set is compared and validated with estimates from assimilation systems, remote sensing data, and airborne electromagnetic sounding data. The comparisons show that the new retrieval algorithm has a considerably better agreement with the validation data and delivers a more realistic Arctic-wide ice thickness distribution than the algorithm used in the previous study. Article in Journal/Newspaper Arctic Sea ice The Cryosphere Max Planck Society: MPG.PuRe Arctic The Cryosphere 8 3 997 1018
institution Open Polar
collection Max Planck Society: MPG.PuRe
op_collection_id ftpubman
language English
description Following the launch of ESA's Soil Moisture and Ocean salinity (SMOS) mission it has been shown that brightness temperatures at a low microwave frequency of 1.4 GHz (L-band) are sensitive to sea ice properties. In a first demonstration study, sea ice thickness has been derived using a semi-empirical algorithm with constant tie-points. Here we introduce a novel iterative retrieval algorithm that is based on a sea ice thermodynamic model and a three-layer radiative transfer model, which explicitly takes variations of ice temperature and ice salinity into account. In addition, ice thickness variations within a SMOS footprint are considered through a statistical thickness distribution function derived from high-resolution ice thickness measurements from NASA's Operation IceBridge campaign. This new algorithm has been used for the continuous operational production of a SMOS based sea ice thickness data set from 2010 on. This data set is compared and validated with estimates from assimilation systems, remote sensing data, and airborne electromagnetic sounding data. The comparisons show that the new retrieval algorithm has a considerably better agreement with the validation data and delivers a more realistic Arctic-wide ice thickness distribution than the algorithm used in the previous study.
format Article in Journal/Newspaper
author Tian-Kunze, X.
Kaleschke, L.
Maaß, N.
Mäkynen, M.
Serra, N.
Drusch, M.
Krumpen, T.
spellingShingle Tian-Kunze, X.
Kaleschke, L.
Maaß, N.
Mäkynen, M.
Serra, N.
Drusch, M.
Krumpen, T.
SMOS-derived thin sea ice thickness: algorithm baseline, product specifications and initial verification
author_facet Tian-Kunze, X.
Kaleschke, L.
Maaß, N.
Mäkynen, M.
Serra, N.
Drusch, M.
Krumpen, T.
author_sort Tian-Kunze, X.
title SMOS-derived thin sea ice thickness: algorithm baseline, product specifications and initial verification
title_short SMOS-derived thin sea ice thickness: algorithm baseline, product specifications and initial verification
title_full SMOS-derived thin sea ice thickness: algorithm baseline, product specifications and initial verification
title_fullStr SMOS-derived thin sea ice thickness: algorithm baseline, product specifications and initial verification
title_full_unstemmed SMOS-derived thin sea ice thickness: algorithm baseline, product specifications and initial verification
title_sort smos-derived thin sea ice thickness: algorithm baseline, product specifications and initial verification
publishDate 2014
url http://hdl.handle.net/11858/00-001M-0000-0023-FCD2-1
http://hdl.handle.net/11858/00-001M-0000-0024-B8EB-F
geographic Arctic
geographic_facet Arctic
genre Arctic
Sea ice
The Cryosphere
genre_facet Arctic
Sea ice
The Cryosphere
op_source The Cryosphere
op_relation info:eu-repo/semantics/altIdentifier/doi/10.5194/tc-8-997-2014
http://hdl.handle.net/11858/00-001M-0000-0023-FCD2-1
http://hdl.handle.net/11858/00-001M-0000-0024-B8EB-F
op_rights info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.5194/tc-8-997-2014
container_title The Cryosphere
container_volume 8
container_issue 3
container_start_page 997
op_container_end_page 1018
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