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 the first demonstration study, sea ice thickness up to 50 cm has been derived us...
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fttriple:oai:gotriple.eu:oai:doaj.org/article:4b8cb5b90c164937933bd65609dcb174 2023-05-15T15:07:49+02:00 SMOS-derived thin sea ice thickness: algorithm baseline, product specifications and initial verification X. Tian-Kunze L. Kaleschke N. Maaß M. Mäkynen N. Serra M. Drusch T. Krumpen 2014-05-01 https://doi.org/10.5194/tc-8-997-2014 http://www.the-cryosphere.net/8/997/2014/tc-8-997-2014.pdf https://doaj.org/article/4b8cb5b90c164937933bd65609dcb174 en eng Copernicus Publications 1994-0416 1994-0424 doi:10.5194/tc-8-997-2014 http://www.the-cryosphere.net/8/997/2014/tc-8-997-2014.pdf https://doaj.org/article/4b8cb5b90c164937933bd65609dcb174 undefined The Cryosphere, Vol 8, Iss 3, Pp 997-1018 (2014) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2014 fttriple https://doi.org/10.5194/tc-8-997-2014 2023-01-22T19:27:58Z 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 the first demonstration study, sea ice thickness up to 50 cm 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 thermodynamic sea ice 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 the SMOS spatial resolution 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. The data set is compared to 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 (Kaleschke et al., 2012). Article in Journal/Newspaper Arctic Sea ice The Cryosphere Unknown Arctic The Cryosphere 8 3 997 1018 |
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geo envir X. Tian-Kunze L. Kaleschke N. Maaß M. Mäkynen N. Serra M. Drusch T. Krumpen SMOS-derived thin sea ice thickness: algorithm baseline, product specifications and initial verification |
topic_facet |
geo envir |
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 the first demonstration study, sea ice thickness up to 50 cm 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 thermodynamic sea ice 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 the SMOS spatial resolution 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. The data set is compared to 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 (Kaleschke et al., 2012). |
format |
Article in Journal/Newspaper |
author |
X. Tian-Kunze L. Kaleschke N. Maaß M. Mäkynen N. Serra M. Drusch T. Krumpen |
author_facet |
X. Tian-Kunze L. Kaleschke N. Maaß M. Mäkynen N. Serra M. Drusch T. Krumpen |
author_sort |
X. Tian-Kunze |
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 |
publisher |
Copernicus Publications |
publishDate |
2014 |
url |
https://doi.org/10.5194/tc-8-997-2014 http://www.the-cryosphere.net/8/997/2014/tc-8-997-2014.pdf https://doaj.org/article/4b8cb5b90c164937933bd65609dcb174 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice The Cryosphere |
genre_facet |
Arctic Sea ice The Cryosphere |
op_source |
The Cryosphere, Vol 8, Iss 3, Pp 997-1018 (2014) |
op_relation |
1994-0416 1994-0424 doi:10.5194/tc-8-997-2014 http://www.the-cryosphere.net/8/997/2014/tc-8-997-2014.pdf https://doaj.org/article/4b8cb5b90c164937933bd65609dcb174 |
op_rights |
undefined |
op_doi |
https://doi.org/10.5194/tc-8-997-2014 |
container_title |
The Cryosphere |
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8 |
container_issue |
3 |
container_start_page |
997 |
op_container_end_page |
1018 |
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