Validation of SMOS sea ice thickness retrieval in the northern Baltic Sea
The Soil Moisture and Ocean Salinity (SMOS) mission observes brightness temperatures at a low microwave frequency of 1.4 GHz (L-band) with a daily coverage of the polar regions. L-band radiometry has been shown to provide information on the thickness of thin sea ice. Here, we apply a new emission mo...
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ftawi:oai:epic.awi.de:37298 2023-05-15T15:12:11+02:00 Validation of SMOS sea ice thickness retrieval in the northern Baltic Sea Maaß, Nina Kaleschke, Lars Tian-Kunze, Xiangshan Mäkynen, Marko Drusch, Matthias Krumpen, Thomas Hendricks, Stefan Lensu, Mikko Haapala, Jari Haas, Christian 2015-02 https://epic.awi.de/id/eprint/37298/ http://www.tellusa.net/index.php/tellusa/article/view/24617 https://hdl.handle.net/10013/epic.44983 unknown Co-Action Publishing Maaß, N. , Kaleschke, L. , Tian-Kunze, X. , Mäkynen, M. , Drusch, M. , Krumpen, T. orcid:0000-0001-6234-8756 , Hendricks, S. orcid:0000-0002-1412-3146 , Lensu, M. , Haapala, J. and Haas, C. orcid:0000-0002-7674-3500 (2015) Validation of SMOS sea ice thickness retrieval in the northern Baltic Sea , Tellus Series A-Dynamic Meteorology and Oceanography, 67 (24617) . doi:10.3402/tellusa.v67.24617 <https://doi.org/10.3402/tellusa.v67.24617> , hdl:10013/epic.44983 EPIC3Tellus Series A-Dynamic Meteorology and Oceanography, Co-Action Publishing, 67(24617), ISSN: 1600-0870 Article isiRev 2015 ftawi https://doi.org/10.3402/tellusa.v67.24617 2021-12-24T15:40:14Z The Soil Moisture and Ocean Salinity (SMOS) mission observes brightness temperatures at a low microwave frequency of 1.4 GHz (L-band) with a daily coverage of the polar regions. L-band radiometry has been shown to provide information on the thickness of thin sea ice. Here, we apply a new emission model that has previously been used to investigate the impact of snow on thick Arctic sea ice. The model has not yet been used to retrieve ice thickness. In contrast to previous SMOS ice thickness retrievals, the new model allows us to include a snow layer in the brightness temperature simulations. Using ice thickness estimations from satellite thermal imagery, we simulate brightness temperatures during the ice growth season 2011 in the northern Baltic Sea. In both the simulations and the SMOS observations, brightness temperatures increase by more than 20 K, most likely due to an increase of ice thickness. Only if we include the snow in the model, the absolute values of the simulations and the observations agree well (mean deviations below 3.5 K). In a second comparison, we use high-resolution measurements of total ice thickness (sum of ice and snow thickness) from an electromagnetic (EM) sounding system to simulate brightness temperatures for 12 circular areas. While the SMOS observations and the simulations that use the EM modal ice thickness are highly correlated (r2=0.95), the simulated brightness temperatures are on average 12 K higher than observed by SMOS. This would correspond to an 8-cm overestimation of the modal ice thickness by the SMOS retrieval. In contrast, if the simulations take into account the shape of the EM ice thickness distributions (r2=0.87), the mean deviation between simulated and observed brightness temperatures is below 0.1 K. Article in Journal/Newspaper Arctic Sea ice Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) Arctic Tellus A: Dynamic Meteorology and Oceanography 67 1 24617 |
institution |
Open Polar |
collection |
Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) |
op_collection_id |
ftawi |
language |
unknown |
description |
The Soil Moisture and Ocean Salinity (SMOS) mission observes brightness temperatures at a low microwave frequency of 1.4 GHz (L-band) with a daily coverage of the polar regions. L-band radiometry has been shown to provide information on the thickness of thin sea ice. Here, we apply a new emission model that has previously been used to investigate the impact of snow on thick Arctic sea ice. The model has not yet been used to retrieve ice thickness. In contrast to previous SMOS ice thickness retrievals, the new model allows us to include a snow layer in the brightness temperature simulations. Using ice thickness estimations from satellite thermal imagery, we simulate brightness temperatures during the ice growth season 2011 in the northern Baltic Sea. In both the simulations and the SMOS observations, brightness temperatures increase by more than 20 K, most likely due to an increase of ice thickness. Only if we include the snow in the model, the absolute values of the simulations and the observations agree well (mean deviations below 3.5 K). In a second comparison, we use high-resolution measurements of total ice thickness (sum of ice and snow thickness) from an electromagnetic (EM) sounding system to simulate brightness temperatures for 12 circular areas. While the SMOS observations and the simulations that use the EM modal ice thickness are highly correlated (r2=0.95), the simulated brightness temperatures are on average 12 K higher than observed by SMOS. This would correspond to an 8-cm overestimation of the modal ice thickness by the SMOS retrieval. In contrast, if the simulations take into account the shape of the EM ice thickness distributions (r2=0.87), the mean deviation between simulated and observed brightness temperatures is below 0.1 K. |
format |
Article in Journal/Newspaper |
author |
Maaß, Nina Kaleschke, Lars Tian-Kunze, Xiangshan Mäkynen, Marko Drusch, Matthias Krumpen, Thomas Hendricks, Stefan Lensu, Mikko Haapala, Jari Haas, Christian |
spellingShingle |
Maaß, Nina Kaleschke, Lars Tian-Kunze, Xiangshan Mäkynen, Marko Drusch, Matthias Krumpen, Thomas Hendricks, Stefan Lensu, Mikko Haapala, Jari Haas, Christian Validation of SMOS sea ice thickness retrieval in the northern Baltic Sea |
author_facet |
Maaß, Nina Kaleschke, Lars Tian-Kunze, Xiangshan Mäkynen, Marko Drusch, Matthias Krumpen, Thomas Hendricks, Stefan Lensu, Mikko Haapala, Jari Haas, Christian |
author_sort |
Maaß, Nina |
title |
Validation of SMOS sea ice thickness retrieval in the northern Baltic Sea |
title_short |
Validation of SMOS sea ice thickness retrieval in the northern Baltic Sea |
title_full |
Validation of SMOS sea ice thickness retrieval in the northern Baltic Sea |
title_fullStr |
Validation of SMOS sea ice thickness retrieval in the northern Baltic Sea |
title_full_unstemmed |
Validation of SMOS sea ice thickness retrieval in the northern Baltic Sea |
title_sort |
validation of smos sea ice thickness retrieval in the northern baltic sea |
publisher |
Co-Action Publishing |
publishDate |
2015 |
url |
https://epic.awi.de/id/eprint/37298/ http://www.tellusa.net/index.php/tellusa/article/view/24617 https://hdl.handle.net/10013/epic.44983 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
EPIC3Tellus Series A-Dynamic Meteorology and Oceanography, Co-Action Publishing, 67(24617), ISSN: 1600-0870 |
op_relation |
Maaß, N. , Kaleschke, L. , Tian-Kunze, X. , Mäkynen, M. , Drusch, M. , Krumpen, T. orcid:0000-0001-6234-8756 , Hendricks, S. orcid:0000-0002-1412-3146 , Lensu, M. , Haapala, J. and Haas, C. orcid:0000-0002-7674-3500 (2015) Validation of SMOS sea ice thickness retrieval in the northern Baltic Sea , Tellus Series A-Dynamic Meteorology and Oceanography, 67 (24617) . doi:10.3402/tellusa.v67.24617 <https://doi.org/10.3402/tellusa.v67.24617> , hdl:10013/epic.44983 |
op_doi |
https://doi.org/10.3402/tellusa.v67.24617 |
container_title |
Tellus A: Dynamic Meteorology and Oceanography |
container_volume |
67 |
container_issue |
1 |
container_start_page |
24617 |
_version_ |
1766342902599909376 |